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I just got a crash course in researching in Claude Code. When creating my two-part State of Marketing Report on 100 B2B companies, I thought I’d spend my normal 20-30 hours per newsletter building these out. I spent way, way longer. But the good news is: I learned so much that I wrote this third newsletter, to save you the time I lost figuring it all out.

I learned about Claude Code’s convoluted “memory,” how to pick the right methodology for researching each data point, when to use and when to avoid using MCPs for research, when to yell at Claude for making up fake numbers, why sites rendered in JavaScript mess up research (and AEO), how to use Claude artifacts to find interesting insights faster, what “curl” and “bash” actually mean, and more.

If you have no idea what any of that means, you will after reading this newsletter—and it’ll save you a ton of time when doing research at any scale in Claude Code, from gathering basic competitive intel on a few companies to building a full data report across hundreds of data points like I did.

There’s also a bigger thought running underneath all of this. After building this report, I’m convinced Claude isn’t just going to help you make content or get cited in LLM answers—it’s also a direct way to distribute content to your buyers. We published this report as a skill on the MKT1 MCP Server because we believe pushing high-value resources (not just product functionality) to LLMs will become a primary way to reach your audience. More on that in the final section of this newsletter.

Now let’s get to it…but first I’ll thank sponsors, share what’s in this newsletter, and tell you more about our next Buildathon on 5/27!

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In this newsletter:

This newsletter covers how to do research in Claude Code and is organized by the scale of research you are doing—from just your company, to a small group, all the way up to building a massive, publishable report.

• 🪞 Part 1: How (and why) to research your own company with Claude Code

• 🍿 Intermission: Learn how Claude Code remembers and saves info

• 🏟️ Part 2: How to research a group of companies—competitors, complements, prospects, or companies you admire

• 📊 Part 3: How to build a research report you can publish with Claude Code

• ⛽ Final thoughts: How Claude is becoming both fuel & engine

This newsletter is part 3 of a 3-part series on the State of B2B Marketing, to see all the graphs and stats I pulled in my research check them out here:

• Part 1: State of B2B Marketing Teams

• Part 2: State of B2B Marketing Activities

• Part 3: This newsletter - Researching companies in Claude Code

Bonus for paid subscribers: 3 skills related to this research & report in the MKT1 MCP Server:

• /mkt1-competitive-research: Run competitive research for any set of companies. Creates a spreadsheet to track data and includes common data points and queries like positioning, pricing, GTM motion, exec team, and AEO readiness.

• /mkt1-state-of-b2b-marketing-data: Query the full dataset behind this report: 100 high-growth B2B startups, 90+ data points each, covering GTM motion, team composition, social, ads, homepages, CMS, conversion, and AEO readiness.

• /mkt1-high-growth-b2b-company-list: My curated list of high-growth B2B companies ready as a reference set. Run quick research across a solid list of companies instead of starting from scratch.

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We’ll cover all these lessons and more in the newsletter below.

Part 1: How (and why) to research your own company with Claude Code

The best way to start doing research in Claude Code is with your own company. Not only will you learn what info is easy to get (and what's shockingly hard), but you'll also do an AEO audit for your company in the process. If you can't scrape the basics about your company, that means the LLMs can't read your site.

This step is also the precursor to everything else in this newsletter, from running competitive research to building full research reports. Nail the methodology on one company and you'll know what to ask for at every scale after.

How to do the research:

1. Run an “incognito-style” session in Claude Code Desktop. Claude Code Desktop doesn’t have a native incognito feature, so you fake it: In the prompt itself, tell Claude to only use what’s publicly available, as if it’s encountering your company for the first time. Or better yet, you can start a new session in an empty project folder (pick a blank folder on your desktop), so no skills or memory get loaded at all.
   Note: Claude Chat does have an Actual Incognito Mode, click the ghost icon in the top right.

2. Prompt Claude to do research on your own company to nail down research methods and to find the gaps where your company isn’t showing up. A good prompt covers four things:

   • Asks Claude to pull a wide range of data points (pricing, customer logos, recent launches, new hires, positioning)

   • Asks Claude to fetch your homepage and tell you what an LLM can vs. can’t read from it (so you catch JS-rendered content)

   • Asks Claude to check the AEO basics, including homepage schema and your robots.txt for LLM crawler rules

   • Asks for a summary: what to fix on your site, what was hardest to pull, and what methods it used to pull information

3. Ask Claude to save this as a reusable skill so you can run the same research on other companies later—competitors, partners, target accounts.

Here are the prompts you can copy & paste into Claude Code:

Prompt 1: Ask Claude Code to research your company

Pretend you’ve never heard of my company at [URL] and only use what you can find on the public web, like an LLM crawler hitting my site for the first time. Then:

1. Pull what you can find on my company: pricing, customer logos, recent launches, new hires, blog post activity, headline copy, positioning, exec team.

2. As you research each data point, tell me how you found it. If you can’t find something easily, stop and tell me what the challenge is.

3. Audit the AEO basics: fetch my homepage (flag JS-rendered content), check the schema, and read my robots.txt for LLM crawler rules.

4. Summarize what was easy, hard, and impossible, what methods you used, and what I should fix on my site.

Prompt 2: Save the skill to use again

Save what we just did as a skill called company-research-skill.

Include the prompts and data points we researched and the methodologies that worked.

Make it reusable for any company URL.

What I learned:

Lesson: Researching your own company doubles as an AEO audit

Doing research on any company in an LLM doubles as an accidental AEO audit (AEO = Answer Engine Optimization, the LLM equivalent of SEO). If it’s not easy to find basic information, something’s off with the AEO, usually with how the site is set up. I noticed this while building the 100-company report. For some companies, Claude Code came back with almost nothing useful, which made me wonder why their info was so hard to find.

So I looked closer at the AEO specifics, specifically at what their site was built on, how it was rendered, what AEO best practices were being followed, and what schema was on the page.

• The reason I couldn’t get basic info from many pages (like whether a homepage mentions “AI” or the most recent blog post publish date): Many sites load content in JavaScript, not HTML. LLM crawlers don’t run JavaScript, so if your content isn’t in the HTML, the LLM sees an empty shell.

• I was also surprised to find many companies aren’t using proper schema on their site—a very quick AEO win to knock out. Schema is markup that tells LLMs what’s on the page; FAQSchema, for example, tells LLMs that there’s an FAQ on a page. Only 2% of startups have it, and 40% have no homepage schema at all. All stats are according to our State of Marketing report (part 1 and part 2) on 100 fast-growing companies, researched with Claude Code.

• Most of us know robots.txt is from SEO, but you should update it with your LLM crawler preferences. Almost all B2B startups (97%) allow LLM crawlers, but only 12% have actually written explicit rules for LLM bots in their robots.txt. You can ask Claude Code to check what your robots.txt currently does, and also to update it for you!

The smartest robots.txt move I saw in my research was Attio’s setup. They block CCBot (which feeds LLM training data), but allow GPTBot and ClaudeBot. Translation: “Don’t train on us, but DO cite us in real-time answers.”

Lesson: Always test on yourself before you scale

If you’re thinking about running competitive research or partner research or building a report (which we’ll cover later in this newsletter), start by researching yourself. Not only do you get some AEO learnings, but you also learn much faster what research is possible, what’s easy, and what takes forever. It’s much easier to spot-check research on your own company when you know it so well.

This is the right approach if you’re building anything reusable, like a competitor research skill. For one-off data about another company, you don’t need to test it on yourself first!

• Things you might try on your own company include: pricing and packaging, homepage copy, customer logos and case studies, recent product launches, and recent hires. Relatedly, if doing person-specific research, try it on yourself first. You’ll learn a lot about what Claude Code can do by trying this first.

• Some research takes longer than you’d think because the data isn’t as available as you’d assume. I was shocked by what took me forever. Even with the Clay MCP, around 10 CMOs were missing from the enriched data on the 100-company report, and Claude’s agent searches confidently surfaced executives who’d left their roles 1-3 years ago. My knowledge of who actually runs marketing at these companies came in clutch. Testing on your own company first surfaces gaps like these cheaply.

• The hard part of doing research is figuring out the right methodology, and Claude Code sometimes suggests hard paths when there are easy ones. I assumed the Clay MCP would be the fast path for a lot of this, but a plain curl (a command that fetches the raw HTML of a public web page) got me accurate LinkedIn follower numbers in under a minute. I didn’t even know what a curl was before this newsletter. Just say “use a curl” and Claude Code does it for you, no Chrome extension needed.

Add MKT1 to Claude Code with our MCP Server

Not only have I added new skills for research (like this week’s new competitive-research skill), but I’ve also updated many of our existing skills to include visual artifact templates and added a set of marketing recruiting skills.

Install the MCP Server

⚠️ Before you go any further…

Learn how Claude Code remembers and saves info

Before I get into how to research a group of companies, you have to understand how Claude Code remembers things. I didn’t, and it cost me.

I duplicated research prompts I should have saved as skills right away. I didn’t notice gaps in my data until I was deep into the report, because I’d been tracking it in a Claude Code session (aka the chat window) that eventually compressed. And I wasted credits running the same things multiple times. There are a bunch of terms that sound similar, and most people use them without knowing the difference. Adding to the confusion, the lingo and methods for saving and remembering things are different in Claude Chat and Claude Code. It’s a bit maddening, TBH. So here’s the table I wish I’d had at the start:

The bad news is, even when you use all these things perfectly, Claude Code doesn’t remember where to save and pull info from all the time. So, you have to actively direct Claude to save things in the right places. And then you have to remind it to reference those things.

I tell it things like “save this to my CLAUDE.md file,” “save this to a skill,” “create a row in the spreadsheet,” “update the skill to reference this spreadsheet or file” or even “tell CLAUDE.md to invoke this skill at this time).” These are prompts I use on a regular basis to keep things organized.

You never have to tell Claude to save to memory (it does that on its own), but I don’t trust it. When something’s only in memory, Claude doesn’t reliably reference it later. So I save to CLAUDE.md or a skill instead, because I created them, I wrote them, and I know what’s in there.

Is this all a little exhausting? Well yes, but once you get the hang of it it becomes almost second nature (emphasis on almost).

Part 2: How to research a group of companies

From competitors, complements, a target account list, or companies you admire

This section covers how to research a group of companies, whether researching your competitors, ecosystem partners, target customers, or just companies you’re trying to learn from. Most people will default to doing this for their competitors, but I always say: Imagine if you spent as much time thinking about your complements as your competitors. So, I highly recommend using this research workflow for potential partners to understand who they are and how they might be able to work with you.

How to do the research:

1. First up, get a list of canonical URLs you’ll be using in your research. You can either ask Claude for help sourcing relevant companies for you, list them out directly, or upload a CSV.

   If you aren’t sure what companies to use, you can use the mkt1-high-growth-b2b-company-list skill in our MCP server as a starting place.

2. Ask Claude to set up a skill for the research you’re doing and a corresponding spreadsheet to track all the data points and URLs. The skill is your repeatable instructions, your spreadsheet is the source of truth for the research itself.

3. Decide which data points you want to track. Common ones: pricing, positioning, customer logos, recent launches, new hires, exec team, GTM motion, headcount.

4. Run the research in batches, 1 data point at a time, 1 company to start. Then you can run it quickly on the rest.

5. Ask Claude Code to make a pdf report, battle card table, visual artifact—whatever you need. Once you get it exactly right, ask Claude to save it as a template referenced by the skill.

We have a skill for this in the MKT1 MCP!

Install the MKT1 MCP Server and run the mkt1-competitive-research skill. You can even duplicate it and ask Claude to make it an ecosystem skill to analyze your partners too. For paid subscribers only.

Here are the prompts you can copy & paste into Claude Code:

Prompt 1: Create your skill & spreadsheet

Take the “company-research” skill I already made and duplicate it as a new skill called [insert name, i.e. “competitive-research”]. Adapt it to work across a list of companies instead of one. The skill should:

• Ask me how I want to source the competitive companies (paste a list, ask you to find them, or upload a CSV).

• Set up a spreadsheet that will be the source of truth for the research, both any URLs and data points we need, and save the company URLs in it, one row per company.

• Suggest data points to track (common ones: pricing, positioning, customer logos, recent launches, new hires, exec team, GTM motion, headcount), work with me to lock them in, then add a column for each.

• If any data points need extra URLs to research (pricing page, LinkedIn page, third-party site), add those URLs as their own columns first and have me spot-check them before you start.

• Run the research one data point at a time across all companies, not company by company. Start with 1-2 companies for each data point to check the method, then run the full list. Don't run everything at once.

• Leave cells blank and flag them when something can't be found, instead of guessing or filling in plausible-sounding values. If a research method isn't working or is taking too long, try another and flag it to me.

• Include the prompts and data points we researched and the methodologies that worked.

• Make it reusable for any company URL.

Prompt 2: Run your new skill

Run the competitive-research skill. I want to compare my company against [3-5 competitors]. Focus on [pricing, positioning, customer logos, recent launches]. Run it for 1 company first and show me the results so we can update the process or data points if needed before continuing.

What I learned:

Lesson: Use a spreadsheet as your source of truth for research

Before doing research on a group of companies, you need to build a spreadsheet to hold it all. You might be thinking “I’m using Claude Code for research because I don’t want to make a spreadsheet!” Valid.

But in this case, Claude Code can make the sheet for you, save info to it, and reference it...you never even have to look at it. I only looked at mine once or twice when building my State of Marketing research report (it was 101 rows and 100 columns, so I’m very happy about that).

Here’s what I learned, and what you should do even if you’re only researching a few companies:

• If you ask Claude to research a bunch of companies across a bunch of data points all at once, you’ll get answers fast, but they won’t be right. When you try to fix the mess piece by piece, you end up with an even bigger mess.

• Instead, have Claude make a spreadsheet at the start of your research. The first column is the company name. Then have Claude research the URLs and add to the second column (or add them yourself, depending on the number).

• Then for every data point you want to research, have Claude add another column. Go column by column. For each data point, figure out the right approach first (Claude Code’s plan mode helps), test it on a couple of companies, spot-check the answer, then run it across all of them. As Claude researches, it can reference the columns it’s already filled in to help.

• If any step involves scraping or checking a URL, it 100% needs to be a column. LinkedIn handle, pricing page, careers page, blog, etc, whatever the skill is going to hit. If you let Claude guess the URL from the company name when it’s researching a data point, it gets messy when it can’t find the right url—and may lead to fake data.

• When you want to add more companies, more data points, or fresher data later, you reference the spreadsheet, not Claude’s memory or a past session. That’s way more reliable, and in Claude Code, “more reliable” also means fewer tokens used.

Lesson: Build it once, then run it forever

Research is a repetitive activity, and when you are doing something repetitive, train your brain to think: Make a skill!

You need a research skill for every type of research you do: competitive, partner, candidate, etc. You can also make a skill for research-basics, that all your research related skills reference so you don’t have to repeat yourself (I made this as I did my report). And maybe you don’t think you’ll want this info on competitors again, or you think it’s just a one-off request from your CEO. It’s probably not. You’ll likely want to refresh, expand, or rerun this. Making a skill is so easy and low stakes (you literally just say to Claude Code, “save what we’ve done so far as a skill called competitive-research”), so why not?

Set up the skill as you do the research, in parallel. It doesn’t need to be perfect at first; you can add to it over time. As I locked in on how to research a data point, I asked Claude Code to add it to a skill.

Here are some of the things to capture in a research skill for a group of companies (or people):

• Add a concrete definition for each data point to your skill (and remember, each data point is a column in your spreadsheet). For example, I was searching for words used in website heroes, but Claude waffled on the hero definition multiple times. Once I gave it specific dimensions for what a hero is and saved that to the skill, it got way better.

• Take competitive research as an example: For every competitor, I want the same things. Pricing and packaging, positioning, recent product launches, customer logos, who they’re hiring, social presence, content they’re publishing, etc. The first time I figured out how to reliably pull each data point, I told Claude Code to save the method to my skill. By the time I got to company #3, the skill could pull most of it on its own.

• Some data points are orders of magnitude harder to pull than others. When you hit one that’s brutal (say, scraping recent LinkedIn posts, which is always a pain since they have no API) decide whether it’s worth keeping in the skill at all. My research skills say stuff like: “Every time we run competitor research, pull these 10 things automatically, but ask me before going after the LinkedIn posts.” That way the easy stuff runs unattended and the hard stuff doesn’t eat up all my tokens like Pac-Man on a bender (I write things like this to see if people are actually reading the newsletter, there will be a quiz on LinkedIn).

• Bonus: You can also set up scheduled “routines” now in Claude Code, to remind you to run competitive research again in say a month.

Join our Slack waitlist - Launching next week

Good news, we’re launching a Slack just for talking about our MCP Server—and using Claude Code in general. It’s invite-only for paid subscribers using the MKT1 MCP Server. Get on the list ➜

Part 3: How to build a research report you can publish with Claude Code

This section covers how to build a research report at scale—pulling data across 50, 100, or more companies and turning it into something you can publish. I built my State of Marketing Part 1 and Part 2 reports this way, mostly by getting it wrong the first time. Most of what’s below is what I’d tell myself if I were starting over.

How to do the research:

1. Figure out what companies you want to research. At this scale you’re probably uploading a CSV—target accounts, industry list, ICP cut, etc. If you don’t have a list, ask Claude for help identifying companies and finding URLs.
   If you’ve already built a company-research or competitive-research skill from Parts 1 or 2, ask Claude to duplicate those skills as a starting place and save it as something like research-report.

2. Ask Claude to set up a skill for the research you’re doing and a corresponding spreadsheet to track all the data points and URLs.

3. Decide which data points you want to track. If you’re building a research report and you’re not sure where to start, ask Claude to help you brainstorm. Ask Claude Code to add these as columns to your spreadsheet, 1 per data point.

4. Run each data point for a small batch of companies at a time before scaling it up. Record the methodology that’s working in the skill itself—the URL, the curl call, the regex, whatever got the answer. That way the skill gets smarter as you go, and you can rerun it later without rebuilding the method.

5. Make sure your data is accurate: Ask Claude to spot-check a few rows and all outliers—outliers are where scrape errors hide. Also set up a rule in your skill so that Claude flags unknowns, instead of just filling them in with nonsense. Read my lessons below for more on this!

6. Ask Claude to build graphs as HTML artifacts in the side panel during iteration—this helps you see what’s going on, try different cuts, and pull insights. Move to Figma using their MCP (or your design tool of choice) once everything’s locked, so you’re not redoing the chart every time data shifts.

7. Save your skill and your spreadsheet as you go. The skill is the instructions, so you can run this again on more companies or easily add data points later. The spreadsheet is your source of truth for the data. You can also ask Claude Code to make a template of your artifact and save that alongside your skill.

8. Publish and share your report. Be sure to caveat your methodology: Flag what isn’t statistically significant, call out where numbers are fuzzy, and note that Claude Code was used.

Here are the prompts you can copy & paste into Claude Code:

Prompt 1: Build the research report skill

Take my company-research or competitive-research skill and duplicate it as a new skill called research-report.

Adapt it to work across a bigger list of companies and prep the data for a publishable report.
The skill should:

1. Ask me how I want to source the companies (paste a list, upload a CSV, or have you find them).

2. Set up a spreadsheet that will be the source of truth for the research, both URLs and data points, and save the company URLs in it, one row per company.

3. Suggest data points to track and work with me to lock them in, then add a column for each. If I’m not sure where to start, brainstorm options first.

4. Run each data point one at a time, starting with a small batch of 3-5 companies to check the method, then scale to the full list. As you go, record the working method (URL, curl, regex, whatever) in the skill itself so I can rerun it later.

5. Flag any cell you can’t fill in—don’t guess or fill in plausible-sounding values. Treat “unknown” as a real third state for any yes/no column. If the methodology gets stuck, takes too long, or hits an unknown value, let me know and we’ll work through new methods together.

6. After each data point is run, spot-check a few rows and all outliers. If the outliers don’t look right, flag them as scrape errors before moving on.

7. Save to the skill and the spreadsheet as you go.

Prompt 2: Build artifacts and pull insights

Using [spreadsheet] with my researched data, build HTML chart artifacts in the side panel showing different cuts of the data, group by [fill in column names or data points].

For each cut, suggest the best chart type (bar, line, or simple table) before you build, I'll confirm.

Reference my brand-guide skill for colors and styling. For each graph, surface the headline insight, where means and medians diverge, and which tells the most interesting story.

When we finish, reference these artifact templates in the skill.

What I learned:

Lesson: Be ruthless about precision

When you’re building a full data report, you can’t check every cell. 10,000 cells is too many to eyeball. So you have to trust the methodology, and to do that in Claude Code, you have to work in phases.

Batching your work keeps you from eating credits like someone at an all-you-can-eat Vegas buffet. But even running things in phases, I still got stuck, changed methodologies midway through, ran data multiple times, and spot-checked into the wee hours of the morning.

Here’s what I learned:

• Don’t trust Claude’s first answer on what methodology is most efficient or assume Claude will flag when there’s a faster, cheaper way.

  • Sob story: I burned 250 Clay credits trying Clay’s MCP for follower counts before realizing a curl call gets the same info in seconds.
    The table below explains what curl is and a few ways Claude can pull data from the web, so you know your options—I just learned about this stuff too.

• If possible, drop entities or data points that aren’t easy to pull—it’s rarely worth the workaround.

  • Another sob story: I built a simple 150-company dataset for our MKT1 MCP Server. 10+ companies came back blank for hero copy because their homepages are built entirely in JavaScript, which curl can’t read. I dropped those companies rather than build workarounds. The same logic applies to any data point: If one is dramatically harder to pull than the rest, it’s rarely worth the trouble.

• As I described in the sections above, you should test your method on a 5-10 company batch before scaling. But this matters even more here because at scale, errors cascade through graphs, through columns, into conclusions you’ve already published.

• After you’ve run the research at scale, always ask Claude to spot-check, and not just random rows, but specifically the outliers. I found that what look like outliers in scraped data are often just bad data, and not real outliers. I caught some data that wasn’t captured right this way.

• Automation gets you to a starting point; manual verification gets you to the finish line. That last mile is really hard to nail; most of my time was spent there.

  • Yet another sob story: Claude Code’s web search confidently surfaced executives who’d left their roles years ago, Clay missed real CMOs, and I ended up reviewing 100 marketing leaders’ LinkedIn profiles manually.

  • Budget time for this, and don’t build graphs or downstream assets until your data is locked.

Why do research in Claude Code, not Cowork or Chat? A simple example…
Claude Code keeps your history very easy to access. It adds everything to one folder on your computer, saves memory across sessions, and shows you exactly how much context you’re using as you go. In Cowork, it’s harder to dig through and track what Claude actually did.
This is more useful than it may sound. Halfway through the build of my State of Marketing reports, I needed to check how an earlier data point got pulled—specifically, what regex we used to find usage-based pricing mentions (regex = a pattern that finds specific text, like “any mention of AI credits or tokens”).
My skill didn’t have it documented; I wasn’t painstakingly writing down every method as I went (I should have been!) But the Python script Claude wrote (Python = the coding language Claude uses to scrape and process data at scale) was still in my folder, the raw HTML was still in my folder, and my tracker file had a one-line note. I could reconstruct what we did and decide whether to trust the data or redo it. I even asked Claude to summarize what we’d done and add a few lines to the skill, so I wouldn’t have to replay the history next time.

Lesson: At scale, small errors compound

A single bad data point in a research report on many companies cascades through your work—the same bad URL gets pulled again, the wrong insight follows, the mistake gets published. I rebuilt graphs again and again (via the Figma MCP) when data shifted, re-wrote insights, and ended up updating the two State of Marketing newsletters after they shipped to correct numbers (with notes on the changes, of course). Errors compound, and so does the work to fix them.

A few rules I learned for keeping a big research project like this manageable:

• Tell Claude to flag unknowns, not fill them in with nonsense. When Claude can’t find an answer, it may fill in a plausible-looking round number instead of admitting it doesn’t know. I figured this out because there were too many round numbers in places where round numbers don’t make sense (7,700 and 12,500 followers, for instance). Instead of Claude telling me it didn’t have the right URL, couldn’t read JavaScript-rendered blog publish dates, or couldn’t find a marketing leader, Claude just filled stuff in and told me the dataset was complete for 100 companies.

  • The same failure shows up if you force a yes/no in a column. If you don’t allow for a third option (yes, no, AND unknown), Claude will just put in “No” when it shouldn’t.

• Slice your data in different ways before committing to one cut. Once your data is in clean spreadsheet columns, the same dataset can be cut by funding, company size, category, GTM motion. Each cut tells a different story, and means and medians often differ (means get skewed by outliers like Stripe and OpenAI; medians don’t). I ran through a bunch of cuts for each graph in my State of Marketing report—what’s more interesting, the by-category story or the by-funding story, for instance?

• Use Claude artifacts during iteration to visualize data, whether for seeing different cuts or to decide what type of graph is best. I naturally want to make every visual in Figma because I’ve been doing that for years, but Claude’s artifact-building has gotten pretty good. You can still use Figma (or your design tool of choice) for the final, publication-ready versions.

  • I learned this the hard way. I made a starter graph in my brand style, connected the Figma MCP, and told Claude where to build the chart. Every time I corrected data or added a column, I had to redo it.

  • What I should have done: asked Claude for quick HTML chart artifacts during the build. They render in the side panel of the desktop app, update instantly when data changes, and look on-brand enough to decide on. Push the final data into Figma at the end for polish. Live and learn—or in this case, graph and learn.

  • After figuring this out, I built a progression into my skill. It starts by making a basic artifact in Claude (chart, table, doc) once the spreadsheet is filled in. Then it asks me if I want to use a specific MCP for the final asset (Mutiny, Gamma, Figma, etc.) if I really want to polish it. And you can go back to your old skills and bolt on artifact steps, which I recently did to all the strategy skills in our MCP server.

Quick definition: An artifact is an asset made by Claude that opens in Claude’s side panel: a chart, table, doc, styled report, etc. This actually works the same in Claude Chat and Claude Code now. Artifacts run on your normal Claude usage; they don’t pull from Claude Design credits (Claude Design is a separate product for pitch decks and mockups).

What’s next? Claude won’t just help you create fuel—it’ll become the engine too

If you’ve read MKT1 for a while, you’ve definitely heard me talk about fuel & engine—the two fundamental elements of marketing. If not, here’s the framework: Fuel is what you create (content, reports, messaging, etc). Engine is the channels you use to distribute the fuel.

Over the past few months building the MKT1 MCP server, people have asked me: What does an MCP server for a newsletter actually do? To which I say: distribute our content and skills—built based on my advising, writing, and templates.

And watching so many of you install and use our MCP Server has given me a new way of thinking about Claude.

While most marketers are already using Claude to create fuel, Claude will increasingly become the engine. And not just because of AEO. I think companies will start to deliberately expose their content, data, and resources to Claude and other LLMs through MCP (or whatever the standard ends up being). It will be a direct path or engine to your users and customers.

Right now, every MCP launch is about connecting products to Claude Code—I’ve talked about Clay, Figma, Airtable, Attio, Mutiny, and more MCP servers in this way. But the same plumbing works to distribute “marketing” fuel: your blog posts, your reports, your data, your point of view.

Are companies catching on and using MCP this way?

Some companies are part of the way there. Profound is a good example (makes sense they’d lead the way—they’re an AEO company). Every blog post on their site has “Open in ChatGPT” and “Open in Claude” buttons in the sidebar. Click one and a prompt with the post link is loaded into your LLM, ready for follow-up questions. The blog post becomes the start of a conversation, not the end. But the button is still a click off their site into an LLM.

AllTrails is an interesting B2C example. Their "product" in this case is really data and knowledge about hiking trails. So their MCP lets you describe your ideal hike conversationally (”a loop trail near me that works for kids, dogs, and has great views”) and get real, ranked options from their 95-million-member database…without leaving Claude. (I love this example, even though you'll never find me hiking!)

What's next: Distribute content and skills—not just your product functionality—through MCP

You can take this a step further. Right now most MCPs only reach existing customers aka people who already use your product. But you can build an MCP that is your free tier. Include skills, content, and research that make it worth installing independent of using your product.

We're trying to prove this out through the MKT1 MCP Server. Two skills are free for anyone who installs it: /mkt1-newsletter (search and pull from past MKT1 newsletter content) and /mkt1-job-board-search (open B2B marketing roles). The rest are gated for paid newsletter subscribers.

So finally the meta moment of this whole newsletter: I used Claude to create this report, and now Claude can deliver it to you as well.

This should now explain why I went the extra mile and published the State of Marketing Reports as a skill (3 newsletters wasn’t enough), giving anyone with our MCP the ability to query the full data in the report themselves. Yes, I’m a bit of a workaholic and don’t know when to stop, but I also wanted to prove this idea I’ve been thinking about for a while.

When thinking about distribution this year, the question may not be “do we start a newsletter?” or “do we record a podcast?” or “do we focus on building a LinkedIn following?” It might be "do we have an MCP server where we can distribute this content?"

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Marketing is in a state of swirl. Old playbooks are dead or dying, new ones are still taking shape, AI is changing everything, and most teams are stuck on the same question: What do I do now?

Some teams are stuck in the old world. Other teams are moving forward: an account-driven foundation, individual social accounts as the new company page, ecosystem and events as growth engines, less reliance on search and inbound. All the things I’ve been writing about for the past year...

But I wanted a better sense of what’s actually going on. Once I started researching 100 fast-growing B2B startups in Claude Code, it was clear I had to move beyond team and leadership data (covered in Part 1 of this report) and into the actual marketing activities. Anything I could glean from scraping websites, social profiles, ad libraries, careers pages, and pricing pages.

Here are the results, covering marketing activities across web, social, and content data points. Scan these graphs, read the analysis in the bullet points, or even access the data in Claude Code via our MCP Server.

Maybe you’re focused on your website and trying to convince your sales leader to actually show pricing publicly, picking a CMS for a relaunch, or making the case for a website redesign. Maybe you’re trying to figure out where to invest content efforts and deciding if your blog should keep going or quietly retire, if your site is AEO-ready, or if your founder’s LinkedIn is worth investing in. Or maybe you just want to see how you stack up against peers your size, get a single stat to back up your strategy, or understand trends in what marketers are doing right now. It’s all in here (or in part 1!).

Want to go further? The MKT1 MCP Server lets you query the full dataset directly in Claude Code. You can also run the same analysis on a list of companies you care about.

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

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In this newsletter:

🔙 Part 1 - Previous newsletter: State of B2B Marketing Teams

➡️ Part 2 - This newsletter: State of B2B Marketing Activities

• State of Websites: What they're built on, what's in the hero, and pricing page trends

• State of Social: Founders vs. companies on LinkedIn and Twitter, LinkedIn ads

• State of Fuel: Blogs, events, communities, newsletters, and AEO readiness

⏰ Part 3 - Coming next week: Claude Code researching and reporting, plus takeaways based on creating these newsletters

Bonus for paid subscribers: 2 new skills related to this research & report in the MKT1 MCP Server:

1. /100_company_marketing_research
   Query the full dataset behind this report: 100 high-growth B2B startups, 90+ data points each, covering GTM motion, team composition, social, ads, homepages, CMS, conversion, and AEO readiness.

2. /high-growth-b2b-company-list
   My curated list of 150 high-growth B2B companies ready as a reference set. Run quick research across a solid list of companies instead of starting from scratch every time.

The State of B2B Marketing, Part 2: Marketing Activities

*Based on what Claude Code can research with Emily Kramer’s prompting

Methodology

A few notes that matter for reading the charts:

• The sample of 100 B2B startups is curated, not random. The intention is to show what the “top” B2B companies are doing right now.

• I divided the companies into 8 categories by audience and function. This is subjectivity—you might have grouped them differently.

• There may be mistakes in the data. No one’s perfect, not even me or Claude.

• For the complete methodology, see Part 1 of this newsletter series ➜

The state of B2B websites

Let’s start with the website. It’s very easy to research web trends in Claude Code, because you can scrape without asking! I pulled the homepage, hero, pricing page, and CMS for all 100 companies, and cut the data by GTM motion, category, and company size.

Want more on web? I recently wrote all about what modern websites include today, with tons of examples in this newsletter. This report gives a more quantitative view of what’s going on.

🎯 MY FAVORITE STAT(S):

• Companies with a sales-led GTM motion hide both their product and their pricing. 22% have product screenshots in the hero, and 0% show prices on a pricing page.

• 0 companies in our study have fully vibe-coded websites. Most use an all-in-one site builder or headless CMS.

What are websites built on? Has vibe coding taken over?

Note: A CMS is the thing that lets a marketer change a headline or swap a logo without bugging an engineer. Framer and Webflow are all-in-one CMSs (design tool + content tool in one). Sanity and Contentful are headless CMSs (just the content tool, paired with a custom front-end).

➜ 39% of B2B sites are still on all-in-one platforms

• The headless CMS category is right behind at 38% (Sanity 15%, Contentful 15%, others combined).

• At 25% overall, Webflow is the most popular way to build a site across all 100 companies, not just the all-in-one category. (Unfortunately I can’t tell when these companies first built on Webflow.)

➜ 23% have no CMS; mostly design tools, dev tools, and AI builders

• This likely means that 23% of marketing teams are annoyed by how hard it is to update their site (just a hunch!).

• Companies in the GTM (5% custom), people, and finance (8% custom) categories almost never go custom. The rule: If your product isn't technical, your website probably isn't either.

• “No CMS” almost always means Next.js code, likely with engineers managing the content directly.

➜ Vibe coding hasn't replaced the traditional CMS yet (emphasis on the yet)

• Zero of the 100 companies built their primary site with an AI builder (not even Lovable or Bolt). Some likely have secondary sites or landing pages built this way, though.

• Among companies under 50 employees, 45% have no CMS.

• Those small companies are the most likely to ditch the developer next year and just ask Claude Code (or a vibe coding tool) to make the change instead.

➜ The bigger the company, the more likely the website is built on headless CMS

• At over 250 employees, there are more headless CMS sites than all-in-one CMS sites. At 50-100 employees, only 21% are on a headless CMS; by 1K+, it’s 55%.

• Why it happens: Once a marketing team has 15+ people, a headless CMS lets the engineers build whatever front-end they want and lets marketers update content separately.

➜ When marketers are first hired, companies move to an all-in-one CMS (from a custom coded site)

• All-in-one CMS peaks at 64% in the 50-100 bucket, the same bucket where the median marketing team jumps from 1 to 4 marketers (detailed in part 1 of the report).

• 45% of sites at companies with less than 50 people are still custom-coded. Founders probably shipped them. The first real marketing hire ends that fast.

As a refresher: Median is the middle value in an ordered dataset, and mean is the average. My team made me put this math lesson in.

What’s in the hero?

➜ Only 22% of sales-led companies have product screenshots, compared to 39% for other companies

• Hybrid (37%) or self-serve (57%) GTM motions show product screenshots way more often.

• Sales-led heroes replace the product screenshot with a background image (74%) or a video (57%). They also run more announcement banners (70%), likely because requesting a demo is a big ask and they need a lighter-weight CTA.

• Why? Sales-led companies are afraid to show anything specific. They don’t just share product screenshots less often; they also rarely have pricing pages, and 0% show prices on the pages they do have (more on pricing pages below).

➜ The average B2B hero has a lot going on

• The standard set of things above the fold: a logo bar (58% of companies), a trust signal (69%), an announcement banner (59%)

  Trust signals includes review sites & analyst badges, customer counts, awards, star ratings, testimonial quotes, and press logos.

• “AI” is everywhere in hero copy (65% of companies say it), but a prompt-style text input box is rarer than I thought, only 9 companies have one in the hero and all of them have a self-serve or hybrid motion.

• A few standout heroes:

  • Legora puts Jude Law in a full-bleed video, really leaning into the “law” pun.

  • Owner asks restaurant owners to type their restaurant name in for a custom AI sales report, the only company not targeting tech companies with a prompt box.

  • And the hero maximalist: Navan stacks 8 of the 9 hero elements we tracked, plus a multiple-choice selector and the tallest announcement bar I’ve ever seen.

  • For more on what’s working on homepages now, check out my newsletter from last month ➜

• Need help managing logos, customer stories, and trust on your website? UserEvidence, one of today’s sponsors, can help you scale customer proof.

What do homepages say?

➜ We’re all AI platforms now: 92% of B2B homepages say “AI” & 66% say “platform”

• 75% companies say “agent” or “agentic” on the homepage: 52 say “agent” only, 19 say both “agent” and “agentic.”

• Only 5 of the 100 companies don't mention AI or agents anywhere on the homepage: Obsidian, Omada Health, Pulley, ServiceTitan, and Tracksuit. I respect the holdouts!

• And please, can we stop saying "revolutionize" (3%), "game-changing" (13%), and "democratize" (5%)? And enough with "seamless" (30%) too.

Does everyone finally have a pricing page?

➜ Good news: 82% B2B companies (finally) have a pricing page

• Most starting tiers are $10-30/mo.

  • The lowest seat-based price is ClickUp at $7/user/mo.

  • Together.ai deals in cents: $0.02 per million tokens.

  • And Pulley is refreshingly straightforward and gives you the price annually: $1,200/year for equity management.

• More money raised = less likely to show prices. 90% of companies in the $50-100M raised range show prices, but only 57% at $500M-1B do. The enterprise sales playbook takes over once you raise serious money.

• Oddly, public companies bounce back to 80%, but that's because 4 of the 5 publics in our sample are hybrid. Let’s break things down by GTM motion a bit more…

➜ Sales-led companies are afraid to get specific (again): 0% show actual prices

• GTM motion is almost a perfect predictor of having a pricing page!

• But also, sales-led companies: We’re going to ask an LLM for your pricing anyway—it might as well be available and accurate on your site. I wrote about this forever ago and can’t believe this is still a debate.

Is usage-based pricing taking over?

➜ More companies are moving to pay-as-you-go pricing to cover AI usage costs

• 36 total companies have usage-based pricing.

  • 28 companies (34% of companies with a pricing pages) have only usage-based pricing.

  • 9 (11% of companies with a pricing page) have both usage-based and seat-based pricing.

• Companies in 7 of the 8 categories have at least one company with usage-based pricing. Design & video companies use this pricing model most often (75%), while 0 vertical industries companies have usage-based pricing.

• There are various types of usage-based pricing: Together.ai (per token), Stripe (per transaction), and Intercom + Fin (per outcome, billed per AI-resolved ticket).

🥤 TAKEAWAYS FROM STATE OF WEB:

The B2B website is finally getting cheaper and faster to build, but companies are still on their legacy CMS or custom-coded site (39% all-in-one, 38% headless, 23% custom).
Meanwhile, sales-led companies are still doing the same thing they've always done: hiding pricing and product screenshots. I think this is actively costing them revenue. Conversion matters more than ever as web traffic and inbound decrease, and buyers are getting impatient—especially when 77% of B2B startups offer a self-serve option.

The state of B2B social

Social is undergoing a shift right now: Human influencers on social are becoming more important than companies on social. And not just for organic. LinkedIn even has thought-leader ads to promote individuals' posts. To see how that's actually playing out, I pulled LinkedIn followers (company + every founder), Twitter followers, and LinkedIn ad activity for all 100 companies.

🎯 MY FAVORITE STAT:

60% of founders at companies under $100M raised have more LinkedIn followers than their company page. After $100M, that drops to 3-6%.

Do founder LinkedIns matter more than the company LinkedIns?

➜ Under $100M raised, the founder LinkedIn beats the brand. After $100M, the company LinkedIn explodes.

• Early-stage, followers are split roughly 50/50 between founder and company.

• The company-to-founder follower ratio (the mustard-colored dots and line on the chart above) jumps from 1.0x at $0 to 100M raised all the way up to 6.8x at $1B+.

• Companies where the founder following still exceeds the company following in followers include Relay.app, Unify, Mutiny, and Sierra.

• And it’s almost always one founder carrying the social weight, not both. The median top founder has 22.1K LinkedIn followers. The median across ALL founders combined is 25.8K So 2nd and 3rd founders only add ~17% on top of what the top founder brings.

• Caveat: Many late-stage companies built their LinkedIn following back when company accounts were the easier path. Now LI seems to favor individuals.

Is Twitter* still alive for B2B? (For some categories, yes)

* Don’t make me call it X

➜ LinkedIn beats Twitter at every stage

• Across all 100 companies, the median company has 6.6x more LinkedIn followers than Twitter followers.

• Not a single category breaks the pattern, the blue LinkedIn bar is taller in every bucket on the chart.

➜ The pattern: technical and creative audiences are on Twitter. Business buyers are on LinkedIn.

• Twitter works in 4 categories: Design & Video (104K median), Builders & Web (106K), AI Infra (75K), and Productivity & Analytics (66K).

• Twitter is totally dead in 4 other categories: GTM (2.4K), Vertical Industries (3.9K), People & Finance (8.1K), and Dev Tools (11.3K).

• Twitter follower counts vary 44x across categories (106K median at the top vs 2.4K median at the bottom). LinkedIn varies just ~6x. So Twitter is the much more category-dependent platform.

• OpenAI has 4.8M Twitter followers, the biggest in the dataset. Anthropic is 2nd at 1.2M. The AI labs in this study are the only ones with truly massive Twitter accounts.

Note: I had to update the LinkedIn and Twitter followers graphs and data from the original newsletter. The narrative remains the same, but Claude had filled in estimates when it couldn't find a number rather than flag the issue. We're all learning how to do research this way and I apologize for the error!

How prevalent are LinkedIn Ads in B2B?

➜ Almost everyone runs LinkedIn ads, but only 56% have figured out thought-leader ads

• The median company in our sample has 386 ad creatives visible in the LinkedIn Ad Library (which tracks the last 12 months). Three companies have over 10K: Canva, Rippling, and ElevenLabs.

• 2 of the 4 companies skipping LinkedIn ads have built major organic presences.

  • Relay.app‘s founder has 70K LinkedIn followers (10x the median for sub-50 companies)

  • Obsidian has 203K Twitter followers (135x the sub-50 median).

• Note: You can pull this info yourself from the LinkedIn Ad Library, or ask Claude Code or Cowork to do it. I’ll share more on how I pulled the data in part 3 of this series.

➜ Who’s figured out that LinkedIn thought-leader ads typically outperform other LI ads?

• Companies in the GTM category run thought-leader ads at 74%. There are lots of influencers in this category, and brands are likely amplifying their posts as paid ads.

• Surprising pattern: Companies in the AI Models & Infra category have the biggest founder LinkedIn followings (41K median, ~2x other categories) but the lowest LI thought-leader ad adoption (23%). The personal brands are massive, but they're not turning them into paid amplification—maybe they should?

• This made me curious: Do companies outside AI Models & Infra with big founder followings run thought-leader ads? Most likely. When you exclude that category, 60% of companies with above-median founder followings (>22.1K) run thought-leader ads vs. 52% for lower founder followings.

• Need help with Linkedin Ads?

  • More on how to use thought-leader ads in my LinkedIn Flywheel newsletter ➜

  • Call Max and August at Closing Media. They're a long-time partner of mine and a sponsor of this report.

🥤 TAKEAWAYS FROM STATE OF SOCIAL

The future of B2B social is less “should I be on LinkedIn” and more “whose voice are we using, and where else do my buyers hang out?”

Currently, LinkedIn dominates. But with 96% of companies running LinkedIn ads, just being on the platform isn't differentiation anymore. The teams that stand out are leaning into growing founder followers and thought-leader ads to put individual voices forward (but still only 56% of B2B startups are using these).

Depending on your audience, it may make sense to add or expand other social channels: Twitter for designers and builders, Reddit and YouTube for technical buyers, and maybe even TikTok for some audiences? maybe?

The state of marketing fuel

Last up in this report, the state of marketing fuel. By "fuel" I mean content broadly: blogs, events, communities, newsletters, podcasts. I was particularly curious about two observations: that events are on the rise, and that while everyone's talking about AEO, many are still behind on actually readying their websites to be read by LLMs.

🎯 MY FAVORITE STAT:
Only 2 companies have a truly AEO-ready website.

Are we still leaning on blogs?

➜ Companies are still posting to blogs regularly

• 100% of B2B companies have a blog, 90% posted 2+ times last month. The median for post per month is 9. This was higher than I thought, I guess the blog isn’t dead yet…

• A better question might be how many of these blog updates are written for humans to read, not crawlers? How many are truly editorial? I didn’t go deep here (yet), but here’s a directional estimate based on the scraped data:

  • ~10-15 companies’ blogs are mostly AI-written posts for crawlers to read — not for humans

  • ~25-35 lean heavily on this AI-for-AI content, even if mixed with editorial

• Note: I had to update this graph and data from the original newsletter. The original scrape couldn’t read the dates on 9% of these blogs. Here’s why it matters:

  • Dates on blogs that load via JavaScript instead of being baked into the HTML aren’t readable by LLMs.

  • While this messed up my report, it has a bigger implication for these companies: their content looks stale to AI, which hurts AI visibility and search rankings.

➜ Beyond blogs, companies lean on events (69%), communities (39%), newsletters (28%) — and very few on podcasts (8%)

• Companies with sales-led GTM motions over-index on events (78%). This makes sense: Longer sales cycles and higher contract values mean relationship-building is essential.

• Only 8 companies have a podcast, those that do are mostly in GTM and Dev Tools categories.

• Channel mix: Only 1 company runs all 4 (events + community + newsletter + podcast). 20 companies run NONE. Most stick to 1-2 channels.

• Caveat: We measured if companies have events, communities, newsletters, and podcasts based on if their homepage or footer has a relevant link. This may miss some.

➜ Communities and newsletters are most popular at product, eng, and design-focused companies

• The biggest divide: Community.

  • 61% of companies in these categories (Builders, AI Infra, Dev Tools, Design) have a community.

  • But only 23% of other companies (in GTM, People & Finance, Vertical, Productivity categories) have a community.

• Having a newsletter has the second-biggest gap (41% vs 18%).

• Builders & Web (70%) and AI Infra (62%) categories lead on community. People & Finance is at 0%. Not a single one of the 12 companies in that category has a community, which is surprising. I thought HR leaders sought community.

LLMs are a distribution channel now; are our websites ready?

➜ Less than 2% of B2B startups in our sample have all the AEO basics in place

• We measured AEO readiness through a few scrape-able signals:

  • FAQ on the site (41%), FAQPage schema, the markup that tells LLMs your FAQ is in Q&A format (2%)

  • Organization schema and SoftwareApplication schema (18%), which tell LLMs details about your company and that you're a software product. You can figure out all the schema types at schema.org

  • Robots.txt rules for LLM crawlers

  • Footer link counts as a proxy for internal linking (median footer links = 44)

• The median B2B footer has 44 links; Datadog tops the list at 119. Sites with few or zero footer links make it hard for crawlers to discover deep pages, which hurts both SEO and AEO.

• 97% of B2B sites let LLM crawlers in (3 block GPTBot, only 2 block ClaudeBot).

  • Attio is doing something smart here: They block CCBot (which feeds Common Crawl, the source of most LLM training data) but allow GPTBot and ClaudeBot. Translation: Don't train on us, but do cite us in real time.

➜ FAQ text is everywhere, FAQ schema is nowhere; only 2 companies have both

• The 2 companies hitting both: Puzzle and Klaviyo. Everyone else has the FAQ content in plain HTML, which LLMs parse less reliably than structured FAQ schema.

• This is the easiest AEO fix on the list: Adding FAQ schema takes about 15 minutes and immediately makes the content machine-readable.

• FAQs are most common in self-serve GTM motions (71%) and the Builders & Web category (60%). The most behind are surprisingly Dev Tools (15%) and unsurprisingly Vertical Industries (31%).

🥤 TAKEAWAYS FROM STATE OF FUEL

We’re seeing more and more content written by AI for AI to read. ~10-15 of the blogs we researched are mostly programmatic; another ~25-35 lean that way.

At the same time, AEO preparedness is lacking for most companies. Less than 2% of companies have the basics — machine-readable dates, FAQ schema, structured data.

Other stats I wish I had time to research…

I had to draw the line somewhere. Here’s what I didn’t get to but would have liked to. The good news is you can pull any of these yourself in Claude Code with our 2 new MCP skills!

• Demo request form fields and form types

• Whether companies offer a “book a meeting directly” option in the demo request flow

• Reddit presence: how many companies have a dedicated subreddit, and how many run Reddit ads

• YouTube channel activity (subscribers and posting cadence)

• Mentions in LinkedIn posts and sponsored LinkedIn posts

• Ads tracking beyond LinkedIn (base on pixels)

• LinkedIn Thought-leader ads broken down: promoting an employee post vs. an outside influencer post

• Types of blog posts that are most common now (launches, thought leadership, customer stories, etc.)

• Events: Webinar frequency and whether the company runs its own conference

Explore the data and do your own research with the MKT1 MCP Server

1. /state-of-b2b-marketing
   Query the full dataset behind this report: 100 high-growth B2B startups, 100+ data points each, covering GTM motion, team composition, open roles, social, ads, homepages, CMS, conversion, and AEO readiness.

2. /high-growth-b2b-company-list
   My curated list of 150 high-growth B2B companies ready as a reference set. Run quick research across a known-good list instead of starting from scratch every time.

Add the MKT1 MCP Server

Plus a bunch more skills in the MKT1 MCP:

Up next: Part 3 of the State of B2B Marketing Report

Part 3 next week will cover my advice for doing research, building reports, and shipping research as a Claude skill. If you want to do this type of report or expand on my research, don’t miss it!

For more stats and graphs, don’t miss part 1 of this report covering marketing teams, leadership, and hiring data.

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📦 MKT1 Unboxing: Watch our video series to see Kramer (that’s me) unbox Mutiny, Wistia, Luma AI, & Attio.

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I accidentally embarked on my first big research report using Claude Code over the past week. The result: a 3-part newsletter on the State of Marketing based on my research of 100 B2B companies from seed-stage to recently public.

Part 1 covers the State of Marketing Teams, Part 2 will cover the State of Marketing Activities (some sneak preview stats from part 2 below), and Part 3 will cover how to make—and even distribute—these reports in Claude Code.

Let’s back up, here’s how this report started. An advisee asked me a simple question: “If we want to start a newsletter for our B2B startup, what platform should we use?” Usually, my brain goes blank thinking of relevant companies to look at when marketers ask me questions like this.

Then I realized with Claude Code I could create and save a list of 100 fast-growing, forward-thinking B2B companies of various sizes, stages, and industries. So I built the list and made a skill to research all 100 companies at once. And then I couldn’t stop. I ended up researching over 90 data points for those companies. I blew past the $100 Claude plan into the $200 plan. I still had to spot-check data and correct graphs manually many times over, but now I can add a company or a data point and re-run the skill for fast answers. And I have about 30 graphs to share with you all.

If you're thinking "how is this different than just using Claude Chat for research?"—reading this series will show you. Specifically, part 3 will cover the details of building a report like this, saving it as a skill, and releasing it via an MCP Server. In other words, I'll explain exactly how to produce researched work, not AI slop.

Subscribe so you don’t miss part 2 and 3 over the next 2 weeks.

Subscribe now

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We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

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In this newsletter:

• Part 1 - This newsletter: State of Marketing Teams, 19 graphs, each with additional analysis you can read or scroll right past

• Part 2 - In your inbox in a few days: State of Marketing Activities, with an emphasis on social and web
  Part 3 - Coming end of April: Claude Code researching and reporting lessons and takeaways based on creating these newsletters

• Next Buildathon: There will be a buildathon related to researching companies in Claude Code, date TBD. In the meantime see the recap and replay of our first Buildathon on building a marketing-strategy skill in Claude Code here ➜

Bonus for paid subscribers—2 new skills related to this research & Report in our MCP Server:

1. /100_company_marketing_research
   Query the full dataset behind this report: 100 high-growth B2B startups, 90+ data points each, covering GTM motion, team composition, social, ads, homepages, CMS, conversion, and AEO readiness.

2. /high-growth-b2b-company-list
   My curated list of 150 high-growth B2B companies ready as a reference set. Run quick research across a solid list of companies instead of starting from scratch every time.

The State of B2B Marketing, Part 1: Marketing Teams

*Based on what Claude Code can research with Emily Kramer’s prompting

Methodology

Before I show you all the beautiful charts and graphs me, Claude, and Figma made together, some notes on methodology:

• I chose 100 B2B startups, mostly venture-backed, from seed to IPO, concentrated in growth-stage. I targeted companies with recent funding rounds, high-growth trajectories, that are referenced as a startup to watch, or are default B2B tools we all know. Claude helped me pull this list together, of course.

• I tried to include a range of GTM motions, audiences, categories, and stages. But it’s concentrated in AI, which is where so much of the fundraising is going right now. This is a curated list, not a random sample. It’s biased and not statistically significant (for example, since I chose “hot” companies, more are hiring than the average startup).

• Categorizing companies into clean buckets is a bit of a fool’s errand. You might have grouped them differently, but I did my best to group companies based on the audiences they target. (See the diagram above for the 8 buckets I used and the companies in them.)

• I pulled and analyzed data via Claude Code using MCP servers (Figma, Clay, Attio, Airtable, and the MKT1 MCP Server). Claude scraped LinkedIn, web pages, ad libraries, and pulled in other sources to validate.

• This report is meant to give you reference points and examples, and show you what the “top” B2B companies are doing in marketing. Despite my best efforts, it may have mistakes. No one’s perfect…not even me or Claude.

How does this sample break down by GTM motion?

I categorized a lot of the data in this report by GTM motion and category, in addition to total funding. Why? Most marketers benchmark against “companies our size.” But there are other “cuts” that dramatically shape what marketing does: GTM motion (how people buy) and category (what you sell).

Quick definitions:

• Self-serve: You can buy without talking to sales. (Some call this PLG. Close but not the same, but that’s a different newsletter.)

• Sales-led: Most buyers go through a rep. You’re getting a demo whether you want one or not.

• Hybrid: A combination of the two, you can sign up or buy without talking to sales or you can buy through a rep, depending on your deal size, use cases, etc.

Two things worth calling out:

1. Certain categories default to certain GTM motions. Vertical-focused startups like Harvey (legal-tech) and Abridge (health-tech) go sales-led because the TAM is narrower and the buyers expect a relationship.

2. I see a lot of marketers try to run a self-serve or PLG playbook at a sales-led company (or vice versa) and fail. Throughout this report, you’ll see how your GTM motion changes what happens in marketing.

The state of marketing team size

🎯 MY FAVORITE STAT
Companies selling to marketers have bigger marketing teams as a % of headcount, with an 8.3% median (8.1% mean). That's more than 2x the rest of the sample. Sample size of 8 is small, but way to practice what you preach.

Let’s start with what’s going on with marketing teams. Obviously, the composition of teams are shifting, agents and AI are doing things humans once did, and we all feel a bit anxious about the situation. But the fast-growing startups in this sample are hiring marketers in large numbers. These companies realize that at a time when it’s easier than ever to build products, marketing, distribution and brand just might be the moat.

Quick caveat/reminder: I scraped data from web, using Clay, and spot checking many careers pages and LinkedIn searches, but this data isn’t perfect, its meant to be directional and a snapshot of what’s going on. It’s not statistically significant.

How big are marketing teams right now?

➜ The median marketing team size is 13; the mean is 44

As a refresher: Median is the middle value in an ordered dataset, and mean is the average. My team made me put this math lesson in.

• I use median as the main measure of the “middle” throughout this report, since the big companies on the list pull the average up substantially. Canva and HubSpot have hundreds of marketers each!

• Team size data on its own isn’t particularly interesting unless you slice it against other datapoints, so let’s slice and dice this data.

➜ Marketing is ~4% of company headcount

• Looking at the above team size charts, I immediately wanted to know what % of headcount sits on the marketing team.

• I’ve long thought 5% was a good benchmark for marketing as a share of headcount (or higher depending on GTM motion and stage), and I’ve fought for that headcount when I’ve led marketing. But, the median in this sample is 4% (mean 4.4%), a bit lower than I expected.

• Marketing team sizes may get smaller in the future (thanks AI), but so will other teams in the org. So, I expect this ratio to stay roughly steady. Maybe I’ll run this skill again in 6 months and see if that holds.

How does marketing team % shift by stage, category, and GTM motion?

When you slice marketing team size, things get more interesting. A few stats stand out:

➜ Below 250 headcount, marketing teams are 5%+ of total headcount.

• Above 250, marketing is consistently 2-4%. As headcount grows, the team size grows, but % of total headcount shrinks.

• Note: It may look like a massive jump in median marketing team size from 500-1K employees (18 marketers) to 1K+ employees (71 marketers). But the 1K+ bucket is a wide range, covering companies from 1,000 people to 15,000.

➜ Companies selling to marketers hire the most marketers.

• The 8 companies building products for marketers have a median marketing team of 8.3% of headcount. The other companies combined median is just 3.8%. It’s a small sample, but clearly having more marketers on the team when you target marketers is beneficial.

• Companies selling to sales teams don’t hire as many marketers. The 6 companies in that bucket run marketing at just 2.9% of headcount. Maybe their sales teams pick up the marketing slack?

➜ Self-serve companies have the biggest marketing teams.

• I expected companies with hybrid GTM motions to have the biggest marketing teams since they have the widest range of channels and content types, plus more ops complexity.

• But self-serve “wins”, with marketing as 5.6% of headcount. Marketers compensate for the lack of a sales team.

• And if you have any self-serve motion (hybrid + pure self-serve) the median is 4.3% vs. the 23 pure sales-led companies with a 3.2% median.

🥤 TAKEAWAY:
Marketing team sizes are a bit all over the place. I love a tidy benchmark, and 2-4% of total headcount is the typical range. But GTM motion, category, and founder preferences shape the actual number a lot.

Brief intermission: Don’t hold another marketing meeting without Granola. It’s now in the MKT1 Perk Stack, which totals $40K+ in exclusive discounts for annual paid subscribers, including Framer, Typeform, Primer, PhantomBuster, and Storylane.
Go to the Perk Stack ➜

The state of marketing leadership

🎯 MY FAVORITE STAT
Only companies with $50M+ in total funding had someone with a “CMO” title in our sample of 100 companies. So don’t expect the C-level title, even if you’re doing the job, until there’s more money in the bank!

Next up let’s look at who’s leading these teams. In my experience, companies that do marketing leadership well have one person owning the whole function with the right title and real scope. Otherwise you end up with silos, gaps, and random acts of marketing.

What titles do we give marketing leaders running the whole team?

Note: These graphs only count the senior-most marketing title per company. A company with a CMO, likely also has VPs too, they just aren’t represented here.

➜ 68% of companies have someone leading all of marketing, but with a mix of Head of, VP, and CMO titles

• Early-stage teams often have no one leading all of marketing. 40% of companies with less than $50M raised don’t have a unified marketing leader; 53% have someone with a “Head of” title.

• That doesn’t mean they have no marketers. Half (3 companies) have someone running a sub-function like content or demand gen. The other half (3 companies) have no marketing hires yet.

• Only 2 companies with under $100M raised have CMOs: Puzzle and Wispr Flow (and given Wispr’s marketing, I think this is a great call, it’s so good!)

• By $500M+ raised, 81% of companies have a unified marketing leader, and 45% have a CMO.

➜ It’s hard to get a CMO title, we found only 27 CMOs across 100 fast-growing companies

• If you have the title, you’re an anomaly not the norm. This bums me out (and without the title you are often under-leveled on compensation too).

• As fundraising goes up so do C-level titles, which does make sense, but still why so low? So let’s compare this to CROs at the same companies to see if they have more seats at the table.

Are there more CMOs or CROs? Or more companies with no C-level GTM leaders?

➜ 59 of 100 companies have no CMO or CRO.

• Three-quarters of those 59 companies have raised less than $500M, meaning C-suite GTM titles are mostly a late-stage phenomenon.

• On the flip side, 15 companies have both a CRO and CMO, all late-stage and mature: Benchling, Chainguard, Datadog, Figma, etc.

➜ CMOs and CROs are basically tied

• 29 companies have a CRO. 27 have a CMO. 59 have nieither. This was suprising to me, I thought CROs would be in much higher numbers than CMO.

• CRO-only companies (14) skew AI infra and sales-led, like Cohere, Rippling, ServiceTitan, etc.

🥤 TAKEAWAY:
Plenty of B2B companies are growing fast without a CMO. Would they grow faster with one? I think yes, but the data can’t prove it. Do marketers deserve more senior titles and the same seat at the table as a C-level sales leader? I also think yes.

The state of marketing hiring

🎯 MY FAVORITE STAT(s)

• 100% of companies with more than $500M raised are hiring marketers.

• ~1/3 of open marketing roles are in ecosystem and events-related functions. These channels are doing the heavy lifting while inbound and outbound both struggle.

Despite fears of AI taking marketing jobs, companies are still hiring in big numbers (at least at the fast-growing startups in this sample). This is likely because so much funding is flowing into AI-era B2B companies right now. I hope it lasts. In the meantime, learn those AI skills!

Are there open roles out there?

➜ Yes, companies are hiring marketers. 87 of the 100 in our sample have open roles, many with more than 1

• Across those 87 companies, there are 507 total open marketing roles. That’s an average of ~6 per company.

• But, 85% of the open roles are at companies with $250M+ raised.

• The 13% not hiring skew small and early: Paper, Obsidian, Navattic, etc.

➜ 100% of companies with more than $500M in funding are hiring marketers right now

• All 42 late-stage companies ($500M-1B, $1B+, pre-IPO, and public) on our list have at least one open marketing role.

• Most open roles are from companies you’d expect: Anthropic, OpenAI, Stripe, Deel, Datadog, and Rippling all have more than 20 roles open each.

How does sales hiring compare to marketing hiring?

➜ 78% of companies are hiring for both marketing and sales right now

• This makes sense, if you are growing fast, you are hiring for both teams, but there was more overlap than I even expected.

• 87 companies are hiring marketing, 84 are hiring sales, 7 aren’t hiring for either.

➜ There are more than 3x as many sales roles open compared to marketing, but most of this is due to a few companies hiring A LOT of sales people

• Rippling alone has hundreds of open sales roles (yes, hundreds). Datadog and HubSpot have over 100 each. Remove those three outliers and the ratio of marketing to sales roles drops to ~1.5x.

• Sales open roles counts are often misleading. Some companies list 1 role for “AE” when they are actually hiring 5. In the other direction, some companies include regional variants for potentially just 1 role. Given this, I think the number of companies hiring for either function in general is more interesting.

Looking for a new role? Inspired by the Claude Code skill I built to scrape roles for this report, we created a new and improved job board. It now has more roles, new filters, and an easier way for paid subscribers to submit jobs for approval.
Go to the job board ➜

What marketing functions are companies hiring for most?

➜ No surprise, Growth and Product Marketing are by far the biggest buckets

• Growth / Demand Gen / Paid leads with 99 open roles. Product Marketing is right behind at 90.

• Together they make up 37% of all open marketing roles.

➜ Events and ecosystem hiring point to what actually works in 2026

• 34% of open marketing roles are in ecosystem and events-related functions (partner, field/events, community, DevRel, and PR). I’ve been saying this for a while, with inbound declining, outbound saturated, and AI slop, human interactions and recommendations matter.

• Field / Events is the #3 bucket with 60 open roles. 5 years ago during peak-Covid times we never could have imagined this!

• Ecosystem marketing roles add up: Partner (16) + Social/Community (44) + DevRel/Advocacy (28) + Comms/PR (23) = just over 100 roles. Companies are hiring marketers to orchestrate relationships with partners, creators, communities, and media to piggyback on trust and credibility.

What do marketing job descriptions say in the AI era?

➜ If you don’t mention AI in your JD, you’re in the minority

• 84% of JDs mention “AI,” 18% mention “agent” or “agentic,” 6% mention “LLM.” Clearly, you need to use AI in today’s marketing roles, but we knew that already.

• Some of the companies that don’t mention AI in their JDs (like Framer and Railway) are very AI-forward. Maybe it’s so obvious it doesn’t need to be said?

➜ The evolution of “cringe”

Cringe is subjective, but here’s what‘s cringe to me just for fun…

• I was expecting “ninja,” “rockstar,” and “hacker” to show up, but I guess we’ve finally moved on (thankfully).

• Instead we have new candidates for cringe like “passionate” (26%), “grit” (3%), and “hungry” (1% - not in chart). It’s giving “Let’s all drink protein-shakes together" vibes.

• You might disagree with me here, but I put “storyteller” in the cringe bucket. It was the WSJ article that did me in.

And what tools do they mention?

➜ Figma and Notion at #1 and #2 was a surprise. Stripe at #6 has an explanation.

• I’m surprised Figma clocks in at #1 (16%), especially given how many marketers prefer Canva. (For the record, all of the graphs in this report were made with the Figma MCP in Claude Code + my obsessive editing.)

• But a caveat for this whole chart: anytime a well-branded tech company shows up in JDs, some of those mentions are name-drops (social proof customer lists, shared investor callouts), not actual tool requirements. Stripe at #6 is the cleanest example — almost all customer name-drops, not actual usage. Figma’s 16% is partly that too: Notion, Hex, and Sanity all name-drop them.

➜ AI tools have taken over, but Marketo is still hanging on

• OpenAI (10%), Claude (7%), Anthropic (6%), and ChatGPT (5%) all show up at meaningful rates. Each one shows up roughly as often as HubSpot (8%) or Salesforce (11%). Lump them together and “AI labs” is the most-mentioned tool category in marketing JDs.

• AI-native tools also show up: Clay (6%), Cursor (5%), Replit (4%), Lovable (4%), Gamma (3%). Honestly less than I expected for Clay and Lovable.

• Meanwhile, Marketo (4%) is still hanging on at roughly the same frequency as Slack and GitHub. Not dead yet.

What are the marketing roles of the future?

I’ve been talking a lot about the Gen Marketer skillset over the last 9 months. So with the job scraping skill I made for this report, I pulled some roles that reflect the need for marketing generalists, who can execute cross-channel campaigns, and work efficiently with AI and agents. Here are some that I found:

• Ramp — Agentic Operator, Growth Marketing: Asks for familiarity with agentic AI, MCP, and evals; if you’d showed me this 12 months ago I would have been very confused!

• Cursor — Marketing Systems Lead: Systems thinker meets marketing ops. Cursor pitching marketing as a systems architecture job is on-brand for an AI coding tool.

• Clay — Chief of Staff, Marketing: I’ve long been a proponent of a CoS in marketing (when leading marketing teams, I called the role something else to get the headcount!). And it’s a perfect role for a Gen Marketer skillset. Lovable also has this role.

• Airtable — Program Manager, AI Programs: Dedicated marketing role for AI-specific programs. Sounds like a Gen Marketer is needed here too.

• Lovable — Field Marketing Lead, Hackathon: Events role written specifically for builder / developer hackathons. A new field-marketing archetype for the AI era.

• Gamma — Product Evangelist: This “Evangelist” role is a mix of a product marketing, content, and DevRel role. Anthropic and Lovable are hiring for "Evangelist" titles too. These PLG, AI-first companies need to educate the market, and this is a new way to do it.

🥤 TAKEAWAY:
There are marketing jobs out there. And yes, you do need AI skills to get them.

Companies are asking for people with broad skillsets and loading the JDs with AI tools and AI buzzwords. But the job titles haven't caught up yet; companies are still mostly hiring for specialist roles. The next time I run this report, I expect to see more generalist, campaign lead, and marketing chief-of-staff titles, and fewer narrow sub-function JDs.

But what’s interesting in this report isn’t just the data…

It’s what this means for how marketers research and distribute content…

It’s now possible to run your own research in Claude, then ship what you learn back to your customers in Claude, where it becomes immediately actionable.

That’s what I did with this report. Claude both co-created the fuel and is the engine for distribution. The research lives as two skills in our MKT1 MCP Server. Now you can use them to benchmark yourself against 150 companies in B2B, or answer the kinds of questions I get asked as an advisor all the time.

2 new research skills on the MKT1 MCP Server

1. /state-of-b2b-marketing
   Query the full dataset behind this report: 100 high-growth B2B startups, 90+ data points each, covering GTM motion, team composition, social, ads, homepages, CMS, conversion, and AEO readiness.

2. /high-growth-b2b-company-list
   My curated list of 150 high-growth B2B companies ready as a reference set. Run quick research across a known-good list instead of starting from scratch every time.

Add the MKT1 MCP Server

Loving our MCP Server, want to talk about it?

Good news, we’re launching a Slack just for talking about using Claude Code or Cowork and/or our MCP Server. It’s invite-only for paid subscribers using the MKT1 MCP Server users. Get on the list ➜

New to MCP Servers and Claude Code?

We hosted a Buildathon that will help you get up to speed. Watch the replay ➜

Reminder: Parts 2 and 3 coming in the next 2 weeks

I’m increasing the newsletter cadence temporarily because what was supposed to be one newsletter turned into three. More graphs, more stats, and more about how I used Claude Code to pull this report together, coming very soon. After that we’ll go back to our normal 2x/month cadence at MKT1, unless I get carried away in Claude Code again for days on end…

Even more from MKT1

🙏 Brought to you by: Softr, an AI platform for business apps; Attio, the AI CRM for modern businesses; and 42 Agency, a Demand Gen and MOPs agency. All 3 companies have offers for MKT1 subscribers!

🤖 MKT1 MCP Server: Add MKT1 to Claude Code, Chat, and Cowork. Paid subscribers get our full library of skills and templates, including the 2 new research skills from this newsletter.

👩‍💻 MKT1 Buildathons: Missed our first Buildathon? Watch the replay to see how to build a /marketing-strategy-skill in Claude Code. Want in on the next one? Get on the waitlist.

📦 MKT1 Unboxing: Watch our video series to see Kramer (that’s me) unbox Mutiny, Wistia, Luma AI, & Attio.

🥞 MKT1 Perk Stack - New Perk: Exclusive discounts worth $40K+ on our favorite GTM tools. For annual & superfan paid subscribers only. We just added 3 months free of Granola, check it out!

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🧑‍🚀 MKT1 job board - new & improved: Jobs from the MKT1 community (it’s free to post as a paid subscriber). And our candidate form if you’re looking for a new role (option to remain anonymous included!).

Subscribe now

On 4/3, we hosted our first ever Buildathon focused on building a marketing-strategy skill that serves as a context layer for all marketing work you and your team do in Claude. The event helped people get started on the process described in detail in this newsletter, it may be useful to read it first.

Video recap

Below is the full video from our Buildathon, but first here are some links you’ll need to follow along:

• Claude Desktop App. We’ll be building in Claude Code Desktop.

• MKT1 prompt library for building the skill

• Slides from the event

Join our Slack Waitlist

We’re launching a Slack just for talking about using Claude Code or Cowork and/or our MCP Server. It’s invite-only for paid subscribers using the MKT1 MCP Server users. Get on the list ➜

2 ways to build a marketing-strategy skill

If you’re building along with the recap video it’s important to note we cover 2 ways to build a marketing-strategy skill. Which path is right for you depends on 2 things: whether you're a paid MKT1 newsletter subscriber and whether you're on a paid Claude plan.

1. With the MKT1 MCP Server: The fast-track way to build a marketing-strategy skill and run all the strategy exercises to populate the skill. It requires the MKT1 MCP Server and a paid version of Claude (if you’re on an enterprise plan, you’ll need to ask your admin to enable it).

   Here are instructions to install the MKT1 MCP Server »

2. Without the MKT1 MCP Server, using shared prompts: The more manual path to building a marketing-strategy skill. Instead of the MCP server guiding you through structured exercises, you’ll work through a prompt list we’ve shared to build and populate the skill step by step. Takes more effort, but you end up with the same output. It requires a paid version of Claude (any plan works).

   Here’s our prompt library for this Buildathon »

Either way, you end up with the same output: a marketing-strategy skill file, saved locally or to GitHub, that acts as a context layer for all your marketing work in Claude

Wait what’s an MCP Server?!

An MCP server connects an LLM to external tools, knowledge, and capabilities—in this case to MKT1 processes, content, skills, etc. Think of it like an integration or API that adds the MKT1 brain to Claude.

Upgrade to install the MCP Server

Buildathon FAQ

Getting up to speed on Claude

I’m new to Claude Code and unfamiliar with how Claude works overall. Where do I start? We have some newsletters that can help. We recommend reading What 4 Gen Marketers Are Building with Claude Code and How to build your marketing strategy in Claude. They cover how Claude Code, Chat, and Cowork differ, what skills are and how they work, and how to think about using Claude as a marketing team. That’s a good foundation before diving into the Buildathon video.

Why use Claude Code over Chat or Cowork? You can build skills in any of them and add skills to any of them. Claude Code is better for building and managing files, planning complex tasks, and doing more sophisticated work. It can also do everything Chat can do. It’s partly preference though. More takes on when to use each on LinkedIn here.

Does the MKT1 MCP server work the same in all three? Sort of. You can use it in Claude Code, Chat, or Cowork. The process just looks a little different visually.

Credits

How many credits does this use—and what does it cost? I’m the Claude Max plan ($100/month) and has only hit the limit once, during a week of intensive building where she created 15+ skills. For regular daily use, the Max plan typically covers it.

Does Claude Code use more credits than Chat or Cowork? It depends more on what you're doing than which interface you're in. Conversational tasks use relatively few credits. Agentic tasks (like browsing the web, interacting with other apps, or running multi-step automations) use significantly more.

Making skills as a consultant, agency, or multi-product company

How do I manage strategy skills for multiple companies or clients? Build a separate marketing-strategy skill for each company. Keep them in separate folders (or separate GitHub repos if you want them fully isolated). Be explicit with Claude about which skill you’re working on. Tell it the context upfront and it’ll keep things straight.

I’m a consultant or fractional marketer, should I build a skill for every client? Yes, one [company name]-marketing-strategy skill per client. You can also have a separate skill for your own frameworks and ways of working that you reference across all clients. For instance I have an MKT1-strategy skill and then marketing-strategy-skills for various advisees.

What if I have multiple products under one company with different ICPs and positioning? You can build one skill that covers all products or separate skills per product line. You can also build a strategy skill that spans all products and references individual strategy skills for each product. Basically, build skills that reference the others within the skill text.

Building the marketing-strategy skill

How do I validate what Claude puts in the skill? Always review what it produces before confirming. For things like TAM or market data, Claude may get things wrong—treat those as drafts to verify, not facts. Just ask Claude to show you what it added to the skill exaclty, check it against what you know, and correct it explicitly. Claude will update the skill accordingly. Remember the skill is just a file, so you can read the contents any time.

How do I keep the skill updated over time? Two ways. Set up a monthly reminder (you can do this via Claude Code or Claude Cowork scheduling feature or even connect Claude to Slack or your Calendar) to audit the skill. Just tell Claude what’s changed and have it update the file. Or do what I do: update it on the fly as you’re working and notice things that are wrong or dated. For larger teams, a scheduled check-in is smarter.

Can I connect execution skills (like SEO) into the marketing strategy skill? Yes, this is the whole point. Your CLAUDE.md points to the marketing strategy skill. The marketing-strategy skill can then reference other skills or files (like a target account list, a voice and tone guide, or an SEO skill). You’re building a stacked architecture where the strategy layer informs everything downstream.

Does this work for B2C or only B2B? The MCP server exercises are more B2B-focused, but the core concept of giving Claude a context layer with your strategy, goals, and who you target applies to any team. Adapt the exercises to fit your business model.

Team sharing

How do I share this with my team? GitHub is the best option as it tracks every change, so multiple people can update the skill and you always have a clear history of what changed and when. A Claude project with the skill added can work if your needs are simple, but as the skill grows and more teammates use it, you’ll want a central source of truth that’s built for this. More opinions on how to do this on this LinkedIn post »

Does everyone on my team need a shared Claude account? No. Everyone can have their own Claude account and access the same skills (or plugin, which is a collection of skills) from a shared GitHub repo.

Can I keep my GitHub repo private? Yes. Just tell Claude exactly what you are trying to do it and it will walk you through the full Github set up.

Troubleshooting

I’m having trouble setting up the MKT1 MCP Server, where do I start?

This newsletter covers the details and includes video walkthroughs »

A few common issues and fixes:

→ Can’t find the Connectors option: You need a paid Claude plan (Pro, Team, or Max). Go to Claude → Customize → Connectors → + → Add custom connector.

→ Connected but don’t see MKT1 tools: Set Tool permissions to “Always allow” on the MKT1 connector. If that doesn’t work, disconnect and reconnect to force a fresh load.

→ Showing as free but you’re a paid MKT1 subscriber: This is almost always an email mismatch. Use the exact email you use for MKT1 Newsletter Substack subscription. If you need to disconnect, reconnect, and re-enter the email that matches.

→ Just subscribed but still showing as free: Wait 2-3 minutes, then disconnect and reconnect to trigger a fresh status check. We’ve built a system for authenticating paid newsletter subscribers, but it does take a couple mins to update.

→ Claude isn’t pulling in MKT1 tools automatically: Set Tool permissions to “Always allow,” or start your message with “Using MKT1 MCP Server...” to point Claude in the right direction.

→ Auth issues in Claude Code CLI: Add it with --transport http — SSE transport won’t work with this endpoint.

→ I had the old MKT1 plugin installed: Uninstall it first (Customize → Browse plugins → MKT1 Gen Marketer → Uninstall), then add the MCP connector. Same skills, but they update automatically now with the MCP Server.

Thanks for your interest in our Buildathon. We hope it helps you successfully build a marketing-strategy skill that dramatically improves your work in Claude!

More from MKT1

🙏 Thanks again to Profound for sponsoring this Buildathon.

🗓️ Don’t miss the next event, get on the list for future Buildathons.

🏃‍♀️ Get on the waitlist for a custom MKT1 Claude Sprint, with Kramer, Halley, and your marketing team.

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I’ve long said your website is your most important marketing asset. Lately, I’ve debated if I still believe this is true.

Websites are in a state of flux right now: LLMs are increasingly where people research products, so less traffic is making it to your site. The traffic that does show up is harder to convert, because prospects have already half-formed an opinion in a chat window. It’s fair to wonder if the website is still worth investing in.

But I’ve landed on my answer: Your website is still your most important marketing asset, but for different reasons.

Your website is a major source of what feeds LLMs, so what’s on your site shapes what those models say about you. And your website, at least for now, is still where prospects go to evaluate and buy. In a world where anyone can vibe code a decent-looking site in an afternoon, your website is your chance to stand out in an increasingly crowded landscape. Don’t vibe code it into undifferentiated chaos!
(A recent report by Framer found that 83% of marketing teams manage multiple websites—vibe coded chaos is very real!)

All of this changes what you need to prioritize on your website now:

• It’s easier to build (and update) websites than ever. Vibe coding and AI tools mean you can spin up pages and match what competitors are doing faster. If you’re not regularly updating your site, you’re already behind.

• Less traffic means conversion matters more. When someone does make it to your site, the stakes on that visit are higher. You need to include the details prospects need to convert, and make sure LLMs can parse those details too.
  (In that same Framer report: 71% say conversion is their top KPI, but only 12% run A/B tests to improve it)

• Credibility is a necessity. Product differentiation is harder (because building products is easier now too), so your brand needs to do the heavy lifting. There are more products in every category and savvy prospects can see through flimsy claims and fake social proof.

• You’re building for two audiences now. Humans evaluating your product, and LLMs deciding whether to recommend it. And this is different from just optimizing for search. With search, you controlled what search engines said about you, from the title to the meta description. LLMs generate a different answer every time and you need to do more to guide the LLM correctly.

To see what this looks like in practice, I called Casey Hill, CMO at DoWhatWorks. DoWhatWorks scans millions of websites and tracks tens of thousands of A/B tests, and Casey’s talked to 75+ website teams about what they’re building and why. He posts those findings on LinkedIn and in the DoWhatWorks Substack. I asked him what’s standing out right now, scanned through 100s of his examples myself to pick out my favorites, and put together this newsletter.

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

Profound: Improve your brand’s AI visibility with Profound. Track how your brand shows up across LLMs, then use agents to turn AI signals into AEO briefs, research competitors, and create campaign-ready content. Used by Ramp, Calendly, Zapier, and MKT1 of course.
🔓 Offer: Mention MKT1 to get a free AI Visibility Report.
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Framer: DoorDash, Perplexity, Mixpanel, and Mutiny’s websites are all built on Framer. From early-stage startups to Fortune 500s, Framer is the website builder I personally recommend. It works like your team’s favorite design tool, with AI-powered building, integrated A/B testing, and one-click publishing
🔓 Offer: Get 15% off a Yearly Pro plan with code MKT15. Annual MKT1 Subscribers get 30% off a Yearly Pro plan in our Perk Stack.

In this newsletter:

I cover the website patterns standing out in the AI era. I’ve categorized 30+ examples into four buckets:

1. Build for humans & machines: We’re now creating content for LLMs, search engines, and humans. These examples cover how to strike the balance.
   Examples include: Wispr Flow, Supabase, Railway, PostHog

2. Go beyond basic social proof to show credibility: AI has lead us all to be more skeptical of what’s real, so the old playbook of basic logos isn’t cutting it. Examples include: Clay, Notion, Linear, Intercom

3. Lower the bar to get started: It’s harder to get people to your site, so when they show up you need them to convert.
   Examples include: Lovable, Replit, Framer, Canva, Zapier

4. Quick wins: Other suggestions to make a high-converting, differentiated site fit for the AI era…and some suggestions of what not to do.

Bonus for paid subscribers: We’ve added all of these website examples and more to our new /website-examples skill in our MCP Server. You can ask Claude for examples of websites that do “X” and it will check the list and report back. I’ll be adding more examples over time.

Subscribe now

Build Claude Code Skills with us this Friday

Come to our first-ever MKT1 Buildathon on 4/3/26. I’ll show how to build a /marketing-strategy skill from scratch in Claude Code.

Free to join thanks to our partner, Profound.

RSVP for the Buildathon

Here’s what to prioritize to build a valuable, high-converting website in the AI era…

1. Build for 2 audiences: Humans & machines

You might think we’ve always been writing for machines (the search crawlers), but it’s a different ballgame with LLMs as the new front door. LLMs generate their own answers with their own copy each time. And many people do not click through on LLM answers like they did with search results. So there are new must-haves to make sure your site is AEO-ready, but still valuable to humans.

➜ Make your site readable by LLMs and search crawlers

I could write many newsletters about AEO, and the noticeable changes to websites, but here are a few ways companies are making their sites LLM-friendly. Some are creating what Casey calls “prompt presets,” pre-built links that send visitors straight to an LLM. Others are adding structured, machine-readable files to their sites. And some are just putting genuinely useful content in places where both humans and LLMs can find it.

Here are some examples:

Wispr Flow: The boldest version of “prompt presets” I’ve seen. At the bottom of their homepage they say “Still not sure that Wispr Flow is right for you? Let ChatGPT, Claude, or Perplexity do the thinking for you.” Then three buttons: Ask ChatGPT, Ask Claude, Ask Perplexity. It’s a way of saying “we’re so confident in how machines see us that we’ll let them do the talking”—and in their case not just in the footer, but in the flow of the homepage.
Some other examples of prompt presets include Glean & Galileo.

Supabase: They link to humans.txt, lawyers.txt, and security.txt in their footer. These are plain-text files that give agents and crawlers a clean, structured way to parse who built the product, what the security policies are, and where to find legal info. Instead of making machines scrape your About page or navigate your legal docs, you give them a direct endpoint.
More on the point of .txt files in this post from Casey »

Kick: This is really clever! Kick lists tax filing deadlines by entity type (S Corp, C Corp, Sole Proprietorship, Partnership) with add-to-calendar buttons next to each one. This shows they really understand their audience. Plus, they did this in a format that’s useful to humans (with an add to calendar option) and easy for LLMs and search engines to cite.

Plain: They put a link to their changelog right in the hero. It signals shipping speed and shows the product is actively evolving. And a changelog is structured, frequently updated content that keeps your site fresh for crawlers.

Read more

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It’s been just over a month since I went all-in on Claude and started writing about agents and Claude Code. Naturally, I’ve also been helping a lot of marketers get up to speed.

One big observation so far: Most marketers using Claude are skipping ahead. You’re trying to produce outputs with Claude based on faulty (or nonexistent) inputs.

The problem with your agents (and honestly your marketing efforts in general) isn’t that you don’t have enough people, tools, or time. It’s that the strategy behind the work isn’t built out enough, high-impact enough, or connected enough to your company’s context.

This has always been a challenge for marketers: You make strategy docs (hopefully), but you rarely look at them again. You update foundational things like ICPs and positioning, but your team doesn’t actually work from the same foundation when planning campaigns or reviewing outputs. So, you end up doing random acts of marketing, random acts of agenting, and random acts of AI-ing instead of focusing on the things that actually help you win.

Here’s what’s different now: Claude can help you build your marketing strategy and then actually use it—in every brief, campaign review, and prioritization decision. Your strategy can live inside Claude and you and Claude can update it regularly as things evolve.

This newsletter explains exactly how to do this step by step. But there’s a shortcut: paid subscribers can use our new MKT1 MCP Server, it has the whole process built in, ready for you to run. Either way, do the damn thing and get your marketing strategy into Claude so your day-to-day work gets better.

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

Attio is the AI-native CRM with built-in enrichment, flexible workflows, and fast set up. Their new “Ask Attio” agent has changed how I personally CRM: It can update fields, do company research, and more with a single AI prompt.
🎁 Offer: MKT1 subscribers get 15% off your first year.
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🎁Offer: Mention MKT1 to get a $2500 paid media assessment free (10 available).

In this newsletter:

• How to create a central /marketing-strategy skill in Claude that becomes your team’s living strategy doc

  • How to run 7 exercises in Claude to build your strategy skill: company overview, ICP prioritization, Marketing Advantages, Perceptions, positioning, Revenue Levers, and Big Bet Campaign exercises

  • Tips for using your /marketing-strategy skill daily to turn your strategy into actual growth

  • How to share and maintain skills across your team using GitHub

• Shortcut for paid subscribers: Our new MKT1 MCP Server can run you through this whole process step-by-step in Claude.

• Need help? Join our first ever Buildathon on 4/3/26 and we’ll walk you through how to build your /marketing-strategy skill in Claude Code.

Subscribe now

The process: Build a /marketing-strategy skill

To build your strategy in Claude, first create one central file: your /marketing-strategy skill. Then run multiple marketing strategy exercises (detailed in the next section) and save the outputs into this skill file. Over time your /marketing-strategy skill becomes a living, breathing foundation for all of your marketing work—not a strategy doc you made once, but something Claude actually uses every time you work.

The MKT1 MCP Server automatically makes you a /marketing-strategy skill file and guides you through the steps below. Paid subscribers get full access here ➜

Here’s how to set it up:

Step 1: Make your skill

• Ask Claude to create a marketing-strategy.md file (that’s your skill!) to hold all your high-level strategy info.

  Here’s a prompt you can use:

  “Create a Claude skill called /marketing-strategy. It should be a SKILL.md file with a description that tells Claude to reference this skill whenever I’m working on marketing—including briefs, campaigns, content review, positioning, planning, and prioritization decisions. Leave the body empty for now.”

• Then tell Claude to reference your new skill whenever your doing something marketing-related for your company. Set this up to happen automatically:

  • In Claude Code or Cowork: Say, “Add this line to my Claude.MD file: reference marketing-strategy.md for anything marketing related.” Your CLAUDE.md file is the instructions file Claude reads at the start of every conversation.

  • In Claude Chat: Ask Claude to update its memory to reference your /marketing-strategy skill for anything marketing related. You can also add it to the instructions for a specific project. Or you can add the /marketing-strategy skill itself to each project.

If you get stuck on any of this, just ask Claude for help and ask it to reference its own “product-self-knowledge” skill.

Step 2: Run strategy exercises and add results to your /marketing-strategy skill

• Run the strategy exercises detailed below, one at a time. After each one, ask Claude to save the output into your /marketing-strategy skill.

• Tell Claude to reference what’s already in the /marketing-strategy skill as you run each exercise. Each exercise builds on the last: company overview feeds ICP prioritization, which feeds marketing advantages, and so on.

• After completing all the exercises, you’ll have a fully built /marketing-strategy skill. More details on each exercise below.

Step 3: Use your /marketing-strategy skill every day

• Once your skill is built, reference it in everything you do: briefs, campaign reviews, prioritization decisions, etc.

• Keep it updated: Give Claude feedback when something feels off, and re-run exercises when things shift. More on this later in the newsletter.

Once you’ve done all 3 steps, your strategy “docs” now live in Claude as skill. You can reference it anywhere in Claude using /marketing-strategy.

Can I just use my CLAUDE.md file for this? Why build a separate /marketing-strategy skill?

You may have heard advice to add marketing strategy details to your CLAUDE.md file. I don’t recommend using it in this way.

• CLAUDE.md should be short. Anthropic recommends keeping this personal instructions file under 200 lines. The longer it gets, the more Claude ignores parts of it. Your marketing strategy will almost certainly be longer than 200 lines on its own.

• A skill is shareable. Unlike CLAUDE.md, a /marketing-strategy skill can be used across your team, every project, and all three Claudes: Code, Cowork, and Chat.

Good news, we’re launching a Slack just for talking about using Claude Code or Cowork and/or our MCP Server. It’s invite-only for paid subscribers using the MKT1 MCP Server users. Get on the list ➜

Run these exercises to add context to your skill

Company overview exercise

Why it matters:

Copying another company’s playbook or stealing random tactics doesn’t work. Your startup is, in fact, a bit of a special snowflake. It has unique attributes that should shape every marketing decision you make. This exercise forces you to document what actually makes your business specific so everything downstream matches the reality. And without it, Claude might make some assumptions about your business model that are out of date or just wrong.

What to document:

• The basics: stage, team size, and funding

• Your business model: ARR, number of customers, GTM motion, how teams adopt your product, and how they expand

• Your high-level audience and TAM, product description, market category, competitive landscape, and ecosystem info (you’ll go deeper on audience and competitors in the ICP and positioning exercises)

How to run the exercise:

1. Ask Claude to help you build a company overview. Give it your URL and let it research your company first, then confirm what it finds and fill in any gaps.

2. Share your stage, company size, pricing model, how customers buy, and anything else unique to how you operate and earn revenue.

3. Ask it to output a clean summary you can save, then tell it to add this to your /marketing-strategy skill (that I detailed how to make in the step above).

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-company-overview exercise. It will research your company, give you a starting point, ask the right questions, and save it all to your /marketing-strategy skill.

ICP prioritization exercise

Why it matters:

Most companies have some version of ICPs, maybe even a persona deck with vanity profiles like “Sales Sally” you never look at. What you actually need are robust ICPs that include both role and company, and you need to prioritize them. Not every segment should get the same effort, budget, or tactics. This exercise forces you to operationalize who you’re spending time on.

What to document:

• Your ICP segments: Both company type and role, and whatever criteria you use to build segments

• Maturity level for each ICP: I recommend using proven/core, scaling, testing, and not a priority.

• Time allocation: Roughly how much overall time your team should allocate to each segment over the next quarter or year.

How to run the exercise:

1. Ask Claude to help you prioritize your ICPs. You can share a list of customers or give Claude access to your CRM to help.

2. Reference your /marketing-strategy skill if you’ve already started building it (so Claude has context on your company)

3. Ask it to output a prioritized table of your segments with maturity levels and time allocation, then add it to your /marketing-strategy skill.

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-icp-prioritization exercise. It will pull in your company overview, walk you through each segment, and save the prioritized list to your strategy file.

Marketing Advantages exercise

Why it matters:

Most companies don’t think deeply about how they can win on GTM before they just start doing. They pick channels, launch campaigns, and copy tactics without thinking about their “accelerants.” Marketing Advantages are the unique catalysts, dynamics, or strengths of your business, product, team, or story that help you grow faster when you focus your marketing efforts here.

What to document:

• The advantages you have—or could have.

• I bucket advantages into 4 categories based on what drives the advantage: product, marketing/ecosystem, fuel, and engine advantages. You can see the broader list I’ve documented here, but you might come up with others that don’t fall neatly into these.

• Strength and maturity of each: How strong is this advantage today, and how strong could it be when fully accelerated? Can it drive step-change growth, or is it just useful? How much energy and focus have you put into this advantage to date?

• Competitive check: Does your closest competitor have the same advantage? If yes, it’s likely a pretty weak advantage.

• Combination check: Are two advantages more impactful together? The best strategies exploit multiple advantages at once.

⠀How to run the exercise:

1. Ask Claude to help you audit your marketing advantages by sharing the descriptions above, this section and diagram from our field guide, and this marketing advantages exercise.

2. Tell it to reference your /marketing-strategy skill and research your top 1-2 competitors. Then confirm what advantages it thinks could catalyze your growth in a meaningful way.

3. Ask it to output a table with each advantage, its strength, and whether it’s competitively differentiated, then add it to your /marketing-strategy skill.

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-marketing-advantages exercise. It will research your company and competitors, help you separate real advantages from aspirational ones, and save it to your /marketing-strategy skill.

Perceptions exercise

Why it matters:
Perceptions are the key narratives you want to drive in your market. They're written from the perspective of your audience and are the foundational tenets of your story. Creating perceptions helps you tell a consistent, repeatable story across all fuel efforts. The majority of your content should ladder up to and support these perceptions.

What to document:

• 3-5 perceptions, covering your company, your market, and your product

• Each written from your audience’s POV, as a belief they’d repeat back to you

• A category for each: company insight, audience insight, market insight, or product insight

• Status: Is this perception already established, emerging, or brand-new?

How to run the exercise:

• Ask Claude to help you define your perceptions by copying and pasting the descriptions above (and by referencing your /marketing-strategy skill.) For more details to feed Claude, reference my newsletter on perceptions and this template for building.

• Ask Claude to output 3-5 perceptions in a table, then add it to your /marketing-strategy skill.

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-perceptions exercise. It will use your company overview, ICPs, and marketing advantages to draft perceptions, then refine them with you.

Positioning exercise

Why it matters: Positioning shapes how you talk about your product to your audience, and without it, you’re probably lacking clarity and maybe even confusing your audience. Most startups overcomplicate this, making long, soon-to-be-forgotten positioning docs that are somehow both exhaustive and unfinished. And even after all that work, they can’t clearly say who the product is for, what it is, and why it’s better than a specific alternative. Once you break positioning down simply, everything else gets easier.

What to document:

• Your answers to the 4 positioning questions: Who is it for? What is it? What are you comparing it to? Why is it better?

• Positioning today vs. positioning in ~1 year: These are often different, especially at fast-growing companies in fast-moving markets. Writing 2 versions solves most positioning misalignment debates.

How to run the exercise:

1. Ask Claude to help you define your positioning. It can check your site and anything already in your /marketing-strategy skill, or you can share any existing positioning work (that 10-page doc from 6 months ago?!) and get help refining. I’ve written about positioning extensively: Here’s my positioning newsletter and positioning statement template for more context.

2. Tell Claude what your product does and who you think it’s for, and let it push back on whether your comparator and “why it’s better” actually resonate with your core audience.

3. Ask it to output a positioning table with two columns (positioning today vs. positioning in 1 year), then add it to your /marketing-strategy skill.

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-positioning exercise. It will research your company, check your ICPs and perceptions, walk you through each positioning question, and save the positioning table to your /marketing-strategy skill.

Revenue Levers exercise

Why it matters:

There are only 4 major ways to drive revenue: new logos, expansion, retention, and pricing. Most marketing teams try to do all four at once and end up doing none of them well. This exercise forces you to stack-rank where marketing can have the biggest impact right now, so you focus your campaigns and goals on the levers that actually move the number.

What to document:

• Stack rank the four revenue levers from 1-4, based on what’s most important to your business right now:

  • Grow top of funnel with core audience

  • Grow top of funnel with new audience

  • Increase customer value

  • Increase efficiency

• For each lever, note the maturity of your current motion: Are you already investing here, just getting started, or not doing anything yet?

• For your top 1-2 levers, describe how marketing will specifically move them with your current team and budget

⠀How to run the exercise:

1. Ask Claude to help you stack-rank your revenue levers by sharing the descriptions above and telling Claude to reference your /marketing-strategy skill. Add more context from this this newsletter and template if needed.

2. Ask it to output a ranked list of these 4 revenue levers with reasoning, then add it to your /marketing-strategy skill.

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-revenue-levers exercise. It will reference your company overview, ICP prioritization, and marketing advantages, walk you through the ranking process, and save it to your /marketing-strategy skill.

Big Bet Campaigns exercise

Why it matters:

Big bets are where strategy becomes action. These are 1–3 campaigns that combine your advantages, perceptions, and ICPs into coordinated efforts. Each one has fuel (content, creative), an engine (channel), and an audience (ICP segment). Without big bets, you end up with a scattered list of tactics. With them, your team knows exactly what you’re investing in and why.

What to document:

• 1-3 campaigns, each with: a name, the ICP it targets, the perception it reinforces, the advantage it leans into, the channel it runs through, and the fuel it requires

• Priority level for each: high, medium, or low

• What success looks like for each campaign

How to run the exercise:

1. Ask Claude to help you design your big bet campaigns by referencing your /marketing-strategy skill. If the above strategy exercises aren’t done and added to the skill, the big bet output ideas won’t be good.

2. Ask Claude to help you brainstorm ideas based on your ICPs, advantages, and perceptions, but the best big bets come from your own creative thinking with all of this context in mind. I’ve written about this more here.

3. Once you have campaign ideas, have Claude output a summary of each, then add them to your /marketing-strategy skill too so you make sure you stay focused on these big things that can move the needle.

Already have the MKT1 MCP Server? Tell Claude to run the mkt1-big-bets exercise. It will pull in the full strategy you’ve already added to your /marketing-strategy skill, paying close attention to your Marketing Advantages, and help you come up with big ideas that will move the needle.

Make skills with me at the MKT1 Buildathon

Come to our first-ever MKT1 Buildathon on 4/3/26 hosted by me, Emily Kramer. We’ll show how we use the MKT1 MCP server and build a /marketing-strategy skill from scratch in Claude Code. It’s the easiest way to go from understanding the concept to actually having this set up and working. Open to all, bring your friends! My dad might even show up (hi dad!)

RSVP for the Buildathon

Other things to add to your marketing-strategy skill

Once you’ve run through all the exercises above, there’s more worth codifying in your /marketing-strategy skill. Here are my recommendations, I can’t cover all of these exercises here, but I’ll be adding skills for each of these things to the MKT1 MCP Server soon!

• KPO Goals: Add your marketing goals and don’t just include KPI or metrics goals. Instead, include goals from these 3 categories: KPI goals (metrics), Project goals (big bets), and Ops goals (foundation work + hiring) Read more in my guide to annual marketing planning and crash course in marketing goal setting.

• KPIs and metrics: Include the specific numbers you track, how you define them, and your targets. Once documented, Claude can reference them when setting goals, evaluating campaigns, or building reports.

• Channel strategy: Document which growth engines you're investing in, the current maturity, and why. Use the exercises above to inform this, not gut feel. Feed Claude my channel-startup fit newsletter (or run the /channel-strategy exercise with the MKT1 MCP Server).

• Lifecycle and account stages: List how contacts and accounts move through your funnel, including lead stages, account stages, product-usage stages, and account tiers. Reference this signal-based campaigns newsletter and the account-driven marketing template.

• Voice, tone, and style guide: Document how your brand writes and speaks. This keeps content consistent across your team, your agencies, and AI writing on your behalf. You can give Claude writing examples or access to Google Drive to get started.

• Brand guide: Add your visual identity: colors, typography, logo usage, diagram style. Share a Figma file or brand PDF directly with Claude to codify.

• Naming conventions, product tiers, and pricing: Adding product details like this prevents Claude from making things up or using the wrong terminology.

• Tech stack and DRIs: Share a list of tools you use and who does what on your team. Makes it much easier for Claude to figure out what’s possible and suggest human and/or tech workflows.

Use your /marketing-strategy skill daily

Run all work through it

Building your /marketing-strategy skill is only useful if you actually reference it. Now that it’s in Claude you can reference it for every marketing thing you do.

Here’s what that looks like in practice:

• When creating briefs: Before any campaign or project, make a GACCS brief (Goals, Audience, Creative, Channels, Stakeholders). This is much faster when you have many of these inputs in your /marketing-strategy skill.

• When prioritizing requests: Sales wants a new deck. A partner is proposing co-marketing. Your founder wants to sponsor an event. Before saying yes to any of it, gut-check it against your /marketing-strategy skill.

• When reviewing content and copy. A generic copy edit in Claude isn’t nearly as effective as checking whether something actually ladders up to your story. Before anything goes out, say: “Review this against my /marketing-strategy” so Claude checks it against your perceptions, positioning, ICP, and brand voice all at once.

The prompt pattern is always the same: Tell Claude what you’re doing and add “reference /marketing-strategy”—that’s it.

Other things you can do when you have this “operating system” built out in Claude:

Once your /marketing-strategy skill exists and Claude is working from it daily, everything else becomes much easier, you can:

• Produce a tangible output from this strategy work. Turn your strategy into a one-page summary for other teams, or a strategy deck—ask Claude to generate it directly from /marketing-strategy.

• Run faster planning cycles. With your ICPs, advantages, perceptions, and revenue levers already in Claude, developing your Big Bets and KPO goals becomes a conversation instead of a process.

• Build a prioritization skill for your whole team. Paste your current to-do list into Claude alongside your /marketing-strategy skill and ask it to stack-rank everything by strategic fit—surfacing the relevant ICP, perception, advantage, and goal for each item. Save that prompt as its own skill, push it to GitHub, and anyone on your team can run it at any time.

• Explain any decision quickly. When a stakeholder asks why you’re doing something, Claude can articulate the strategic rationale instantly—because it’s already in the skill.

• Share your strategy with partners. Need to brief an agency or co-marketing partner? Ask Claude to generate a tailored summary from /marketing-strategy and cut it down for the audience.

The more consistently you reference the skill and keep it updated, the more useful it becomes.

Share it with your team & update it regularly

You should update your /marketing-strategy skill regularly. If you run the skill and anything feels off, ask Claude to help you make updates so it avoids the same mistakes again. And then share it with your team…

• Right now, most teams are sharing skills over Slack, Google Drive, or email. That works once. Once you update a skill, everyone else is on an old version with no way to know what changed.

• Some teams are using Claude Projects or an Enterprise plan instead.

  • On Team, owners can push skills to all members by default.

  • On Enterprise, admins can provision skills org-wide so they appear for everyone automatically. But teammates can’t share directly with each other without going through an admin.

• GitHub was the clear consensus for sharing skills when we asked on LinkedIn. When a skill lives in a shared repo, every update is versioned, every change is tracked, and teammates can always pull the latest version. GitHub gives everyone that flexibility, regardless of their plan.

Here’s how to set it up:

1. Create a private GitHub repo: Call it something like team-claude-skills

2. Add your skill files: Put each SKILL.md in a folder (e.g., /skills/marketing-strategy/SKILL.md)

3. Invite teammates: Settings → Collaborators, add team members

4. Each person adds skills to their Claude setup: In Claude Code, skills in .claude/skills/ are picked up automatically when teammates pull the repo; in Claude Chat or Cowork, they download the .md and upload it to their Skills settings

5. When you update, push the change: In Claude Code, teammates run git pull and they’re current; in Chat or Cowork, they download the updated file and re-upload it to their Skills settings.

You can also just ask Claude: “Help me set up a GitHub repo to share Claude skills with my team. I’m not technical — walk me through it step by step.”

Note: There are many ways to do this, including Claude’s newer plugin feature. It’s worth exploring what setup would work best for your team.

Shortcut for paid subscribers: Install the MKT1 MCP Server

More details are in this newsletter announcing the MCP Server.

What is the MKT1 MCP Server?

The MKT1 MCP Server is live in beta now, and paid subscribers get full access, including all the exercises above. It will help you put everything you read about in this newsletter into action—tracking progress along the way and updating your /marketing-strategy skill for you.

An MCP server (Model Context Protocol server) is a service that connects an LLM (like Claude) to external tools, knowledge, and capabilities—in this case to MKT1 processes, content, skills, etc. Think of it like an integration or API that adds the MKT1 brain to Claude.

Why we built this:

I’ve always thought about MKT1 Newsletter as more than a collection of writing. It’s meant to be a system for running marketing. Templates and resources in Sheets, Docs, Figma, and even Lovable apps were a start.

But with MCP servers, it’s now possible to run your marketing team on the MKT1 Method. You can have your own C-Level Gen Marketer operating inside Claude.

How to install:

Install the MCP server in Claude through your desktop or web app and it will work in Claude Chat, Cowork, or Code. The whole thing takes about 2 minutes. Connect it once, and new skills will show up automatically as we build and deploy them.

Find a walkthrough and by step-by-step-instructions for installing the MKT1 MCP Server here:

Learn how to install the MCP Server

Note: Some versions of Claude, such as Free or Claude Enterprise, may limit access to custom connectors.

While we haven’t thoroughly tested this, it’s also possible to add the MKT1 MCP Server to ChatGPT. Find instructions here.

How to start on your strategy exercise and skill using our MCP Server:

• Once you’ve installed the MKT1 MCP Server, you can ask it what skills it has and also tell it to run the “MKT1 Marketing Strategy Setup” to work through the process in this newsletter.

• This will create your marketing-strategy.md file (that’s your skill) and save it locally to your computer

• It will show you a progress dashboard and walk you through each strategy exercise detailed in this newsletter in the right order

• As you complete each exercise, the output gets saved to your /marketing-strategy skill—and Claude reads it automatically in everytime you pick back up on the marketing strategy setup exercise.

• If you want to skip around on exercises, you can. The setup skill will flag what you missed and suggest going back, but it won’t block you.

• That means when you plan Big Bets, Claude already knows your ICPs, advantages, and perceptions, etc. The exercises compound because they’re all writing to the same place.

• We also have many other skills in our MCP Server that all reference your /marketing-strategy skill if you have one saved.

• The one thing the MCP Server doesn’t do is share this skill with your team, you’ll need to decide how you want to do that (we recommend Github).

Upgrade for full access to the MKT1 MCP Server

Anyone can install our new MCP Server and get access to newsletter content in Claude, but only paid subscribers unlock the full set of skills, including the exercises in this newsletter. Upgrade now to get full access.

Subscribe now

Note: It takes a few minutes for us to register your paid subscription, so if you have any issues installing and authenticating the MCP Server, restart Claude and wait a few minutes before reaching out via our support form.

Conclusion

Right now, most teams are using Claude without a real foundation. They’re prompting into the void, getting something between AI slop and a decent-ish result, and calling it progress. Without a clear marketing strategy underneath, you’re mostly just speeding up random acts of marketing.

Building a /marketing-strategy skill forces you to do the foundational strategy work you may have been putting off, and then makes that work actually usable in your day-to-day.

Your strategy starts to compound when you use your /marketing-strategy skill in daily work, and push updates back into the skill in real time. Your /marketing-strategy skill becomes a true living document that evolves with your business and your marketing work becomes sharper.

Most teams aren’t failing because they lack ideas or effort. They’re failing because their strategy isn’t connected to the work. This is one of the first real ways to fix that.

If you do this right, Claude stops being a place you ask for help and starts becoming the operating system your team actually runs on.

More from MKT1

🙏 Brought to you by: Attio, the AI-native CRM; UserEvidence, for capturing customer proof and building advocates; and Omni Lab, an agency partner for paid media & demand gen. All 3 companies have MKT1 discounts!

👩‍💻 Claude Code Buildathon: Our first-ever Buildathon is on 4/3 at 9am PT / 12pm ET. I’ll show you how to build everything described in this newsletter in Claude Code—while you build along! RSVP now to save your spot.

🗓️ Meet me at Profound’s Zero Click SF event: An exclusive gathering for the world’s top AI Search experts on 4/8/26. Register here »

📦 MKT1 Unboxing: Watch our new video series to see Kramer (that’s me) unbox Mutiny, Wistia, Luma AI, & Attio.

🧰 Template & resource library: We have 100+ templates and resources available to paid subscribers in our template & tool library….

🧑‍🚀 Job board: Jobs from the MKT1 community (free to post as a paid subscriber). And our candidate form if you’re looking for a new role (option to remain anonymous included!).

Join our Slack Waitlist

We’re launching a Slack just for talking about using Claude Code or Cowork and/or our MCP Server. It’s invite-only for paid subscribers using the MKT1 MCP Server users. Get on the list ➜

But with MCP servers, it’s now possible to run your marketing team on the MKT1 Method. You can have your own C-Level Gen Marketer operating inside Claude.

So we built the MKT1 MCP Server and started adding skills to it. It’s live now, and while anyone can install & search our newsletter archive, paid subscribers get access to our growing library of skills (15 & counting!).

What’s inside the MKT1 MCP Server

What’s an MCP Server?
An MCP server (Model Context Protocol server) is a service that connects an AI model like Claude to external tools, knowledge, and capabilities. It lets Claude pull in specialized context, instructions, and capabilities on demand.
In this case, think of it like an integration or API that adds the MKT1 brain to Claude.

Once you add the MKT1 MCP Server to Claude, it should work across Claude Chat, Claude Code, and Cowork. Connect it once, and new skills will show up automatically as we build and deploy them.

To explore what’s available, connect the MCP Server, then ask Claude: “What can the MKT1 MCP Server help with?” Detailed instructions below ↓

Paid subscribers can access 17 skills through our MCP Server right now

More coming weekly…if not daily.

• mkt1_marketing_strategy_setup: Helps you build a tailored marketing strategy so Claude can operationalize it (using many of the other skills in the MCP Server).

• mkt1_homepage_positioning_review: Reviews your homepage against the MKT1 positioning framework and tells you what’s working, what’s missing, and what to fix.

• mkt1_candidate_linkedin_profile_review: Paste in one or more LinkedIn profiles, add a specific role, and evaluate if candidates are a match, based on MKT1 hiring scorecards.

• mkt1_high_growth_b2b_company_list: Use MKT1’s curated list of 150 high-growth B2B companies to do your own research. This skill is available for free.

• mkt1_100_company_marketing_research: Query MKT1’s State of B2B Marketing dataset (100 startups, 80+ data points across GTM, marketing, social, ads, conversion, AEO).

• mkt1_channel_strategy: Determines the best marketing channel strategy for your startup, based on your company stage, audience, GTM motion, and Marketing Advantages.

• mkt1_marketing_advantages: Helps you identify which Marketing Advantages are unique to your business.

• mkt1_icp_prioritization: Helps you identify your ICPs by company type and role, then prioritize them by maturity.

• mkt1_perceptions: Defines your 3–4 strategic Perceptions to guide your “fuel” strategy. These are the narratives and messages you want your audience to repeat back to you.

• mkt1_company_overview: Researches your company and walks you through documenting your stage, business model, audience, and competitive landscape—the foundational strategy drivers everything else builds on.

• mkt1_positioning: Walks you through the 4 positioning questions (who it’s for, what it is, what you’re comparing it to, and why it’s better) and outputs positioning today vs. positioning in ~1 year.

• mkt1_revenue_levers: Helps you stack-rank the 4 revenue levers based on where marketing can have the biggest impact right now, so you stop trying to do everything at once.

• mkt1_job_board_search: Search the MKT1 job board for open B2B marketing roles at vetted companies. This skill is available for free.

• mkt1_website_examples: Search 100+ B2B homepages and patterns by company, category, or what you’re trying to build.

• mkt1_big_bets: Designs 1–3 campaigns that combine your Marketing Advantages, Perceptions, and ICPs into coordinated efforts— ach with fuel, an engine, and a target audience.

• mkt1_gaccs: Describe a campaign, launch, or project and it generates a GACCS Brief so your team is aligned before work starts.

• mkt1_newsletter: Ask any B2B marketing question and it searches the full MKT1 archive to find the most relevant posts. This skill is available for free.

• mkt1_templates: Describe what you’re working on and it finds the right spreadsheets, docs, and interactive tools from the MKT1 library.

How to install the MKT1 MCP Server

For Claude

Install the MCP server in Claude through your desktop or web app and it will work in Claude Chat, Cowork, or Code. The whole thing takes about 2 minutes. Here’s a walkthrough, followed by step-by-step-instructions:

Claude desktop app or web browser

1. Open Claude and click Customize in the left sidebar, then click Connectors. Hit the + button at the top and select Add custom connector.

2. You’ll see two fields.

   1. Name: MKT1

   2. MCP server URL: https://mcp.mkt1.co/mcp

      
      You can also right click on this button, and select “copy link address”:

Copy MCP Server Link

3. Click Add. The MKT1 MCP Server now shows up in your connectors list under “Not connected.”

4. Click on it, then click Connect. This will open a new window where you enter your MKT1 Newsletter subscription email (your Substack login email). Give it a moment to verify; if it seems to stall, just try again.

   1. If you’re a paid subscriber, you’ll see all available tools & everything we ship in the future. Upgrade to unlock full access ➜

   2. If you’re not a paid subscriber, you’ll be able to search our newsletter archive.

5. [Optional] Once connected, click on the MKT1 MCP Server in your connectors list and find the Tool permissions dropdown that says “Custom.” Switch it to Always allow. That way Claude can use MKT1 skills without asking your permission every time, which gets old fast.

Note: Some versions of Claude, such as free or certain enterprise plans, may limit access to custom connectors. Talk to your administrator if you don’t see the options above.

Claude Code CLI (not desktop app)

If you use Claude Code from the command line, run:

claude mcp add mkt1-mcp --transport http https://mcp.mkt1.co/mcp

This connects the MCP Server to your Claude Code configuration. You’ll be prompted to authenticate the first time you use a skill. This will open a new window where you enter your MKT1 Newsletter subscription email (your Substack login email). Give it a moment to verify; if it seems to stall, just try again.

• If you’re a paid subscriber, you’ll see all available tools & everything we ship in the future. Upgrade to unlock full access ➜

• If you’re not a paid subscriber, you’ll be able to search our newsletter archive.

For Claude Enterprise

If your organization uses Claude Enterprise, an admin can make the MKT1 MCP Server available to everyone on the team. Individual users then connect with their own MKT1 subscription email.

Admin setup (one-time) - copy these instructions & send to your Enterprise admin

1. Go to your Claude Admin Settings → Connectors page. Click the + button and select Add custom connector.

2. Fill in these two fields:

   • Name: MKT1

   • MCP server URL: https://mcp.mkt1.co/mcp

3. Click Add. The MKT1 MCP Server will now appear in the connectors list for all users in your organization.

For each user

1. Open Claude and go to Customize → Connectors. You’ll see MKT1 listed as a custom connector.

2. Click on it, then click Connect. This will open a new window where you enter your MKT1 Newsletter subscription email (your Substack login email). Give it a moment to verify; if it seems to stall, just try again.

   1. If you’re a paid subscriber, you’ll see all available tools & everything we ship in the future. Upgrade to unlock full access ➜

   2. If you’re not a paid subscriber, you’ll be able to search our newsletter archive.

For ChatGPT (now in alpha)

While we haven’t fully tested this, it is possible to connect the MKT1 MCP Server to ChatGPT. These instructions were verified on 3/19/26 using chatgpt.com with a Plus plan.

1. Click your profile icon → Settings → Apps → Advanced settings. Enable Developer mode (the elevated risk warning is expected), then click Create app.

2. Fill in two fields:

   • Name: MKT1

   • MCP Server URL: https://mcp.mkt1.co/sse

3. Check the acknowledgment box and click Create.

4. Enter your MKT1 Newsletter subscription email (your Substack login) and click Connect.

   • Paid subscribers get full access to all tools. Upgrade to unlock full access ➜

   • Free subscribers can search our newsletter archive.

5. You’re connected. Start any prompt with mkt1 to use it — for example: mkt1 help me write perceptions

How to use the MKT1 MCP Server

There are no slash commands with an MCP server. Instead, you talk to Claude the way you normally would. Something like:

• “What skills does MKT1 MCP Server have?”

• “Run the MKT1 channel strategy skill”

• “Run MKT1 homepage positioning review on [your URL]”

• “Search MKT1 newsletters for anything on content strategy”

• “Find me a MKT1 template for budgeting”

Claude will pull from the MKT1 MCP Server and run the skill. This just augments how you already use Claude. The skills work with whatever context you give Claude, and the more context you provide about your company, the better the output gets. Upload a doc, paste in competitor info, reference a meeting transcript, etc. to make the skill more effective. The point is to run the MKT1 skills on your specific situation.

If something isn’t working

Just ask Claude: “I have a question about the MKT1 MCP Server.” We built support documentation directly into it, so Claude should be able to help with most common issues. You can ask Claude to reference mkt1_mcp_help to see the FAQs.

Most issues—wrong access tier, missing a new skill, a skill failing to load—are fixed by disconnecting & reconnecting the MCP server and/or restarting Claude. It’s a classic “turn it off and turn it on again” situation! Also, make sure the email you connected with matches your Substack subscription email exactly!

A note if you installed the MKT1 plugin a few weeks ago: It still works for now, but we’re not updating it going forward. The MCP server connector above is simpler and updates automatically. You can keep both, they won’t conflict, but we will likely deprecate the plugin sometime soon.

Feedback and support

We would love your feedback on the skills, but please refer to Claude documentation & the built-in help skill (mkt1_mcp_help) as much as possible for troubleshooting. We are a small team at MKT1, it’s Kramer plus Katie and Halley who work part-time. We are not a tech company with built out support and we are experimenting with ways to enhance your newsletter subscription.

That said, if you have feedback and questions, the best way to reach us is through this MCP Server support form.

Fine print:

You will be asked to approve our Terms of Service when you install this MCP Server. These terms of service state:

• Access to MKT1 AI and the MKT1 MCP Server are currently included for paid subscribers while we test, improve, and determine next steps. A paid subscription—including an annual subscription—does not guarantee ongoing access to these tools.

• Access to MKT1 AI and the MKT1 MCP Server is for individual use and should not be shared.

• You can use outputs generated by MKT1 and the MKT1 MCP Server in your work, but the underlying frameworks, prompts, and tools remain MKT1 intellectual property.

Subscribe now

Things are escalating quickly around here. I’ve barely slept since the last newsletter. It’s not insomnia. It’s not too much advising. It’s not a booming social life. The truth is, I’ve been Clauding and I can’t stop. And I probably won’t stop.

In my previous newsletter, I introduced the idea of hiring your first marketing agent, from choosing the right agent-building tool to the agents I recommend you build first. In this newsletter, we’re going deeper. I’ll walk you through how marketers are actually building in Claude Code and Claude Cowork.

These newsletters follow my own journey; I’ve been learning and building while writing. Just a couple of weeks ago I was on a basic Claude plan. I thought the LinkedIn discourse was a little overhyped. Then, over one weekend, I upgraded my plan and started building everything I could in Claude Code. I’ve basically recreated my (marketing) brain in skills.

I want you to feel the thrill of Claude Code too. No, it’s not always pretty. I have yelled at Claude (in text, not out loud). Claude Code is a bit rough around the edges for a (previously?) non-technical person. But the shift feels as dramatic as when we all got ChatGPT for the first time.

Part of my journey involved calling three people who started building before me: Elaine, Kamil, and Aditya. I’ll share what we all built in detail, covering 5 builds total (2 by me). Paid subscribers can access the skills I made via our new MCP Server and use them directly in Claude.

I hope this inspires you to go deeper.
Warning: This gets addicting fast, you may want to free up some nights and weekends. Your dogs may get shorter walks. Your partner may get annoyed. You might need to purchase a second computer…

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

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In this newsletter:

This newsletter is part 2 of 2 in a series about building agents, skills, and automations. You can catch up on the previous newsletter here.

• A quick primer on Claude for marketers: When to use Claude Chat, Cowork, or Code. Plus, a glossary of Claude terms in the appendix.

• How we’re building with Claude: 5 real skills built by 3 marketers and me

  • My homepage positioning checker and marketing advantages skills

  • Elaine Zelby’s customer lookalike outbound agent, connecting Claude Cowork to HubSpot + Clay + Slack + email

  • Aditya Vempaty’s humanizer skill for reviewing AI-generated copy, using Claude Code + Google’s Antigravity

  • Kamil Rextin’s LinkedIn ad competitive intel agent, using Claude Code, deployed via GitHub + Railway + Vercel

• What we wish we knew before building in Claude Code & how to get started

• For paid subscribers: 4 5 6 (as of now) Claude skills based on MTK1 frameworks on our new MCP Server you can plug in directly to Claude. We’ll also be running a Claude Code Hackathon (among other tools) very soon—get on the invite list here.

Subscribe now

Claude decoded*

*Pretty unoriginal wordplay, but I tried?

Claude becomes scary-powerful when connected to your work, desktop, browser, other tools, and data. But it’s confusing to know which version to use when and to learn all the lingo. Even when you ask Claude what its own terms mean, the answers can be unclear or conflicting, which doesn’t help the situation.

That said, I’m not covering everything about Claude today (that would be one very long newsletter), but there’s a glossary in the appendix if you need more guidance. The goal in this newsletter is to give you inspiration!

Choosing the right Claude for the job

“Claude Code is the worst branding…maybe in the history of technology.”
–Kamil Rextin, Founder, 42 Agency

If you’re new to Claude (or haven’t ventured beyond chat), it has 3 main tools: Chat, Cowork, and Code.

Despite the name, Claude Code is not just for coding. I built both of the skills covered below without writing a single line of code. Kamil might have been exaggerating in his quote above (maybe?!), but if Anthropic’s trying to attract marketers the name isn’t helping! We see “code” and think “not for us.” Claude Code does so much more than “code.” It’s like regular Claude, Claude Cowork, and “coding” all wrapped together.

I also asked on LinkedIn how you’re all using Claude Cowork vs Claude Code:

Start by understanding skills

The one thing you should walk away understanding after this newsletter is skills. I’ve spent most of my time in Claude building skills, and they’re incredibly powerful—even without deploying “apps” or layering agentic workflows on top.

What are skills?
Skills are reusable sets of instructions stored as Markdown files (a simple text file format) that Claude pulls into context when triggered. Think of them as structured playbooks Claude can reference automatically.

Where do you build skills?
You can create (and use) simple skills in regular Claude Chat. But if you want file access, tool integrations, or multi-step workflows, it’s better to use Claude Code or Cowork. You can also build skills in other tools like Google’s Antigravity or OpenAI’s Codex and save them as Markdown files.

How do you use skills you or someone else built?
You can add skills to Claude Chat, Cowork, or Code. But there’s no automatic sync between the three Claude products—hopefully soon, Anthropic? You can export a skill as a Markdown file and upload or paste it elsewhere, it just won’t stay updated automatically across tools. It’s honestluy a little messy right now.

Can I build an agent in Claude Cowork or Code?
“Agent” doesn’t mean the same thing in Claude as it does in tools like Relay.app (covered in part 1 of this series). When people say “I built an agent in Claude Code,” they usually mean a skill, plugin, app, or some combination.

The closest thing to true “agent” behavior in Claude is the brand-new scheduled tasks feature in Cowork. For now, to get something you built in Claude Code to run on a schedule, you need to ask Code to help you write a script and then use a tool like GitHub Actions, Vercel, or Relay.app to schedule it.

How we’re building with Claude

I’ll share 2 skills built off my MKT1 frameworks Krameworks. Then I’ll cover what Elaine, Aditya, and Kamil built.

/homepage-positioning-checker skill in Claude Code, built by me

📦 Job to be done: Make sure a B2B startup homepage makes sense to visitors.

⚠️ The problem: I’m constantly frustrated when I land on a B2B homepage and can’t quickly tell who it’s for, what the product actually is, and why it’s better than the alternatives—and I know I’m not alone. I figured if I could help people pressure-test their homepage against my positioning frameworks, maybe we could end this whole situation once and for all?!

🧠 What it does: Type the skill name and any web url (eg. /homepage-positioning “website.ai”) into Claude Code to get the review underway. The skill evaluates the homepage against my MKT1 positioning framework. It scores the hero and full page separately with letter grades, checks whether the core positioning questions are answered, and gives a concrete fixes including rewritten headlines.

🥷 Steal this learning: Ask Claude Code to build a skill, share a framework you like, then test it on real-world examples. This is the fastest path to building really useful skills. For me, I connected Claude Code to my templates and resources folder in Google Drive, gave it real URLs to test the skill against, told it what to fix based on the output, and then asked Claude Code to update the skill. Four rounds of iteration took the skill from 60% to 90%.

Details of my build:

• I asked Claude Code to access relevant MKT1 newsletters & templates on positioning. I had already granted Claude access to my Google Drive, so it already had my templates folder. It sorted through all of them to find the relevant ones.

• First working draft took minutes. It had all the needed details but was long and not structured well—probably because I didn’t give it an example output.

• So I tested it on a real homepage and started giving feedback. I ran it on an advisee’s homepage and immediately saw what needed to change: scannable scoring, evaluation of CTAs, and a diagram to summarize findings for each positioning question.

• I told Claude to fix each thing, it updated the skill, and I ran it on a new site. I did four rounds of revisions across four companies I advise. Through these rounds, I made rules for headline copy length, guidelines for CTAs, and added what should change for early-stage vs. late-stage startups.

• On my last run, Tracksuit’s homepage got an A- on both hero and homepage positioning. I agreed with the assessment it was good enough to share with the marketing team there—that’s when I knew it was working. I was so excited I also shared the results with Katie and Halley on team MKT1, my first skill for MKT1 subscribers, check…on to the next.

/marketing-advantages skill in Claude Code, built by me

📦 Job to be done: Help marketers build a strategy based on their product, business model, and market.

⚠️ The problem: I wanted a way for subscribers to identify and pressure-test their Marketing Advantages™. I constantly remind marketers to focus on accelerating real advantages instead of defaulting to random acts of marketing. But that’s easier said than done.

🧠 What it does: I built the /marketing-advantages skill with two phases. The “Identify” phase walks you through four rounds of questions to surface your top 2–4 advantages from my 12 Marketing Advantage categories. The “Review” phase lets you paste in your stated advantages and pressure-tests them for specificity, maturity, and strength. It forces clarity on whether something is actually a catalyst for growth or just a tactic dressed up as strategy.

🥷 Steal this learning: Building skills for review processes is an amazing place to start with Claude Code. So many of us already use ChatGPT or Claude to review copy, strategy, or plans. But turning those review processes into a structured skill is even more effecive. I really wish I had this when I was leading marketing teams and spending two hours every night reviewing everything from copy to strategy to campaign plans. Aditya built a skill like this too, more on that later in the newsletter.

Details of my build:

• It was faster to get started this time, because Claude already had access to my Google Drive and knew how to pull relevant newsletters & templates. (Claude often remembers what you’ve taught it, but sometimes you still need to remind it or reference prior skills.)

• The first draft was too generic and not what I’d actually ask an advisee to help them figure out their advantages, so I just gave Claude Code better questions, the same way I’d talk to regular Claude.

• After a few runs, I noticed the reviews weren’t reliably surfacing two important advantages: network effects or proprietary data. So I added explicit questions to force that analysis.

• The first phase to identify advantages was 90% there. So I built the second phase. Building incrementally like this works well.

• I validated the skill against a real submission from my recent Gen Marketer course and compared it to my original written feedback. It landed on the same core insight I had, a good sign.

• Doing the review work manually first and then comparing it was really effective. So, I fed the skill more reviews of marketing advantages I did for students in my course. I probably should have started by giving these examples; you live you learn.

• I briefly considered turning skill into a web app, which would require other tools, API access, and ongoing costs. Then I decided I should just share the skill file directly with paid subscribers without hosting anything (and then we later decided to build an MCP Server to ship them to you automatically). More on how to upgrade a skill to a full web app in Kamil’s breakdown below.

Get the MKT1 MCP Server:
Run MKT1 frameworks in Claude Code & Cowork

Our new MKT1 MCP Server is live in beta (anyone can install, but paid subscribers get full access). Get the 2 Claude skills I built above, plus make GACCS briefs, find your best growth channels, search MKT1 newsletters & templates, and more.

Get the MKT1 MCP Server

/customer-lookalike-outbound in Claude Cowork, built by Elaine

Elaine Zelby is the co-founder of Tofu and a former marketer. She built this in Claude Cowork, connecting it to HubSpot, Clay, Slack, and email.

“A skill is literally knowledge that Claude now has. I think of a skill as a tool in a tool belt. You have your hammer, your wrench, your screwdriver. Skills are just different tools you use for different situations.” –Elaine Zelby, co-founder of Tofu

📦 Job to be done: Find lookalike accounts from closed-won deals and reach out to them.

⚠️ The problem: Your closed-won deals already contain the pain points, objections, ROI story, and the attributes of the right accounts and contacts. Yet we rarely operationalize that insight. Elaine wanted a system that continuously turns closed-won context into tailored outreach.

🧠 What it does: Every week, Elaine’s /customer-lookalike-outbound “agent” looks at deals that moved to closed-won in HubSpot. It pulls structured call data from the CRM, identifies 10 lookalike companies based on the attributes of those deals and her ICP definition, finds 3–5 contacts per company using Clay, drafts a 4-email sequence plus LinkedIn DMs for each contact, and sends drafts into Slack for the team to review.

🥷 Steal this learning: Before building agents, build foundational skills. Elaine created reusable skills for ICP, personas, messaging, and product information first. Those became the building blocks for this skill. Once you have that base knowledge structured in Claude, assembling agents becomes much easier and more consistent.

Details of Elaine’s build:

• Elaine added HubSpot, Clay, Slack, and email to Cowork. She used the official Claude Connectors, so it has API access (not just browser access). This way, the “agent” is reliable enough to run unattended.

• She went piece by piece, making sure her workflow accesses closed-won deals in HubSpot first. Then, she prompted the skill to find lookalike accounts and contacts in Clay. Next, she scheduled it to share drafts in Slack.

• Since she built in Cowork, she could schedule it to run weekly without an external scheduler (you can’t do this in Code yet). Each run looks at deals that moved to Closed-Won in the last 7 days.

• On each run, Cowork pulls call transcripts from HubSpot (originally recorded in Sybill). Because Sybill already fills in structured CRM fields like situation and pain, Claude has richer context to work with. So, the outbound drafts are very close to sendable each time.

• Elaine evolved the output over time. It started as a manually downloaded CSV; now it’s delivered in Slack so the GTM team sees it in their normal workflow. She hasn’t automated outbound sending yet, as she’s intentionally keeping a human in the loop.

• Her advice: When things break, keep talking to Claude. If something isn’t updating or a file isn’t where it should be, have Claude walk you through fixing it.

  

“The thing I’d recommend people do immediately before they build any kind of agent is create three skills: Number one, ICP. Number two, personas. Number three, messaging.” –Elaine Zelby, co-founder of Tofu

/humanizer skill in Claude Code, built by Aditya

Aditya Vempaty is VP of Marketing at MoEngage, a Series F customer engagement platform. He builds in Antigravity and Claude Code, running Anthropic’s Opus under the hood in both.

“Claude Code does a job. Chat does a job. I honestly don’t understand what Cowork is for. It feels like the odd one out. They’re all in the same UI, but you still have to move files around to keep context, which is frustrating.” –Aditya Vempaty, VP of Marketing at MoEngage

📦 Job to be done: Catch and fix AI-sounding copy before it goes out.

⚠️ The problem: When AI writes copy, it sounds like AI wrote it, no matter how hard you try to get it not to. You can layer in brand guidelines, tone instructions, and examples, but the output can still feel slightly off. Instead of endlessly tweaking prompts, Aditya wanted a way to review near-final drafts, check the “AI-ness” of it, and fix it systematically.

🧠 What it does: The /humanizer skill scores drafts, flags specific patterns making the piece feel AI-generated, and rewrites the draft in Aditya’s voice.

🥷 Steal this learning: Every time you use a skill (which again is just a .md file), ask Claude Code what it learned and to update the skill accordingly. That way, with every use the skill gets sharper.

🎰 Steal these credits! If you’re throttling your AI costs, you can get creative like Aditya. He uses credits in AntiGravity running Anthropic’s Opus then ports the finished .md skill file into Claude Code later.

“When I first started running into credit limits in Claude, I did something kind of funny. Antigravity can also run Opus and gives you a bunch of credits for $20/month, so I started building the skills there and then porting the .md file into Claude. It basically gives me double the Opus credits without having to pay $120.”
–Aditya

Aditya’s happy to share his skill, just follow & DM him ➜

Details of Aditya’s build:

• Aditya started by collecting a few paragraphs of his own writing that actually sounded like him. Those became the baseline for the Humanizer.

• He didn’t want a simple rewrite like regular Claude might give you. So he defined four scoring categories (AI likeness, authenticity, reader value, domain credibility), each on a 1–10 scale.

• The skill scores first, diagnoses what’s driving the scores (things like overly structured formatting, generic transitions, predictable phrasing), then rewrites.

• After a new draft runs through /humanizer, he gives Claude feedback. Then he asks Claude Code how the skill itself should be updated. If Claude identifies a new pattern that wasn’t previously codified, it adds it to the skill.

“In Claude, you don’t always know when an agent ran or what it’s actually doing. Antigravity shows me what’s happening from opening tabs to pulling data. That gives me context and confidence. If something’s off, I can rewind and see exactly where it went wrong.” –Aditya Vempaty, VP of Marketing at MoEngage

/LinkedIn-ad-intel in Claude Code, built by Kamil

Kamil Rextin is Founder of 42 Agency. He builds in Claude Code and deploys agents to run on the web using GitHub, Vercel, and Railway.

“For complex projects, I’ve learned not to just jump right in. I use Plan mode in Claude Code to map out the output first. Once that looks right, I switch and let it execute step by step.” –Kamil Rextin, Founder of 42 Agency

📦 Job to be done: Turn publicly available competitor ad data into a structured, ongoing intelligence report.

⚠️ The problem: One of the most common AI use cases is gathering competitive intel, but the output is usually generic. Meanwhile, the LinkedIn Ad Library is hiding in plain sight. It’s free, covers the last 12 months of ads, and in B2B it’s one of the highest-signal places to see how competitors are approaching performance marketing, positioning, and brand. The catch: It’s manual, scroll-based, and impossible to track over time. Kamil wanted to automate it and get updates on what’s changed.

🧠 What it does: Run the /LinkedIn-ad-intel agent with anyURL and it first pulls a list of competitors using his pre-made /competitors skill. Then it scrapes each company’s LinkedIn ads, analyzes messaging themes, and tracks ad volume.

🥷 Steal this learning: Kamil didn't stop at building a skill to run from his desktop. He built a true agent; one that runs on a schedule and delivers results automatically. That required going beyond Claude Code and deploying to infrastructure: GitHub to store and version the code, Vercel or Railway to host and run it. It’s a bit technical, but Claude Code can help you do it.

Download the skill here & a sample report here ➜

Details of Kamil’s build:

• He starts in Plan mode to map out the output before writing any code. Once the plan looks right, he switches to 'Ask Permission' mode and lets Claude execute step by step. This screenshot shows you how:

  

• Kamil previously built a /competitors skill that pulls every competitive company from G2 and TrustRadius. The /LinkedIn-ad-intel agent calls that skill first, stacking skills on top of each other.

• LinkedIn scraping sometimes breaks due to JavaScript restrictions. When that happened, he went back to Plan mode. Claude inspected its own implementation, identified missing retry logic, and proposed fixes.

• Once the agent worked, he pushed the code to GitHub, so it lives in the cloud (not just on his laptop) and he can share it with his team and clients.

• He also set up Railway and Vercel to host his agents. He did this in his browser directly since it’s easier and faster than creating accounts directly in Claude.

• Once the accounts were set up, he connected everything from inside Claude Code by asking it to configure the integrations. By connecting Vercel and Railway to GitHub, he only has to push to GitHub for everything to be updated.

• Railway runs the agent on a schedule via cron jobs (a cron job is just a scheduled task, like “run every Monday at 9am”).

• He later decided to expand what he built to include Meta and Google ad libraries, not just LinkedIn. Starting with just LinkedIn Ads made the build process more manageable.

• The output is a branded PDF report, generated automatically in about 5 mins. Here’s an example for Sierra.ai:

“If your computer isn’t on and your terminal isn’t running, a Claude Code agent can’t run. If you want it hosted on the web, instead of being just on your laptop, you need to deploy it.” –Kamil Rextin, Founder of 42 Agency

Join the first MKT1 Buildathon on 4/3

We’re planning a live buildathon series with the creators and power users of some of our favorite AI tools.

Our first session will be on 4/3/26, hosted by me—we’ll be building a marketing strategy skill in Claude Code.

RSVP now

What we wish we knew before building in Claude Code

The first time…

• Block 2–3 hours for setup. The first time you use Claude Code, plan for it to take a while. Connecting your Google Drive, enabling connectors, granting permissions, figuring out where files live, testing what it can and can’t access, that’s not instant. Block real time for this. Once it’s wired up, it gets dramatically faster.

• Set up a CLAUDE.md file, a standing set of instructions for how you want to interact with Claude, used across all sessions. Type /init to generate one, then add your technical level, preferred approach, and anything you find yourself repeating.

• Build your marketing foundations as skills first. Skills are the compounding layer everything else works off of. So, take time upfront to add skills for your ICP, voice, positioning, GTM motion, etc. (everything in the Marketing Decision Dashboard).

• Claude doesn’t know what Claude can do. It will tell you it can’t browse the web, access a connector, or run something in the desktop app. For how-to-Claude questions, you can ask it to check the “product-self-knowledge” skill that references Anthropic’s docs. In general, if you think Claude is wrong, push back (you won’t hurt its feelings, it’s not human…or is it?!)

Keep going…

• Turn your frameworks and processes into skills. For instance, If you can articulate how you evaluate a draft or share how you created a report step-by-step, that’s a skill. Start with review processes and frameworks you already use. Then run them consistently, share them with your team, and build on top of them.

• Use Plan mode before you “build.” For anything complex, map the output before you let Claude start executing. Confirm the structure, then switch to “ask permission” mode and let it run. This saves credits, reduces chaos, and forces clarity on what you’re actually building.

• Iterate on real examples, not hypotheticals. The first version of everything you build will be solid, but not perfect. Run the skill on actual companies, copy, or deals. Compare the output to what you would have done manually, tell Claude exactly what’s missing, and update the skill.

• The best way to budget time for Claude Code: Build skills in the flow of work. Next time you’re doing a repeat task and have 20-30 extra minutes, like drafting emails or pulling quotes form a transcript, add a little extra time and codify your thinking into a skill.

Appendix: Claude Code terminology

Here’s my best attempt at a glossary to explain all the terms you’ll encounter when connecting and setting things up in Claude Code.

• Integration: Not an official term, just what people say when Claude is connected to something. Could mean any of the below.

• MCP (Model Context Protocol): The “shared language” Anthropic created that lets LLMs, AI applications, external tools, and data connect to each other. Now an industry-wide standard not limited to Anthropic—like a USB-C port, but for AI.

• MCP server: Something a company or developer builds to give AI secure access to their tool’s data and actions. In other words, anything someone builds that speaks MCP. You can add them to “your” Claude (or other LLMs) manually if you have the URL.
  Get access to the MKT1 MCP Server here ➜

• Connector: MCP servers that Anthropic has vetted and packaged for one-click enabling. There are thousands of MCP servers out there, but Connectors are the approved ones you can add instantly.

Used in a sentence: Anthropic built MCP a while back and now they have lots of “integrations” built by developers; for examples, Asana, Slack, Stripe, and Figma have built MCP servers that Anthropic approves and packages into the Settings menu as Connectors, and MKT1 built a custom MCP Server that you can add via URL.

• Skill: We covered this one, but to reiterate…A saved set of instructions and playbooks in a markdown file for Claude (or other AI platforms).
  Example: “Grade my homepage copy against the /MKT1 positioning framework.”

• Plugin: A bundle of skills, connectors, and/or commands packaged up that you can add to Claude. If Claude is your team, it’s like hiring someone new to join the team. You, your company, or third-party developers can all build and share them — Anthropic even has an official directory.
  Examples: Anthropic has pre-built plugins for Marketing

• Command: A /shortcut you type to trigger a saved workflow, skills, or connector. Example: Type /release-notes→ Claude runs this Anthropic-built skill

• Apps & Extensions: Ways to bring Claude into other places you work; not bring other tools into Claude.
  Examples: Claude Desktop for Mac, Claude for Excel
  

  Note: This is a V1 glossary, updated on 3.1.26. Claude is changing regularly and it’s very hard to get a simple definition for these terms, even from Claude. Please let me know in the comments if anything seems off.

Happy Claude Coding! Can’t wait to run some hackathons to help you learn, join the invite list here.

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We’re all hearing the word “agent” more lately. And if you read what’s on LinkedIn, you’d think most m teams have 100 agents doing 90% of our marketing work and spending their whole day in Claude Code. In reality, many marketers I know are still figuring out the difference between workflow automation, chatbots, copilots, and agents. And the vast majority are just dipping their toes in agent building, with varying degrees of success.

No matter where you fall in this spectrum, the time is now to get a handle on how AI can actually automate work for you, Agents represent a real shift in what AI can do, and I think every marketer should be learning to build them right now. Agent-building can be a frustrating and computer draining process, but things are improving quickly. The gap between teams that figure this out and those that don’t is about to get very wide, very fast.

Agents run work on your behalf, in the background, without you initiating every action. An agent monitors your competitors overnight and drops a report in Slack by morning. It watches for job changes at your target accounts and drafts outreach before you’ve had coffee. It takes your webinar recording and turns it into five draft LinkedIn posts without you asking.

If you’ve been following thinking on the new role and skillset I’m calling the “Gen Marketer,” you understand why. Marketers need to use AI to move with increased velocity, learn faster, and run leaner. That way, you can focus on your time on creating work that stands out from the increasingly noisy pack.

I’ve been building and experimenting with agents myself, but I wanted to bring in someone who sees what hundreds of marketers are building. So I phoned a friend: Jacob Bank, Founder & CEO of Relay.app. After watching him wow students in my course with agent knowledge and skills, I knew he’d be able to help MKT1 readers too. So, this newsletter is based on my conversations with Jacob.

In this newsletter:

Part 1 - This newsletter: Learn how to build marketing agent “teammates”

• WTF is an agent? How is different than an automated workflow? Can’t Claude do all of this?

• How to build your an agent you actually ship by thinking in job descriptions, not prompts

• 4 agents every marketing team should create, plus descriptions you can plug into your agent builder of choice

Part 2 - Next week’s newsletter: How 3 marketers built 3 agents step-by-step
This upcoming newsletter will dive a bit deeper on how to build agents in specific tools, step by step.

Subscribe now

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

Attio just shipped Ask Attio, and it makes other CRMs feel outdated. Search, update, and create with AI in one prompt. Ask Attio anything: update fields and stages, run company research, or prep for meetings with full context. (And yes, Attio is MKT1’s CRM).

🎁 Offer: Try Ask Attio for free.
—
Closing Media is a boutique agency that runs LinkedIn and Google campaigns for growth-stage startups. They know the best ways to build and scale ad campaigns in 2026 (hint: thought leader ads!) and have years of expertise (I worked with them in 2018!).

🎁 Offer: Reach out to Closing Media here & mention MKT1 to get $5,000 of free ad spend for your next campaign.
—
Wistia: Wistia is a one-stop video marketing shop. I’ve used them for 10+ years starting with video hosting, and now they cover recording, editing, webinars, and social clips. Wistia’s LLM embeds make videos AEO-ready, helping AI tools understand your transcripts and content.

📦 MKT1 Unboxing: Watch me unbox Wistia with Co-founder Chris Savage: How to make video embeds LLM-friendly, their new remix feature, their webinars product, and more.

A quick break to unbox Mutiny

Mutiny’s brand new AI agent is here. They did the heavy lifting to build the perfect agent for marketing and sales teams to create on-brand, shippable assets using your company’s data and context. Think case studies, business cases, 1:1 landing pages–anything customer facing. I chatted with Jaleh Rezaei, CEO & Co-Founder, who gave me a live demo in our latest MKT1 Unboxing video.

Some highlights from this unboxing and discussion with Jaleh:

• How to build ABM landing pages & business cases that automatically pull in your brand, your sales calls and account history, and link to existing content—in a single prompt.

• How to put an end to the sales request queue by starting from pre-built Mutiny blueprints or saving your own work to create templates for your team.

• How to measure success of assets built in Mutiny, hint: you can see person-level data for every asset, so no more wondering if that enablement asset actually got used and seen.

• Why Jaleh is so focused on bringing sales & marketing closer together and why we think velocity is the most important metric for marketers now.

Join the Mutiny waitlist to get 30 days free with unlimited AI usage »

About MKT1 Unboxing: A series of 30-minute demos + conversations where I (Emily Kramer) unbox marketing and GTM tools—no slides, no scripts, no sales pitch. Just real tools, real workflows, and real talk. The goal: help you find AI tools worth using.

And now, time to build your first marketing agent…

Part 1: WTF is an agent?

“Agents are a totally different way of thinking about work. An agent is not a place that you go to do work. An agent is a doer of work.” – Jacob Bank, founder of Relay.app

An agent is an AI that gets work done for you. It can reason and take action on its own. Think less “assistant I talk to” and more “junior teammate who handles their own to-do list.” You set the parameters, but the agent figures out how to approach the task, uses the tools available to it, and moves toward the outcome.

But everyone defines “agent” a bit differently. It’s admittedly a little confusing—I found myself getting stuck on definitions and what’s what when writing this very newsletter (even with the help of conversations from Jacob). We have tools to help us build AI agents and workflows. We have whole companies dedicated to building a purpose-built AI agent for you. We have the big AI companies building agent builders.

That said, most definitions of an AI agent converge around three characteristics: agents are outcome-focused, reason and plan across steps, and integrate with other tools.

How does an AI agent compare to a chatbot or workflow automation?

“We’re at the beginning of a complete phase shift in how people think about productivity tools. A productivity tool forever has been a place where I go to click buttons and do work…But an increasing amount of the work we get done will be through workflows and agents that are doing that work automatically.” – Jacob Bank, founder of Relay.app

To me, an agent feels like a chatbot and a workflow automation came together… and made a super-kid. “With those tools, you are the operator. But with agents, you are the manager. You set them up, review their output, and train them over time,” explained Jacob.

Here’s a detailed breakdown of what all this nomenclature means:

• An LLM is the underlying model (GPT-4)

• A chatbot is an interface built on top of an LLM. You ask it something, it responds (ChatGPT, Claude)

• A copilot (or embedded AI agent) lives inside a product you already use. It assists you in using the tool and is powered by an LLM. More sophisticated versions can take action inside that system. Think “Ask Attio” inside Attio’s CRM.

• A rule-based workflow automation is triggered by predefined rules and executes actions across tools. It follows explicit if/then logic. These don’t necessarily use an LLM, though they can. Think Zapier in its pre-AI era.

• An AI agent uses an LLM for reasoning, like a chatbot or copilot. It acts across tools and systems, like a workflow automation. Unlike traditional workflow automations, it doesn’t just follow fixed rules—it can interpret context, decide next steps, and work toward an outcome.

And here’s a comparison for understanding what an AI agent actually is (and isn’t):

Part 2: How to build your first agent

I know what you’re thinking: this sounds cool, but I’m not technical enough to build agents. But luckily, you don’t need to know JSON, webhooks, or advanced automation to build an agent. Back to the teammate metaphor: If you can write a job description for a new hire, build a step-by-step workflow in any tool, and use an LLM, you can definitely build an agent.

There are 3 phases here: Pick a task, build your agent, and refine your agent. I’ll walk you through each one.

Phase 1: Pick a task, hire an agent

1. Identify the task

While agents can do multi-function workflows, it’s best to start with something simple. Think of a task that takes manual or repetitive effort. I start by thinking about the things I’m already doing in a few categories:

1. What am I already asking LLMs to do regularly? This usually means generating or editing content. For me, it’s editing a LinkedIn post or writing YouTube descriptions. Can I turn this into an agent with better inputs and less manual cleanup?

2. What processes am I doing in other tools that feel manual? We all log into tools and do the same things over and over again. For me, that’s finding the right people to invite to events or cleaning up screenshots before sharing them. Could an agent run this workflow end-to-end?

3. What research could I do more frequently or in more depth? We all say we want to do more research on our audience, competitors, partners, market, trends, top prospects, etc., but it’s hard to keep up. For me, this could be tracking what advisees’ competitors are doing, monitoring what B2B startup marketers are discussing across communities, or analyzing call recordings for content ideas. Could an agent handle the scanning and summarizing so I can act on it more regularly?

2. Write an agent spec (like it’s a job description)

Once you have an idea, make sure your agent’s first task has a measurable deliverable, something like: “Pull out three potential clips from this webinar transcript.”

Think of this like writing a simple job description: Start with a descriptive agent name and write a short list of responsibilities. You’ll then feed this into your agent building process.

Jacob described this as “A good responsibility tells the agent what-when-how,”, specifically:

• What work should the agent do

• When they should do it

• How they should do it, including how they should deliver the final output

Phase 2: Build the agent

3. Pick a tool to build your agent

There are a lot of options for building agents right now. Some are more autonomous, others are more structured. Some are triggered automatically when something happens behind the scenes (e.g. a new contact enters your CRM). Others are activated by you each time (e.g. by prompting them directly, even via text message, like in the very trendy OpenClaw). Some are pre-built and productized, and you buy them off the shelf. Most teams will end up using all three: autonomous tools for discovery and one-off work, structured systems for the workflows that matter most, and productized agents for the most time-saving, repeatable work.

But you don’t need to overthink this if just getting started, the goal is to try to build something! I find lots of marketers overthink what’s the best tool, and it prevents them from building.

Here’s how I think about the landscape right now:

Autonomous agents like the newish Claude Cowork, let you describe a goal and they figure out the path.

• You point them at a folder or tool, tell them what you need, and they determine the steps in real time.

• But, despite the label “autonomous,” you typically need to activate these agents each time; they don’t just run continuously in the background by default.

• These are powerful for exploratory work or tasks where the process isn’t predictable. (I’m also running this stuff on a second computer, because they are slow!)

Structured agent builders like Relay.app, Zapier, or n8n work differently.

• You define the available tools, triggers, and logic upfront.

• You determine if you want them to run automatically based on a trigger or at your command.

• The agent operates within those boundaries, often with human-in-the-loop controls and explicit error handling.

• These are better when you need repeatability, visibility, approval workflows, or something that runs reliably at scale.

Productized agents (like Mutiny) are pre-built and robust.

• You’re not designing the logic; the company has already defined the job and built the workflows.

• These can be more refined and “sturdy” than something you build yourself, especially for well-defined, common use cases.

And no matter which you choose, use ChatGPT or Claude (the non-Cowork version) to help you research what to build, where to build it, and how to build it. This path is (usually) cheaper than going straight into tools and saves you some major headaches.

4. Build the agent

Now take the “job description” you wrote in step 2 and actually build the agent.

In most tools, there’s a prompt box or setup screen where you can paste in your agent spec. Start there. The platform will usually guide you through the next steps—connecting tools, defining triggers, choosing models, or setting output formats.

Most modern builders have a built-in co-pilot that asks follow-up questions and helps you fill in gaps. You don’t need to architect everything upfront. You respond, refine, and move forward.

The process is often more guided than you expect.

Here’s an example of what this might look like…

Phase 3: Refine your agent

5. Ship it and improve it

Once you’ve got a minimum viable version working, publish your agent and let it run on real tasks. You’ll learn far more from seeing it operate in the wild than from endlessly tweaking it in setup mode.

Most tools provide logs, error messages, and step-by-step visibility to help you understand what went wrong. Use that feedback to tighten the instructions, clarify the output format, or adjust the logic.

If things are breaking, explain the problem to an LLM and have it help you debug, start again with a prebuilt template, or go simpler. E.g. Instead of building a social media monitoring agent across multiple channels (like in my example above), have it monitor just one.

6. Build more

Keep going! Once you build one, you’ll start getting ideas for more on the regular. Go try to build those too. Maybe someday you’ll end up like a person on LinkedIn saying they’ve automated 40% of their job, but know that’s not the reality for most…yet.

I have a lot of 75% done agents that I don’t go back and finish. I don’t have any great advice here, I usually go back to them when I am doing the thing manually again and fix them. I think this is the reality for most people here. You only actually ship and use a small percentage.

“If you were hiring a new competitive analyst, you would not write them a thousand-word document about what you want them to do. You’d say, ‘Hey, look at our competitor YouTube videos and send me a report, tell me if there’s anything interesting.’ And then they’d give you the report and you’d say, ‘Focus more on this, focus less on this.’ And that’s exactly how you should work with your AI agent.” – Jacob Bank, founder of Relay.app

But what about “Agent Swarms” and “Parallel Agents”?

You may see a lot of people talking about multi-agent systems, meaning agents coordinating with each other, running in parallel, forming little AI “teams.” Tools like Antigravity and CrewAI are built for exactly that.

I think in most cases we may be getting our head out over our skis (have I been watching too much Winter Olympics with this phrase)?

Short answer: Yes, some marketers are building those, but that’s not where most teams should start.

When you’re getting started, focus on outputs. Pick one clearly defined task with a tangible deliverable (a competitor brief, a repurposed content draft, a weekly report). Build an agent that owns that job end-to-end. Let it produce something visible in a shared system: a Google Doc in Drive, a Slack message, a CRM update.

If and when you add another agent, don’t over-engineer coordination. Have it work off the output of the first one (that Google Doc, for instance). One agent creates a doc; another reviews or enriches it. One pulls data into a sheet; another analyzes it. They don’t need to “talk” directly. They can collaborate through shared artifacts, just like humans working in the same tools.

Start with one job, and let agents collaborate through shared systems. You’re still ahead of the game if you do this, I promise.

“If you’re wondering how multiple agents work together, it’s just like people! They send each other emails and Slack message, collaborate on the same Google Docs, etc, so you don’t need to think about a totally new concept of an “agent swarm.” – Jacob Bank, founder of Relay.app

4 marketing agents you can build right now

“In general, the rule that I found is for a purely hands on keyboard knowledge work task…an AI agent can do 50 to 90% of what a great human employee can do.” –Jacob Bank, founder of Relay.app

Here are 4 “popular” ideas for agents that most B2B marketing teams could use. You can find more in this LinkedIn post I did this week, template libraries from various agent-building tools, or by asking an LLM.

You can copy and paste these “job descriptions” directly into a tool (like Relay.app) to start building your own version. Or make these your own. The beauty of any AI workflow is it can be fully customized to your needs. So use these templates as a starting point or a first experiment to understand what’s possible, and iterate from there.

1. Competitive intelligence agent

Most marketers deprioritize or shortcut competitive intel because it takes so much time (and because we’re burned out from “battle card” requests from sales). Build an agent instead! A competitive agent is an easy one to start with because it runs entirely on public data, and doesn’t need internal permissions.

• What: Scan competitor websites, LinkedIn, YouTube, press releases, job boards, and G2 reviews for new features, pricing updates, positioning shifts, key hires, and funding announcements.

• When: Weekly on Monday morning (or daily if your industry is super-competitive or fast-moving).

• How: Deliver a structured report to Slack or email. Highlight what changed since the last run and flag anything that could impact positioning, campaigns, or sales conversations.

• Add context: Add a step that pulls in your positioning from Google Docs, Notion, etc. and prompt the agent to assess competitor changes against those claims.

• Related agents: Competitor pricing tracker or a product feature comparison agent that maintains a live feature matrix

Analyze complements, not just competitors. Leveraging the trust and credibility of 3rd-party partners, aka ecosystem marketing, is a very effective way to grow right now. So don’t stop at competitive research. Create an agent to analyze the latest from potential partners, influencers, analysts, etc with the same intentionality you would competitors.

2. Content repurposing agent

Most teams create strong fuel and then don’t extract enough mileage from it. Not because they don’t want to, but because repurposing takes time and mental energy. Since the source material is your own content, the quality floor is significantly higher than generating content from scratch. This is one of the easiest, highest-ROI agents to build.

• What: Take new long-form content (webinars or podcast transcripts, newsletters, a successful longer-form LinkedIn post), and repurpose it into social posts.

• When: Triggered automatically when new content is published or uploaded.

• How: Deliver a set of draft posts to a Doc or directly to your social platform channel for review.

• Add context: Feed the agent your brand voice guide, target persona definitions, past social posts with data, and current social goals, so it aligns with what you’re actually trying to drive.

• Related agents: Full recording to clip transcript extractor, customer quote library builder, evergreen content resurfacing agent

3. Social listening agent

You can’t manually monitor every place your brand or category gets mentioned. Agents are great at monitoring conversations happen in LinkedIn comments, Slack groups, Reddit threads, and X replies, especially when given a few keywords to monitor. This agent helps you know what people are saying, and can chime in when needed.

• What: Monitor specific mentions of your company across LinkedIn, Reddit, Slack communities, X, and relevant forums. (I think it’s best to start by choosing one platform at a time).

• When: Real-time alerts for high-priority mentions (so you can engage in a timely way) plus weekly reports.

• How: Deliver a concise digest to Slack that prioritizes mentions based on: Posts from high-reach or high-authority accounts, posts gaining engagement quickly, mentions tied to priority topics. Show the highest-impact opportunities first.

• Add context: Pull in focus keywords or topic, brand name variations, and top influencers or creators in your space.

• Related agents: Executive name mention tracker, partner mention alert agent, target account mention agent.

4. Growth analyst agent

Automate the jobs a strong growth marketer does every day: check HubSpot, look at email performance, scan ad accounts, and figure out what actually needs attention. The problem is that analytics live in different systems, and most teams don’t have the time to synthesize dashboards daily. You can also have the agent share updates with the whole team so everyone has visibility into what’s changing.

• What: Pull data from HubSpot, your email platform, ad accounts, and anywhere your marketing analytics exist. Share daily KPIs and flag meaningful shifts.

• When: Send a daily KPI snapshot, with a more detailed weekly trend summary.

• How: Deliver a short update to Slack or email that includes: Core KPIs vs target and last week notable changes or anomalies, 1–2 areas that likely need investigation

• Add context: Pull in your KPI targets and quarterly goals from your planning spreadsheet so the agent evaluates performance against your actual goals.

• Related agents: Pipeline quality monitor that tracks conversion rates, paid campaign monitor, Forecast vs. actuals agent

More examples of things people have actually built from this LinkedIn post’s comments:

Account research & outreach agents

• Cold outreach agent with ICP mapping, research, and email composition

• Customer lookalike agent pulling HubSpot data, finding similar companies via Clay, personalizing email sequences and LinkedIn DMs

• Weekly database scanners for high-intent signals with ICP lead enrichment

• Case study opportunity detector (or just use Mutiny!)

Content creator agents

• Executive POV miner (pulls themes from sales calls, customer interviews)

• A blog post generator that pulls in the latest news each week

• Landing page creation agent trained on brand guidelines

• Resource hub built and updated by agents

• Podcast guest research agent

Social media manager agents

• LinkedIn page management

• Content insights from top voices

• LinkedIn post topic finder

Research agents

• Trademark clearance agent for agency that does naming

• Research agent synthesizing audience signals, competitor posts, and content pillars into prioritized ideas

• Conference opportunity analyzer

Productivity agents:

• Job board scraper and poster

• Draft intro emails directly in Gmail by sharing LinkedIn profiles

More tips from my workshop with Jacob

Here are some things to keep in mind as you build:

Use LLMs to help you build agents.
Describe the job to ChatGPT or Claude and have it help you break the work into steps, anticipate edge cases, and refine instructions. I rarely build in any AI tool without an LLM helping me plan & write prompts as I go.

Design for reliability before scale.
A lot of the questions during my session with Jacob came down to trust. How do you know which model to use? What about subtle logic errors?

The answer isn’t finding the perfect prompt, it’s constraining the system. Start by defining the exact structure of the output. Don’t just ask for “three clips” or “a competitor summary.” Specify the fields you expect. Most modern platforms support structured outputs, which force the model to return content in a predefined format. That constraint dramatically reduces formatting drift and vague answers.

Check your work with another agent.
People are always concerned about hallucinations, and rightfully so. For higher-stakes work, use a simple writer + checker pattern: one pass generates, a second pass audits against a short checklist or your definition of done before it ships.

Security, cost, and access, concerns are valid
Treat permissions like you would with a new hire, begin with read-only access, limit what the agent can change, and expand write access only after you’ve seen it behave well on real inputs.

The same discipline applies to cost. Keep scopes bounded and steps explicit so the agent doesn’t wander. Open-ended tool use and retries are what make usage unpredictable.

For this reason, I’m less likely to use a brand new unestablished tool that might be hot that day. And if your company doesn’t give access to all tools, you may be able to start with basic productivity tasks that require less tool access.

Don’t create another place to go. Treat agents like teammates, not tools to visit.
If your agent lives in its own interface, you’ll forget it exists. The best agents deliver work into systems you already use (Slack, Drive, your CRM, your project tracker) just like a teammate would. And remember, you can use one agent’s output (a Google Doc, a Slack message, a spreadsheet) as another agent’s input.

Relatedly, I find that setting every agents output to daily seems like a good idea when setting it up, but is overly ambitious. I’m not actually going to look at if a competitor changed their customer’s page daily, so don’t add the extra noise!

How agents fit into modern marketing teams

“Whenever you’re in doubt about how you should work with an agent, just think about how you’d work with a person. Write a job description like you would for a teammate. Assign tasks like you would to a teammate. Review and edit the work like you would with a teammate. Give feedback like you would to a teammate.” –Jacob Bank, founder of Relay.app

Truth be told, when I start to think about agents too much, I get a little freaked out about what happens to human marketers. I can’t 100% predict where this goes in the long term.

But for now—and likely for a while—the teams that learn when to use humans versus agents are going to operate more effectively. I’m bullish on marketing teams shifting away from specialist-heavy silos and toward flatter structures built around Gen Marketers: AI era generalists who own campaigns end-to-end and pull in specialists, contractors, and agents as needed. A Gen Marketer with a team of well-tuned agents can execute faster, learn more quickly, automate the mundane, giving them more time to spend on campaigns that actually stand out.

Here’s how I see the division of labor today…agents handle repeatable knowledge work: monitoring, drafting, enriching, reporting. Humans handle strategy, creative judgment, and anything where the cost of being wrong is high.

For now, just start building. And if you want to go deeper, get on the waitlist for our upcoming hackathons—we’ll be working on everything from agent building to vibe coding to AEO workflows.

More from MKT1

🙏 Brought to you by: Attio, the AI native CRM; Closing Media, a LinkedIn Ads & Paid Media agency, and Wistia, a one stop video marketing shop.

🔓 Gen Marketer Hackathons: Be the first to know when we kick off our Hackathon series, get on the list here.

📦 MKT1 Unboxing: Watch our new video series to see Kramer (that’s me) unbox Mutiny, Wistia, Luma AI, & Attio.

🥞 MKT1 Perk Stack: Exclusive discounts worth $40K+ on our favorite GTM tools. For annual & superfan paid subscribers only.

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🧑‍🚀 Job board: Jobs from the MKT1 community (free to post as a paid subscriber). And our candidate form if you’re looking for a new role (option to remain anonymous included!).

🍽️ MKT1 Supper Club: Get on the list for monthly IRL dinners with Kramer, a small group of smart marketers, good food, and conversations on topics that actually matter in your role—made possible by some of my favorite GTM tools.

• How to build ABM landing pages & business cases that automatically pull in your brand, your sales calls and account history, and link to existing content—in single prompt.

• How to put an end to the sales request queue by starting from pre-built Mutiny blueprints or saving your own work to create templates for your team.

• How to measure success of assets built in Mutiny, hint: you can see person-level data for every asset, so no more wondering if that enablement asset actually got used and seen.

• Why Jaleh is so focused on bringing sales & marketing closer together and why we think velocity is the most important metric for marketers now.

Join the Mutiny waitlist to get 30 days free with unlimited AI usage »

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The hottest B2B marketing trend right now isn’t AI, it’s dinner. Okay, that’s probably an exaggeration. But it’s true that founders and marketing leaders are getting multiple invites every month to some kind of “dinner”: small group dinners, executive roundtables, salons–or even flower arranging classes. We’re right on top of this trend at MKT1, we hosted our own MKT1 Supper Club dinner last week in NYC with Profound.

Whatever you want to call these events, it’s clear that somewhere in the last 5 years, the company-hosted “dinner” replaced the trade show as the B2B event du jour…and I support this “trend.”

I’ve podcasted and written about in-person events before and cautioned against the old strategy of throwing your whole budget at conference booths. But a dinner done right is increasingly a high-leverage way to stand out in a sea of AI slop, and it’s an elegant way to put your ecosystem to work. Especially for high-ACV businesses, getting the formula for a successful dinner right can be transformative.

So I called Sheena Badani, who works with companies to host standout events through her company RevAura, to get an expert take on running dinners that work in 2026. At RevAura she’s running dinners, cooking classes, and even nail salons, all aimed at getting the right people in the room. Sheena was previously a marketing leader at Gong, but decided to double down on executive events after seeing their impact firsthand.

In this newsletter, I’m sharing her best tips along with my own to help you get the most value out of this strategy.

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

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In this newsletter:

• Why dinners have replaced trade shows as the reigning champ of B2B events

• How to make sure your dinner is worth the investment

• Why a good dinner nails the 3 Ps: people, place, and programming

• Operational tips for making dinners repeatable

• For paid subscribers: A map of SF & NYC dinner venues hand-picked by the MKT1 community

MKT1 Unboxing: A quick break to unbox Wistia

Learn how to leverage video in the AI era from video marketing GOAT, Chris Savage, Co-Founder + CEO at Wistia. Wistia has evolved from “video hosting” into a one-stop video marketing shop. They handle hosting, embeds, analytics, recording, editing, social clips, podcast distribution, and multi-language dubbing—so if you’re looking for tools to help you manage video marketing, watch this:

Some stand out moments in this episode of MKT1 Unboxing:

• LLMs don’t watch videos, so you need to add context for AI search.

  AI tools read text, not video. Wistia makes video embeds LLM-friendly so your videos can actually be indexed and show up in AI search. Watch this clip »

• Most social clipping tools only grab what’s obvious.

  Clipping a single moment is easy. Finding the best moments across an entire recording is harder. Wistia’s new (beta) Remix feature does this for you, watch at 12:04 »

• Webinars work better when they’re part of your video stack

  Running webinars in the same place you host, edit, analyze, and repurpose video makes them easier to re-purpose and measure over time. Here’s how Wistia approaches it, watch at 19:49 »

Get started with a free trial of Wistia here »

MKT1 Unboxing is our new video series, each video is a 30-minute demo + conversation where I (Emily Kramer) unbox marketing and GTM tools — no slides, no scripts, no sales pitch. Just real tools, real workflows, and real talk. The goal: help you find AI tools worth using.

Now back to in-person events…

Why the “dinner” replaced the trade show

“Events used to be more trade show-oriented, taking advantage of other people’s events to leverage for lead generation. Now attendance at those just looks different. People are less inclined to travel to those large trade shows. So the new event model is using your own hosted events for deal acceleration.” –Sheena

Trade shows were the primary event model for decades. You’d sponsor someone else’s event, set up a booth, and hope decision-makers wandered by. But post-Covid, which forced everyone to figure out deal cycles without conference infrastructure, companies started questioning the ROI.

Companies were investing so much money sponsoring, not to mention their own employees’ travel costs and time, then crossing their fingers that the right people would come find them. As I said in one of my most successful LinkedIn posts to date, when I look at most conference booths, I just see dollars in trashcans.

But what many of these booth exhibitors noticed was that the most valuable moments were the side conversations: the dinner the night before, the coffee meeting in the lobby, the drinks after a long day on the floor. At some point, people started asking: Why not just do those things directly?

You control the budget, the venue, and the guest list. You can get the right mix of existing champions, active prospects, and warm accounts. You’re not trying to collect 500 badge scans from people who will never respond to follow-up emails. You’re connecting directly with ~12 people who are actually in your pipeline, actually evaluating you, and giving them a reason to move forward. Seems like a better use of money.

In some ways, the prospect and/or customer dinner is the oldest trick in the GTM book. Wine and dine your potential customers, close the deal. In my recent rewatch of Mad Men, which is the true historical record for how marketing once was, I saw Don Draper do this on repeat (though usually inappropriately).

But I’ve definitely seen this surge recently. The other reason these dinners are a go-to strategy is not just the reaction to the trade show reboot post-Covid, it’s of course, AI-related too. In the age of AI-generated everything, this kind of authentic human connection is a strong differentiator. A dinner forces real conversation. You can’t automate your way through it. That’s why it works.

And the last reason I think these dinners are surging right now: It’s never been easier to access and fully enrich account and contact data. What used to be a massive, manual process now takes minutes. You can do this quickly with tools like Clay, then feed it into your CRM—or even manage the entire event invite flow in Attio (like we do at MKT1).

Watch my 1 min walkthrough of how I manage exec dinners in Attio ➜

Watch our in-depth Attio Unboxing with Head of Success, Zev Leibowitz ➜

“People who go to these dinners tell me they want to either meet their peers, somebody interesting, or they want to learn something new that they can take back to their business. That’s ultimately what they care about. And ideally, it’s both. You’re helping facilitate those connections, and you’re helping facilitate the exchange of ideas.” –Sheena

Read more

We also polled the MKT1 community to build a map of 40+ venues great for company-hosted dinners. We have SF & NYC (for now!) and will continue to add to these over time.

Read more on building an IRL event strategy here & hosting successful dinners here. And you can find all MKT1 resources in our template library here.

Read more

What we cover in this unboxing:

• AI-searchable video (LLM-friendly embeds) → Wistia makes video transcripts readable by LLMs, so your videos can show up in AI search—not just the title.

• Remix long-form videos (new + in beta) → Instantly turn podcasts, webinars, and interviews into new videos by pulling the best moments from across the entire recording based on a prompt.

• Easily-repurposable webinars→ A fully native webinar platform with backstage control, higher-quality playback, built-in editing, and clean analytics for live and on-demand views.

• One platform, not eight tools → Hosting, embeds, viewer analytics, recording, editing, social clips, podcast distribution, and multi-language dubbing—all in Wistia.

Get started with a free trial of Wistia here.

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Hopefully, you’ve heard: I hosted a 4-hour virtual Gen Marketer Summit with 500 of you and 11 speakers from companies including Profound, Primer, Framer, Unify, Tofu, Closing Media, Clay, Stripe, and OpenAI in December.

The focus of the event was how to uplevel for the AI era by becoming a Gen Marketer (a term I coined last year).

During the Summit, I felt like I got a glimpse into the future, watching speakers show off the latest AI products and talk about how they are upleveling their teams to handle the AI shift.

And after talking with every speaker, watching the live reactions, and reading hundreds of questions in the chat, I got even more clear on what actually matters heading into the new year. I personally became more confident that “Gen Marketer” isn’t simply a new job title, but a baseline skillset all marketers need.

Since then, a few ideas—let’s call them “mantras”—have been buzzing in my head. So, this newsletter isn’t going to recap the event in full (because you can watch it here, and paid subscribers can get the slides from my keynote here). Instead, I want to focus on what stood out after the event (and trust me, I did a lot of reflection on the event because afterwards I was stuck inside with a flu-like situation for 10 days!)

In this newsletter

Here are 3 marketing “mantras” for the new year that came directly from speakers. I think they’re great reminders, whether you came to the event or not:

1. Being a generalist doesn’t mean being mid at everything

2. With new GTM tools, there’s no excuse for Random Acts of Marketing

3. The new bar: “Learnings per minute” for your audience

This newsletter covers what we mean by each of these phrases, why it matters, and gives you clips and quotes to dive deeper into each.

Watch the event replay

Here are the recordings if you want to catch up on the full event, broken up into chapters so you can jump to what’s most interesting:

• Keynote with Emily Kramer (that’s me) - get my slide deck here

• AI workflows for Gen Marketers with Profound, Tofu, Framer, & Unify

• Scaling paid efficiently with Primer & Closing Media

• Roundtable with marketers from Stripe, Clay, & Pear VC (ex-Vanta)

• Fireside Chat with Dane Vahey, Head of B2B Marketing at OpenAI

• Q&A from the audience with me

Thanks to our Gen Marketer Presenting Sponsors

Primer: Expand your paid efforts with Primer. Primer helps you build, enrich, and sync custom B2B audiences and deploy them across Meta, LinkedIn, Google, Reddit, and DV360 at 40–90% match rates.

🎁 Offer: Get 10% off an annual subscription with code MKT110.
🔒 MKT1 Perk Stack Offer: 30% off for customers new to Primer’s Annual Plan
_

Profound: Improve AI visibility and craft AEO optimized content with Profound. Track how you’re seen across ChatGPT, Gemini, and Perplexity, uncover real-time AI search insights, and build workflows to generate and optimize content.

🎁 Offer: Use code MKT1 for 20% off Profound Growth (new customers only)

—

And thanks to all of our Summit sponsors: Framer, Unify, Tofu, Closing Media

Join my new course: Gen Marketer Bootcamp starts January 27th!

If you loved the Summit and/or want an intensive of becoming a full-stack marketer for the AI era, I’m returning to teaching cohort-based-courses on Maven and my new course is open for applications.

If interested, check if your L&D budget covers courses. And Annual paid subscribers get a $100 discount (you’ll basically net $1 in this deal, since it’s only $99 for an annual subscription). Just comment that you’re an annual subscriber in your application, and if accepted, I’ll apply the discount.

Now on to the mantras…

Being a generalist doesn’t mean being “mid” at everything.

What stood out at the Summit:

Being a Gen Marketer doesn’t just mean you are a generalist. It’s a specific set of skills marketers need to operate in the AI era.

Ting Ting nailed it:

“I’ve always believed that the world sort of belongs to generalists. Being able to understand other functions well, being able to hold different mental models in your head of how sales works or product works, that’s what makes generalists strong. [Being a generalist] is not an excuse to be bad at multiple things or be mid at multiple things.” –Ting Ting Luo, Head of Product Marketing at Clay Watch ➜

And this explanation seemed to land with the audience:

“You might be sitting there thinking, I’m a growth marketer, I’m a product marketer, I’m a content marketer, I’m a partner marketer—does this apply to me? Yes. Gen Marketer isn’t just another job title—it’s actually the new baseline skill set for marketers. So, whatever role you’re in, you need to uplevel your skill set to gain more generalist skills for the AI era.” –Kramer Watch ➜

Why it matters:

Since it’s easier to build products, create content, distribute across channels, and access data due to AI, the skills needed to succeed and get your product noticed have changed. Marketing teams have been a bit slow to keep up here, and it’s time to face the music: Your skillset and your team’s core competencies need to change.

The AI era isn’t rewarding marketers who know one narrow thing in isolation; it’s rewarding generalists who can connect the dots.

But being a generalist doesn’t mean giving up your edge or your craft. It means being excellent at one or two core marketing disciplines, and layering on enough cross-functional understanding to move work forward without constant handoffs. Handoffs only slow you down when velocity is the name of the game, and maybe more critically, they hurt creativity. Gen Marketers are well-suited to remove bottlenecks and give your team both the edge on velocity and quality.

You might recall I’ve also called this a π-shaped marketer. A π-shaped marketer has deep expertise in two areas (for example, product marketing and growth), with working knowledge across the rest of the function. A Gen Marketer takes this a step further by becoming proficient in executing campaigns and using AI to orchestrate.

So, you don’t need to change your title, and you still need to be excellent at executing in your key area, but you also need to expand how you operate. The marketers who will thrive are the ones who can retain a core competency, but also translate ideas into campaigns, campaigns into execution, and execution into results—without needing a small army to get there.

What to watch from the Summit:

• Hear from our roundtable of marketers who came up in 3 different disciplines (product marketing, growth marketing, and content & brand) to become Gen Marketing Leaders. Thanks, Zena, Ting Ting, and Jenny! Watch ➜

• Learn why Gen Marketer is the new baseline skillset in my keynote Watch ➜

• See Gen Marketers in action:

  • See how Nick at Profound prototypes AEO products based on his deep understanding of their audience Watch ➜

  • See how James at Framer creates an event landing page and connects the data to other tools Watch ➜

Modern GTM tools leave no excuse for Random Acts of Marketing

What stood out at the Summit:

“Instead of just focusing on my one swim lane, I’m thinking about the whole swimming pool.” –Jenny Thai, Head of Marketing at Pear VC Watch ➜

With each new presenter at the Summit, we saw the future of GTM tools. These tools serve different functions and produce different outcomes, but they increasingly share the same core functionality: enrichment capabilities, workflows & agents, and AI prompting built directly into the product. Together, these tools leave no excuse for shipping generic content across disconnected channels that don’t align with your audience.

1. Enrichment: More of your GTM tools will enable you to pull in demographic, firmographic, and behavioral info about accounts and contacts—without manual research—to give you a full picture of your audience. That includes company size, industry, tech stack, funding, hiring signals, intent data, and increasingly, AI-derived insights from usage and behavior.

   What enrichment enables: When enrichment is built into your GTM stack, “we didn’t have enough context” stops being a valid excuse. Teams can define audiences, prioritize accounts, and personalize campaigns based on real signals—not guesses or static ICP slides.

2. Workflows & agents: Your GTM tools will enable you to define sequences of steps within a product or across products (i.e., lead fills out form from tier 1 account, add to CRM, alert Sales in Slack). AI-powered agents will take this a step further and decide how to progress work through various steps.
   
   Note: Some tools help you orchestrate workflows and build agents across many products (like Make, Relay, and Zapier), while other products (like Tofu, Unify, and Framer) are building workflows and agents directly into their platforms to connect their tools out to the rest of the GTM stack.

   What workflows and agents enable: Disconnected point solutions are becoming a thing of the past. Agents and workflows allow teams to run repeatable, end-to-end campaigns where signals trigger action, actions generate learning, and those learnings continuously improve execution. This is the infrastructure required to eliminate Random Acts of Marketing—and replace them with connected activities that compound.
   

3. AI prompting: More of your GTM tools will enable you to generate, adapt, and personalize content and creative directly inside the product—emails, ad creative, landing pages, call scripts, summaries. Instead of starting from a blank page or a generic template, you’ll be able to prompt to produce relevant “fuel” at scale, tailored to a specific audience, signal, or moment. As a side benefit, prompting within products will also help teams learn how to use the tool.

   What AI prompting enables: Prompting can remove creative bottlenecks, but only when paired with the right structure and inputs. As content creation gets built into tools that already have your proprietary data, brand guidelines, workflows, and analytics, you are more likely to produce work that resonates (and avoid generating slop). Add in a Gen Marketer with a high-quality bar and taste, and you can stand out!

Why it matters:

Now more than ever, Random Acts of Marketing™ just won’t do. When everyone can generate content and spin up channels quickly, throwing more spaghetti at the wall isn’t a strategy. You will simply not be able to keep up.

The good and bad news: It’s getting easier to run tightly coordinated campaigns with the new generation of GTM tools I just described, so:

• If you’re just doing random one-off activities, you’re toast (to put it bluntly).

• If you’re connecting activities, you’re only keeping pace.

• If you’re connecting workflows into repeatable campaigns, flywheels, or loops—and grounding them in real audience insights, leaning into clear Marketing Advantages™, and maintaining a high quality bar—you have a chance to win. (More on that in the next section.)

The other way to win: Most marketing teams are not set up today to meet the AI moment. With no “glue” connecting teams or owning campaigns end-to-end, impact doesn’t happen. By upskilling or empowering your team to act like Gen Marketers, who own connected workflows and campaigns, you can be a step ahead.

What to watch:

During the Gen Marketer Summit, several speakers walked through real workflows using modern GTM tools—showing what connected marketing activities look like in practice.

• In Tofu, Elaine shows how to re-engage closed-lost accounts by making repeatable, personalized, cross-channel campaigns based on account history and context (like why they churned) pulled in from other tools.
  Watch ➜

• In Unify, Austin shows how to trigger automated follow-up campaigns based on traffic source—specifically LLM-driven traffic—so high-intent, mid-funnel visitors don’t get lost and AEO work actually converts.
  Watch ➜

• With examples from Closing Media clients, Max shows us how to amplify top-performing organic LinkedIn posts into Linkedin Thought Leader Ads, extending the life of that content. I also wrote all about the “LinkedIn Flywheel” in this newsletter. Watch ➜

• With examples from Primer customers, Keith explains how to use paid channels to test messaging and audiences, then feed those learnings back into organic efforts, instead of running paid and organic in isolation. Watch ➜

• Bonus: To understand the AI skills you need, listen to Dane talk about the “AI primitives” he thinks all marketers should be learning. Watch ➜

You can watch all of these workflows and see the future of GTM tools here:

Focus on “learnings per minute” for your audience.

What stood out at the Summit:

I’ve always had a pretty simple bar for marketing work: does this actually add value to the audience?

Truthfully, it’s a quality bar that has annoyed people I’ve worked with over the years—can’t we just ship it?! But this bar, and the rigor behind it, matters more now than ever, because it’s simply too easy to make crap. That’s why I loved when Dane brought this idea up during the Summit, using his own framing:

“I have this informal metric when I think about content, which is learnings per minute…And I don’t think enough marketers really optimize for learnings when they think about their content.” – Dane Vahey, Head of B2B Marketing at OpenAI Watch ➜

And I also loved how Ting Ting reinforced that you can have both speed and quality when you don’t have too many cooks in the kitchen:

“We are able to move fast because people can take things from end to end…the death of a marketing team is when every single idea takes 20 people to execute.” –Ting Ting Luo, Head of Product Marketing at Clay Watch ➜

Why it matters:

You need to become obsessed with putting out work that meets the “learnings per minute” or “adds value” bar.

I can bring on amazing presenters to show you powerful GTM tools and impressive workflows all day, but simply using these tools isn’t enough. The reality is, everyone will be using these tools sooner or later.

These tools help you do your job with increased velocity, but they aren’t a substitute for marketing fundamentals, strategic thinking, and human judgment. Here’s how to balance using AI to move with velocity and coming up with creative ideas that will drive outsize impact for your company:

• Start with a real understanding of your audience, product, and market

• Be clear on your unique Marketing Advantages and how you can actually win

• Plan for big bet campaigns and initiatives that play to those strengths

• Spend time developing high-quality, differentiated creative fuel ideas—humans are needed here!

• Develop creative with a specific engine (or engines) in mind—and get it to the right audience at the right time

• Use AI to help you orchestrate, move faster, and explore ideas

• But, don’t just take what AI gives you: Have a high-quality bar for your big bets. Sameness is invisible! Don’t be vanilla!

And that’s why this is such a great time to be a marketer. We have tools that enable us to execute on anything we can think up, faster than ever before. But creativity, taste, and judgment are still what separate good from great.

What to watch:

All of that can sound abstract: intentionality, judgment, having a bar. So, to ground this in reality, during the Summit, I walked through campaigns that are actually working right now.

These campaigns have the following in common: a clear creative idea, rooted in audience understanding, leveraging real Marketing Advantages, pairing fuel and engine that actually go together, and run by Gen Marketers who are able to move fast without sacrificing quality.

• Watch me explain what works now when it comes to standing out from the crowd. Hint: be human, focus on education, and leverage your “ecosystem”. Watch ➜

• I walked through 4 campaign examples during the Summit:

  • Granola Crunched Watch ➜
    (The only Spotify Wrapped–style clone that actually stood out this year. That said, this is not an endorsement for your company to run yet another Wrapped-style campaign; in fact, probably don’t!)

  • Lovable SheBuilds Watch ➜

  • Profound Index Watch ➜

  • Clay World Records Watch ➜

• Hear Dane from OpenAI’s answer to this question: “What was a big bet or a large campaign that you ran in 2025, why did you choose it, how did it work? Tell me everything.” Watch ➜

Other takeaways and aha moments from the event:

I hope this newsletter has compelled you to watch (or even rewatch) sections of the Summit. I really do think we packed in the learnings per minute (but I’ll leave that to you to decide).

Here are some other moments you may want to check out:

• Nick from Profound on what drives AI brand visibility: “If you’ve heard about AEO research or content, you might know that FAQs are things that LLMs love. Why is that? LLMs are lazy. They want to be served up an answer without spending a lot of compute power figuring this stuff out.” Watch ➜

• Keith from Primer on paid in 2026: “If inventory is constrained, and competition is rising, what is paid for in 2026? I think the new moat is not how much you spend, it’s how quickly you learn. Execution is easy now. AI killed execution, scarcity, everyone can launch fast, everyone can test fast. Everyone can spin up creative fast. The winner is not the biggest spender. It’s the fastest learner in this context. So you just have to optimize faster.” Watch ➜

• Zena Davé from Bridge on career trajectory in the AI era: “I don’t feel the need to build a kingdom of people…just because I don’t have a ton of people around me or under me doesn’t mean [this new role] was a step back by any means.” Watch ➜

🙏 Thanks again to our Gen Marketer Summit sponsors, all of whom have discounts for the MKT1 community!

Profound: Get your brand mentioned by LLMs, track visibility & improve AEO
🎁 Offer: 20% off Profound Growth Plan with code MKT1

Primer: Target your B2B ICP on B2C ad channels with precision targeting
🎁 Offer:10% off annual subscription with code MKT110

Framer: Site builder trusted by startups to fortune 500: Integrated CMS, SEO, & Analytics
🎁 Offer: Free Year of Pro ($360 Value). Apply to startup program.

Tofu: Ship integrated, cross-channel campaigns faster
🎁 Offer: Mention MKT1 for 10% off Tofu Starter package

Unify: Capture intent signals, run AI agents, and send personalized outbound
🎁 Offer: Mention MKT1 for 10% off an annual plan

Closing Media: Boutique agency partner for LinkedIn ads and paid media campaigns
🎁 Offer: Mention MKT1 for $5,000 of free ad spend for your next campaign

More from MKT1

🏕️ Gen Marketer Bootcamp: My new course starts January 27th and is open for applications! Paid annual subscribers get $100 off (pending acceptance; mention your subscription in your application to redeem).

📦 MKT1 Unboxing: Watch the first in our new video series to see Kramer (that’s me) unbox Luma AI & Attio.

🥞 MKT1 Perk Stack: Exclusive discounts worth $40K+ on our favorite GTM tools. For annual & superfan paid subscribers only.

🧰 Revamped, upgraded template & resource library: We have 100+ templates and resources available to paid subscribers in our brand-new template library.

🛠️ MKT1 GTM tools library: An organized, sortable list of recommended products on MKT1.co.

🧑‍🚀 Job board: Jobs from the MKT1 community (free to post as a paid subscriber)

🍽️ MKT1 Supper Club: Get on the list for monthly IRL dinners with Kramer, a small group of smart marketers, good food, and conversations on topics that actually matter in your role—made possible by some of my favorite GTM tools. Join the list here.

Read my takeaways from the Gen Marketer Summit in this newsletter. And you can find all MKT1 resources in our template library here.

Read more

But before we get to our most sought-after resources and templates this year, we have some housekeeping items.

1. Gen Marketer Summit replay: If you couldn’t make it or just want to relive the 4-hour experience over and over, here’s the link. And if you missed out on the partner discounts we shared live for Primer, Profound, Framer, Tofu, Unify, or Closing Media, you can access them here.

   We’ll share edited, chapterized, and clipped up versions in early 2026, but many of you simply couldn’t wait for our editing process to catch up. So before we send that to everyone, our paid subscribers get a first (second, really?) look.

2. MKT1 Perk Stack: Need to use up your end of year budget for tools? Get started on yo…

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As I proclaimed back in September, we’re in the era of Gen Marketers™. Gen Marketers are generalists who are fluent in generative AI, and who are ready for the generational shift we’re seeing in marketing.

But “Gen Marketer” isn’t another job title. It’s the new baseline skillset marketers need to succeed in 2026 and beyond. No matter your role in marketing, you will benefit from gaining a Gen Marketer skillset.

In other words, how we build B2B marketing teams has fundamentally changed in the last 2 years. And if you’re still hiring, interviewing, or organizing teams the old way, you’re probably struggling to keep up with the pace of change.

Candidates need to bring different skills to interviews (and to their roles!). Hiring managers need to evaluate candidates against new criteria. And Heads of Marketing need to evolve their org charts and practices.

This newsletter will help you get hired and hire in 2026. It’s your guide to the Gen Marketer skillset: the foundational capabilities every marketer needs to be effective now. It covers what types of candidates are most needed in the AI era and how to tactically gain those skills if you’re on the job market—or if you just want to stay competitive in your current role.

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

➜ Default puts scheduling, routing, and enrichment in one platform, so the data in your CRM stays clean and you can orchestrate GTM 10x better. Plus, it’s used by startups like Replit, Profound, Unify, JustWorks, and Decagon.

🎁 Offer for all readers: Mention MKT1 to get 2 months free on any plan for up to 10 seats ($1500+ value)
🔒MKT1 Perk Stack offer for annual paid subscribers: Get 5 seats free + 1 year of free intent data with a new annual plan.
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➜ 42 Agency: Let 42 Agency handle the MOPS work your team avoids. From routing logic and fixing scoring, to aligning Hubspot + Salesforce, to setting up new GTM tooling, 42 Agency is ready to help your B2B startup clean up and scale your ops.

🎁Offer: Mention MKT1 to get 10% off a Hubspot Audit or Hubspot Sprint.

__

➜ Ten Speed is an organic growth agency that unifies SEO, AEO, content marketing, and digital PR. They know how to combine the right fuel and engine for your ICP—and they’ve supported many of my advisees.

🎁Offer: Mention MKT1 to get up to $5,000 off.

In this newsletter:

• Part 1: The skills all marketers need (and need to hire for) in the AI era

• Part 2: Actionable steps to learn these skills and become a highly in-demand candidate

• Part 3: Interview questions to assess these skills—whether you’re practicing or hiring

• Bonus: Open roles that value the Gen Marketer skillset

• Conclusion: How to network like it’s [almost] 2026

This newsletter is a companion to the Gen Marketer Summit next week!

• The virtual Summit is for paid MKT1 Newsletter subscribers only. It’s only $9 a month or $99 a year. You also get access to our template library, Perk Stack (for annual subs), and all the other benefits of being a paid subscriber.

• But, if you’re currently unemployed, you can get free access to the event. Fill out this form (passcode: 1010) to RSVP.

RSVP for the Summit

Part 1: Skills all marketers need right now, in the AI era

If you’re job searching, these are the skills that will make you stand out. If you’re hiring, these are the capabilities you need to evaluate for—not just nice-to-haves, but fundamentals that determine whether someone can operate effectively in the AI era.

Do you need to abandon everything you ever learned and just focus on this skillset? Of course not. But since publishing my Gen Marketer newsletter, I’ve had many conversations about what this means for specialists. So let me be clear: This isn’t about abandoning specialization. If you’re a killer demand gen marketer or a product marketing expert with deep domain knowledge—great, keep that. But that specialization alone isn’t enough. You need to layer generalist skills on top of your depth to stay valuable in 2026 and beyond.

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This past week I’ve been spinning on newsletter topics. Staring at a list of ideas, starting to write, backtracking, scrapping paragraphs, rewriting them again. Nothing felt quite right.

And honestly, that feels like the default state of marketing right now.

We’re all scrambling to break the mold and stand out. We’re overwhelmed by everything we could do, yet underwhelmed by the results of what we are getting.

Then it hit me: The best follow-up to my recent annual planning newsletter isn’t more prioritization frameworks or more structure. It’s the opposite. Whenever I’m advising marketers, the biggest breakthroughs come from thought experiments: hypothetical exercises with a few intentional constraints. These conversations force new ideas to the surface and bend your brain just enough to reveal ideas that might actually work.

So this newsletter shares 5 of my go-to thought experiments. Simple, occasionally uncomfortable prompts to jolt you out of the rut and help you rethink your 2025 strategy with a fresh, more creative brain.

Recommended products & agencies

We only include sponsors we’d recommend personally to our community. If you are interested in sponsoring our newsletter, email us at sponsorships@mkt1.co.

➜ Default puts scheduling, routing, and enrichment in one platform, so the data in your CRM stays clean and you can orchestrate GTM 10x better. Plus, it’s used by startups like Replit, Profound, Unify, JustWorks, and Decagon.

Offers:

🎁 All subscribers: Mention MKT1 to get 2 months free on any plan for up to 10 seats ($1500+ value)

🔒MKT1 Perk Stack offer for Annual paid subscribers: Get 5 seats free + 1 year of free intent data. Redeem here.

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➜ Luma AI: Before you outsource your next video production, try Luma AI’s Dream Machine, an AI-powered video generation platform. Start with text, an image, or another video to produce and edit on-brand, cinematic-quality content in minutes.

See more: Luma AI is featured in today’s Unboxing video!

🎁 Offer: Mention MKT1 to get 20% off an Enterprise Essentials plan.

__

➜ 42 Agency: Let 42 Agency handle the MOPS work your team avoids. From routing logic and fixing scoring, to aligning Hubspot + Salesforce, to setting up new GTM tooling, 42 Agency is ready to help your B2B startup clean up and scale your ops.

🎁 Offer: Mention MKT1 to get 10% off a Hubspot Audit or Hubspot Sprint.

In this newsletter:

5 thought experiments and how to run them:

1. No new content

2. No new target accounts

3. Positioning stress tests

4. Would you rather

5. Pick your dream speaker

More from MKT1:

• I unbox Luma AI in our 2nd video in our new Unboxing series, which helps you discover new GTM tools

• Gen Marketer Summit: Registration is open for our first-ever virtual conference! We’ve announced the first wave of speakers, more coming soon. Free for all paid subscribers.

• MKT1 Perk Stack: Exclusive discounts worth $40K+ on our favorite GTM tools (like Lovable, AirOps, Framer, Default, and more). For annual & superfan paid subscribers only.

Thought experiment newsletter

Use these when you’re stuck, overwhelmed, or circling the same ideas during planning. Thought experiments work because they drop you into a constraint that forces new thinking. Pick a prompt, treat the constraint as real, and follow it through with hypothetical examples to see where the discussion goes. The goal isn’t to “solve” anything; it’s to shake you out of your defaults, surface blind spots, and make you see things from a new angle.

THOUGHT EXPERIMENT 1

No new content

To start, here’s one of my favorite questions to ask startup marketing teams to get them out of their comfort zones. I first shared this thought experiment in a series on my own content strategy.

The prompt

What if you weren’t allowed to create any net-new content for the next quarter, or even six months? In this hypothetical, you can reuse things you have and modify things slightly for new channels, but you must grow by distributing existing assets. What would you do? Do you think this would help or hurt your ability to hit your KPIs?

Why this experiment

If you are over-indexing on creating “fuel” and under-indexing on building an “engine” to distribute, this thought experiment will help you recalibrate.

Teams default to creating new things instead of deepening and compounding what already works. They set content goals around volume (i.e. “15 new pieces of content a month”), but never meaningfully distribute that content.

The best ideas may just be extensions of things you’ve already created. More ROI may come from redistributing things you already have (aka getting more mileage). This experiment exposes how much growth is trapped inside your existing content.

Consider this..

• What would happen if distribution—not creation—became your focus for a whole quarter?

• Which pieces of existing content have never been fully distributed?

• What would happen if you “franchised” your best ideas? What could become a series or workshop?

• What content is outdated but fixable?

• What 5–10 existing pieces, if improved, would outperform anything net-new?

• Which assets should have driven a key KPI but didn’t? Would distributing or repackaging help?

• What content types perform best channel by channel, and could these be extended or tweaked to serve other ICPs and/or work on other channels?

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• Paid subscribers: Jump down to get the access code and RSVP.

• Free subscribers: This event is for paid MKT1 Subscribers only. Not paid? Upgrade for costs $9 a month or $99 annually.
  If you upgrade for just 1 month to attend the conference, I won’t hold it against you, but a paid plan also gives you access to our 100+ templates & resources and archive of posts—plus annual subscribers get access to our new Perk Stack.

Subscribe now

Thanks to our presenting partners: Primer | Profound
And our sponsors: Framer | Tofu | Unify | Closing Media

Agenda

All times approximate and in Pacific Time, but I 🧡 my global audience.

• 9:00 - 9:35 AM: Welcome & Keynote with me, Emily Kramer

• 9:35 - 10:40 AM: AI Workflows in Profound, Tofu, Framer,& Unify

• 10:45 - 11:15 AM: Paid Marketing in the AI Era with Primer & Closing Media

• 11:15 - 11:55 AM: How we became Gen Marketers: Zena Davé (Bridge by Stripe), Ting Ting Luo (Clay), Jenny Thai (Pear Ventures, Ex Vanta)

• 12:00 - 12:35 PM: Fireside Chat: Emily Kramer & Dane Vahey (Head of B2B Marketing at OpenAI)

• 12:35–1:00 PM: Q&A with Emily Kramer

Discounts from our Summit partners

Each partner of the Gen Marketer Summit is offering a special discount for attendees. These discounts are for new customers only. Some of these partners are also in our Perk Stack for annual paid subscribers.

• Primer: 10% off an Annual Plan with code “MKT110” or unlock the Perk Stack Offer for annual subscribers

• Profound: 20% off Profound Growth Plan with code “MKT1”

• Framer: Get a free year of Framer Pro ($360 value) by applying to their startup program at framer.com/startups or unlock the Perk Stack Offer for annual subscribers

• Tofu: 10% off Tofu Starter Package, mention “MKT1”

• Unify: 20% off an Annual Plan, mention “MKT1”

• Closing Media: Get $5,000 of free ad spend for your next campaign, mention “MKT1”

RSVP now

(Below the paywall!)

This event is for paid MKT1 Subscribers only. Not paid? It costs $9 a month or $99 annually. And if you upgrade for just 1 month to attend the conference, I won’t hold it against you.

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We’re getting a headstart today with our most valuable launch to date: The MKT1 Perk Stack. Think of it as a caffeine for your GTM Tool budget…still working on the metaphor here.

➜ Perk Stack
➜ Gen Marketer Summit access for paid subs
➜ New resources & tools recap

MKT1 Perk Stack: $40K+ off GTM tools for $99 annual paid subscription

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