Founder | B2B GTM | Scale without headcount by mapping your playbooks into an AI revenue engine

Be honest - how many Linkedin posts have you seen this year saying that XYZ tech/playbook/widget is absolutely essential to your GTM this year?

Probably a lot

We now have thousands of sales and marketing technologies on the market

And all of them are pitching their solution as best in class

With playbooks, agencies, influencers to sell them

And yes, we have preferred tech vendors

Here's the difference

We don't throw you in canned playbook, we actually look at your Go to Market model before making recommendations

Let me tell you a funny story

I talked with an SDR team that was booking 80 meetings a month with parallel dialers and 10k emails per SDR per month

But 60% of their meetings got disqualified

Why?

They didn't qualify target accounts before doing outreach

Tech and playbooks don't save you deploy the wrong one at the wrong time

So what do we do different?

When you work with us, we start with an assessment

We look at your funnel metrics, your best customers, your messaging/copy, and get input from your team on detailed attributes that make up a great customer

That you CAN'T find in an off the shelf tool

After that we use our knowledge of best practices and tooling to identify the biggest opportunities to unlock more revenue per headcount in your team

This could look like

> Customer analysis
> Serviceable Addressable Market Mapping (because TAM is where you lose deals not win them)
> Target Account Lists
> Automated Contact Prospecting & Enrichment
> Pipeline Validation (we build out a script, test it to book meetings for you, help you take the meetings through completed discovery with next steps, then give you a completed call framework, email sequence, and discovery framework)
> Outbound Sales Team Coaching (Phone first)
> Sales Process Optimization
> Managed Cold Emails & Cold Calling
> Inbound Lead Flow Optimization
> AI Business Case Building (which we used to open a $300k+ opp at UPS)
> Implementation of Nooks, Clay, Evergrowth, and other sales tooling

Yes, we do that under one roof

Yes, it was very hard to find a team good enough to do all of this in one place

If you want to learn more, book a time here: https://calendly.com/b2bcatalyst/your-gtm-system-audit-linkedin
> Cold Email Infrastructure

Scott Martinis

GTM engineers & AI platforms are trying to figure out GTM context engineering by reinventing product marketing from first principles. Most will fail.

Context - I am seeing a ton of really smart people like Nico Druelle, Charlie Saunders, Alex Fine🌲, 🏍benyamin ‎ and others start to work on the problem of how to create centralized context libraries to iterate on messaging and targeting.

I am also seeing many platforms try to do the same thing.

The operators I included above will probably succeed. 

The platforms and GTM engineers that follow in their footsteps will largely fail.

Why?

Simply put - GTM context engineering is effectively reinventing a complete and fleshed out disciple (product marketing) from scratch.

Given INSANE amount of training volume, ML modeling (Karpathy released a new library to help automate this) CAN effectively invent the necessary cognitive architecture to help generalize those patterns.

Outreach could probably do this if they really wanted to. Gong as well.

But that's a waste of time, and anyone with less training data will probably fail horribly.

Think about what ACTUALLY happened to optimize messaging in high performing GTM orgs years back:

Product marketers would run meeting analysis, win/loss interviews, customer interviews, and talk with analysts.

They would then consolidate this into strategic narratives, positioning frameworks, competitive battlecards, ICP/segment/persona definitions, and value frameworks for major audiences.

If you want to do context engineering, you could try to reinvent this discipline from first principles.

But you're going to demonstrably slower than people who just... 

Interview good product marketers 

And figure out how to automate the product marketing analysis pipeline.

The marketers I've been most recently impressed with on this front are Emily Pick, Julia Hugg, Trinity Nguyen 💎

Octave, of course, is way, way ahead of the pack here.

Instead of trying to figure this out all by themselves, GTM engineers and revops leaders should take the shortcut and take the time to learn product marketing from elite practitioners instead

This was why all the AI SDRs failed by the way. 

It's not the lack of data foundations that broke them as many revops people supposed (though that doesn't help)

It was actually the lack of understanding the GTM strategy is quite complex, and guessing and checking without proper PMM foundations is not fast enough to get ROI on automated outbound.

What does this mean?

Well, the actual foundation of your GTM strategy is not revops OR GTM engineering, it's REALLY good product marketing

Both of those functions rely on good PMM to build good data models and automated workflows... though they both relying to some degree on well thought out enablement playbooks to know what to include in the data model and what to automate as well.

TLDR: model your context engineering on PMM. Will save 6-12 months.

I make AI work for complex B2B GTM through pipeline impact, not data projects | CEO, B2B Catalyst

So it turns out you can CSV dump from every GTM tool into your GitHub repo then Claude Code can write you data lake scripts in like... 20 minutes?

And if you dump in cold call transcripts from Gong or Chorus then you can basically rewrite any messaging playbook your org has in a few hours

Working next on ways to extract use cases from sales calls at scale, map in depth what messaging wins and loses

Then take the use cases and scrape online presence of won deals to extract custom signals

Tag won and lost deals with them

And build custom signal models predicting win rate and ACV

Future is pretty wild

Next up:

- Automated coaching briefs across the org
- Down funnel marketing campaign attribution
- Automated and targeting iterations for marketing campaigns and sequences
- Weekly or monthly auto playbook updates broke. down by segment
- Weekly or monthly value framework updates, battle cards, competitor battle cards (possibly automated)

Of course the more normal use cases like 

TAM scraping, signal sourcing, account prioritization, contact sourcing, qualification, classification 

TitanX phone intent

AI outbound personalization on emails calls LinkedIn

AI content generation and amplification 

AEO

AI inbound and outbound SDRs

Personalized ABM content

Personalized meeting prep

ETC

Candidly those feel a bit more pedestrian and table stakes to me though in 2026

Still... very exciting possibilities for GTM orgs

The key I think is knowing where to start

Which is usually your biggest bottleneck 

(DM me "context lake" if you want this in your org)

Every GTM intelligence tool is racing to answer the same question: who should we target?

Intent data. Buying signals. De-anonymization. Account scoring.

The targeting layer is getting genuinely good. 

And it's about to be commoditized. 

The same way signal aggregation became table stakes after Clay and 6sense turned it into infrastructure.

There's a deeper problem.

These tools are optimized for finding people who want to buy tools like them. They surface intent signals and firmographic matches.

They don't find the prospects where YOU have a differentiated advantage at closing.

That's a different ICP layer. Not "who looks like our customers" but "who has a problem we solve better than anyone else."

Most teams build messaging off the same shallow foundation. Company value props plus signals. "They just raised a Series B, mention growth." "They posted a sales role, mention scaling."

Relevant first line. Generic pitch.

The signal tells you WHEN to reach out. Your value prop tells the buyer what YOU think matters. 

Neither one tells you what the BUYER thinks matters.

The thing that converts is explaining why your solution beats the buyer's current state in a way they actually agree with.

That's differentiation. And it's missing from almost every discussion on signals & ABM I've seen. 

A VP of Ops at a 200-person logistics company. What's her job-to-be-done? What objection does she raise first?

That's not in your intent data. It's in your call recordings. It's in the patterns your best reps know but nobody's formalized.

Pull your last 30 closed-won deals. Listen to the first calls. What did the buyer say they cared about? Group them.

You'll find 3 to 4 patterns. Those are your real use cases.

Each one should shape both WHO you target and WHAT you say. Not a template with a different first line. A different reason to meet, built on why your solution changes their current state.

The targeting will keep getting smarter. The message won't get better until someone studies the buyer.

If you want help building this layer, DM me.

I rebuilt my company's website through an MCP inside Claude Code. Told my AI co-worker what to change. It read the Webflow data directly, made the edits, and published.

Mostly. I still had to open Webflow for some formatting changes the MCP couldn't handle. But 80% of the work happened without touching the UI.

That alone changed how I think about platforms.

MCP is Model Context Protocol. It lets AI talk directly to a platform's data and take actions.

Every legacy platform is walking the same path right now.

Step 1: Platform. You log in, click buttons, build reports, configure sequences. Standard SaaS.

Step 2: The AI can READ the platform's data. Pull reports, see pipeline, check analytics. You still log in to do anything.

Step 3: The AI can ACT. Create records, update fields, trigger workflows. You log in less.

Step 4: The AI owns the domain. It decides what to do, does it, reports back. You make decisions. You rarely touch the platform.

I'm somewhere between step 3 and 4 with Webflow. It's not perfect. But the direction is clear.

Now think about Salesforce, HubSpot, Outreach, Salesloft.

Once an AI can read your CRM, update records, pull analytics, manage sequences, and trigger workflows.. what's the UI for?

Salesforce has Einstein. HubSpot has Breeze. Outreach has "AI everywhere."

Bolting a chat window onto a legacy platform is step 2.5 at best. And the companies building step 4 aren't starting from step 1. They're starting fresh.

Pick the GTM platform you use most. Map it against the 4 steps. Where the AI feature actually sits vs. what the marketing claims will tell you everything you need to know about that vendor's roadmap.

Maximus Greenwald

ceo @ warmly.ai | revenue ops obsessed | ex-google | follow to watch me try to build a sales tech unicorn

Follow me for researched insights around Demand Gen, Sales & Marketing problems and how they can be solved with AI, grit & Purple Cow Marketing 🟣🐮.

Go-To-Market & Marketing for B2B will change forever with AI. From talking to 100s of CMOs & CROs from our customer base, we will soon see legendary, small demand-generating marketing teams who create massive pipeline with full-funnel orchestrations & automation. I'm deeply passionate about building AI Marketing & Sales Agents to aid this evolving landscape. 

Founders - Read my founder newsletter "Going CLEAR" to get the behind-the-scenes on growing our AI Marketing startup, Warmly. https://www.linkedin.com/newsletters/7174798574000439296/

GTM Teams - How to build a repeatable sales motion from 0 to 250+ paying customers:
> https://www.growthunhinged.com/p/the-path-from-0-to-100-paying-customers
> https://www.growthunhinged.com/p/a60761fe-4af2-4a29-9ca7-7b479565f31a

Personal interests: triathlons, telemark skiing, chess, rugby & freestyle rap (amateur but having fun)

Warmly,
Max

Cofounder & CEO

maximus greenwald

So our app goes down during our team offsite… 

Ship Happens | Ep 1: The Outage

Take a peak behind the scenes of the shenanigans we get up to at Warmly. It's pretty accurate honestly.

Never a smooth ride!

ps. the app did not actually go down, Claude (& Binil) would never allow it. No Claude's were harmed in the making of this film.

ceo of warmly.ai, the #1 GTM brain for agents and humans | sharing behind-the-scenes marketing insights & trends | ex-Google & Sequoia scout

I actually have no idea what I'm supposed to do now... does anyone know how to do stuff?

My sales team skipped prospecting hour to go to dinner instead. I should have been angry but I wasn’t.

Why? Because our TAM agent prospected for them while they ate.

We’re entering into a wild era - full telemetry into B2B buyer behavior combined with the muscle of AI (across the web and your CRM) to find your best leads.

But it’s hard to make this list:
- you can’t ask Chatgpt to find you 10 leads that will actually convert
- you can’t ask your CRM to find you 10 leads that will actually convert

You need a long term memory store of your GTM data combined with the world’s data to make it happen.

The result is a ready-for-you prospect list that updates each hour and can be sent into any channel by inbound/outbound/human agents

We’ve been hard at work testing our GTM agent harness with our customers & are excited to show folks now —> check out our website to learn more about Warmly, ‘s TAM agent.

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Update #86: Feb 2026... Here are our real numbers from last month & my learnings:

- MRR: $571,751 (+5.89%) 
- Last Month Net Revenue Projected (Actual): $350,000 ($381,360)
- Last Month Upsell Revenue: $34,065

BACKGROUND:
- I started Warmly in 2020 with my cofounders after quitting Google to change the world of GTM
- We were slapped in the face with humble pie having 0 knowledge in sales & marketing/ pivoting 6 times in 3 years
- Once we stopped "playing startup" & got to work we grew 0 to $1M in 2023, $1 to $2M in 2024, and $2M to $6M in 2025
- Our next goal is $10M ARR & to get there we need to really unlock a marketing engine

What we do (now): Warmly is #1 Agentic Marketing Teammate that warms up your TAM by collaborating with both humans + agents.

For example our Outbound & Inbound Agents to engage your hottest leads omni-channel (on chat, email, linkedin, ads) so you can book meetings while you sleep.


📚Read on to learn: 

↳ reflections on pricing complexity with credits

↳ about our website rebrand & Agentic GTM Brain

↳ how it really frustrates me we need to devote resources to cost optimization


💡Asks:

↳ Hiring AEs: Come sell a product you can use yourself to hit quota! Must have prior experience selling $30k+ ACVs DM Keegan Otter (Software Cowboy 🤠)

↳ Are you looking for SDRs? Hire AI-enabled ones by reaching out about our SDR placement program WarmLegency by Warmly,!

♻️ Repost to help other saas founders & GTM teams learn or investors to get benchmarks for the sales tech space

Metrics - Feb 2026 Warmly Lead Platform MRR: $571,751 (+5.89%) This Month Net Revenue Projected (Actual): $350,000 ($381,360) This Month Upsell Revenu

Open article: [Update #86] Feb 2026: Start of the Agentic Marketing Teammate by maximus greenwald • 4 min read

[Update #86] Feb 2026: Start of the Agentic Marketing Teammate

📣 Drift is sunsetting. If you need a new chat tool, we'd love to migrate you to Warmly's Inbound Agent - the #1 chat solution for both Humans & AI with a deep Salesloft Integration.

In the last 6 months we've switched over 20+ Drift customers to Warmly because of our 1:1 feature match combined with simplicity & AI.

Top reasons Drift-switchers pick Warmly:

1/ Advanced workflows for reps with lead routing, scheduling, round-robin [we will migrate your old Drift workflows for you]

2/ Ultra-simple AI workflows trained on your website, content, sales-calls with enterprise controls to test & train and make sure the AI talks in your brand voice

3/ Auto-followup in Salesloft cadences if you miss the prospect while they're on the website

4/ Customizable brand control

5/ Pop-ups & offers to help drive more conversions

A guy named his company "AI Slop" backwards. Then took it to $3M ARR in under 3 months (+$1M in the last 3 days).

One founder. 
Zero employees. 
Thousands of AI agents running 24/7.
Meet Ben Cera and Polsia. <--- the name gets me every time.

A few years ago Ben ran a food company.

Then he moved to San Francisco, slept on a couch for two years, taught himself to code with AI, and started building.

What he landed on was Polsia. 

A platform that does not help you run a company. 
It runs the company for you.

AI agents that plan strategy, write and ship code, launch marketing campaigns, allocate ad budgets, cut what is not working, and double down on what is. 

Every morning the agents report back, like a team that never sleeps.

He launched mid-December 2025. 
Today he sits at $3M with 3k+ active companies on the platform. 

The model is simple. 
$49 a month gets you servers, databases, email, marketing, engineering. 
Then Polsia takes 20% of ad spend.
They only win when you win.

I signed up Warmly to learn how this might work and in 20 minutes it had researched us, created a landing page for us, started sending cold emails for us & even produced our first ad on Meta with a live tracking script for attribution

There are 2 VPs of Marketing at Series B Companies ($30-$50M ARR). & 1 is getting fired for not building this GTM Context Graph:

VP #1 has Salesforce. HubSpot. Gong. Clay. 6sense. Apollo.

Every tool has a login. Every tool has a dashboard. Every tool has a CSM asking for a QBR.

None of them share context with each other.

VP #2 spent 3 months doing something different. Connecting the ones they have into a single brain their whole GTM team can talk to.

Here is exactly how VP #2 built it.

Step 1: Pick a shared agent harness.

This is the command layer. The place your whole GTM team goes to ask questions, run plays, and direct agents. Think of it like a cockpit. You can use Claude, ChatGPT, or any LLM that supports MCP (Model Context Protocol). 

MCP is just a standard that lets AI models talk to your tools directly instead of requiring a human to copy-paste between them.

Step 2: Connect your tools to it via MCP.

Most major GTM tools now have MCP servers. Salesforce. HubSpot. Slack. Google Calendar. LinkedIn. You connect them to your agent harness the same way you'd connect an integration, except now your AI can read and write across all of them in a single session.

Your CRM data. Your email engagement. Your intent signals. Your meeting notes. All of it visible to one agent at the same time.

Step 3: Layer in specialized agents for each GTM job.

This is where it gets interesting.

Your agent harness is the brain. But the actual work gets done by specialized agents that each own one job with near-perfect accuracy. 
One agent handles identity resolution. 
One handles buying committee mapping. 
One handles intent scoring. 
One handles outbound personalization.

You are commanding a fleet where each agent is built to do one thing well, and the harness coordinates them.

(This is exactly what Warmly, by the way is built to be: one of those specialized agents. The one that de-anonymizes your website visitors in real time, maps the buying committee, scores intent across first and third party signals, and surfaces who to talk to before your rep even opens their laptop. 

It plugs into the same harness as your other agents. It does not try to replace them.)

Step 4: Feed outcomes back in.

This is the step most teams skip and it is the only step that makes the whole thing compound.

When a deal closes, the context that closed it needs to flow back into the graph. When a deal dies, same thing. 
What signals were present. 
What plays ran. 
What the buying committee looked like. 
What message worked.

Over time your context graph stops being a connection layer and starts being an institutional memory. The patterns that close deals at your specific company, in your specific market, with your specific ICP, get encoded. Not in someone's head. In the system.

The reason VP #1 is getting fired is not that they have the wrong tools.

It is that they have 30 tools producing 30 different answers to the same question: who should we focus on right now?

If you email like an exec, you'll get responses like an exec. & its not something any AI system can write for you. Here are 8 ways to get replies tomorrow (for non-execs):

(The irony btw is not lost on me as someone who sells intent data & outbound sdr AI.)

But I do study how to maximize cold email replies for a living. Here's what 100,001+ high-touch cold-ish outbound emails have taught me:

1/ Throw everything you ever know about formality out the door.

Busy ppl don't care about formality, they care about getting results w/ as little effort as possible.

If you Dear Sir, or To Whom It May Concern --> delete.
If you "My name is X and I'm an SDR at Y" --> delete. (& I know who you are dude, your name is in your email header)

2/ Brevity > everything else (but w/ a PS. trick).

You only get 3-4 sentences. If its longer than that, it takes me work to read.
I don't want to do work.

Trick: I shove 3 extra sentences in the PS as bullet points. It always works.

PS's are juicy & they don't count since they're after your sign-off

3/ Abbreviate b/c you seem more important.

Use commonly accepted business-casual abbreviations (w/ b/c w/o fyi fwiw).
No lol.
No slay queen.
Most execs aren't genZ yet.
But busy game respects busy game.

4/ Don't ask for their time, ask for their reply

Execs don't want to meet w/ you
I dont want to meet w/ you
Ask them to loop in someone else (an EA to schedule them or a named champion)
Nothing makes an exec more a hero than getting the win of replying while making their report do the work

5/ subject line needs to trick them into thinking they know you / continuing a convo

a busy inbox is divided into: 
(a) is this something new I have to do (low reply)
(b) is this something existing I should push forward (high reply)

examples:
"FWD: Continuation of pipeline discussion with {{Champion}}?"
"re: Linkedin DM on AI marketing agents (Warmly AE) - time next week?"
"Jonathan intro: looping in your Demand Gen Leader?"

^ who is jonathan? tbh it doesn't matter. 

could be fake name (works). 
could be your name (works 2x). 
but ideal if you had any interaction w/ someone on their team before & reference them (works 3x). 

6/ have a unique sign-off like "warmly,"

I will die on this hill. 
So many people disagree with me.
Call me biased.
But "sincerely" is not cool. 
"Dangerously," and "consequentially," are cool.

7/ no more than 2 lines per paragraph ON MOBILE

Your exec is reading this on mobile phone while putting kids to bed at 8pm

She's not wearing her glasses so small print is kinda hard to digest 3+ lines

A block of text means no read
Test how someone could read your email in 20 seconds and reply in 10.

8/ send email at night their local time or weekend

I have 1 trillion problems to solve during the work day
I promise you replying to your AI agent demo request is not one of them
Catch me when I'm procrastinating taking out the trash (or don't email me at all)

As long as buyers are human, this will work for you.

About 18 months ago, my co-founder Alan and I launched a podcast called Revenue Rebels & it failed. I thought the name was great. We booked some guests. Talked to revenue leaders. Put episodes out there.

And it just... didn't land.

No real theme. No narrative arc. 

No reason someone should pick us over the 50,000 other MarTech and sales tech podcasts fighting for attention. 

We were throwing spaghetti at the wall and hoping for "traction."

So we stopped. 
Classic founder move.
If the numbers don't pop in month one, kill it and move on to the next thing.

That was a mistake.

I sat down with Dave Gerhardt for Episode 6 of Founder Brand and he called this out directly. 

He said the single biggest mistake founders make with podcasting is treating it like a short-term campaign. 

He compared it to training for a marathon. 
You don't run 5 miles and decide running isn't for you.

His own Exit Five podcast only hit its stride after he committed to shipping weekly. 

He told me the growth curve follows the consistency curve almost perfectly. Not the other way around.

But here's the part that really changed how I think about it.

A podcast isn't a podcast. 
It's the engine for everything else.

Dave calls it the Content Flywheel. 
You sit down for one hour. 
You have a real conversation about your industry. 

And that single hour becomes:
1/ 5 LinkedIn posts that actually get engagement. 
2/ A 1,500-word newsletter built around the one nugget that made your guest laugh. 
3/ A serialized series your customers want to follow.

You're not blocking time to "create content." 

You're mining the conversations you already have as a founder, with customers, investors, partners, your team, and turning raw signal into something that compounds.

I think about this a lot at Warmly,. 

It goes like this:
- Every week I'm deep in conversations about how B2B teams find and act on buying signals. 
- Those conversations are full of insights that would take me hours to write from a blank page. 

But in a 30-minute conversation? They just come out.

The other thing Dave said that I can't stop thinking about: as a founder, you are the only person who can do this well. 

You're the crazy person who decided to start the company. 
You're the one having the hard conversations with buyers and churned customers and skeptical investors. 
People want to hear that perspective. 
Even when your voice is raspy and you're running on half a brain. 

(Which, for the record, was me during this recording.)

Consistency IS the strategy. 

Full conversation with Dave here: https://lnkd.in/gQA59vEB

I’m looking to beef up our integrations at Warmly, - what are the best non-obvious CRMs, SEPs & Data Providers out there that we should connect with?

Integrations are the heart & soul of a connected tech stack for GTM and critical to our building of the GTM context graph.

Our favorite & most used integrations today are Outreach, Salesforce, HubSpot , Demandbase , Clay, Apollo, Salesloft, 11x, RB2B , Vector 👻 , Metadata  

Plus coming this quarter we’re adding Microsoft Teams, Gong Engage, Marketo & have room for 7 more!

I’ve been hearing good things about
- Attio 
- Connect The Dots 
- Pipedrive 
- Instantly.ai

Everyone's trying to build their own AI GTM agent right now. Most will quit in a week. Here's why:

It's not because the AI isn't good enough. It is because the infrastructure isn't there.

Here's what happens when you give Claude Code access to your CRM and intent tools and say "go prospect for me":

Wooo millions of signals per day! Dang: That's not fitting in a context window.

Wait why am I seeing the same person 3 times? The agent doesn't know that 3 different records are actually the same person.

Try my website traffic! Shoot Half your "website visitors" are bots. The agent doesn't know that either.

How about using this data vendor we bought? Grrr one data vendor gives you 60% coverage and it goes stale every 3 months.

Let's sync my CRM! Oops, you burn through CRM API calls. You still can't filter out existing deals and customers.

End result: you spent a week and a bunch of tokens to get... a list. Not pipeline. A list.

We spent 2 years building the actual infrastructure so you don't have to endure this.

Our TAM Agent:
- Aggregates all activity and signals to map your TAM
- Does entity and identity resolution
- Creates the full context graph
- Enriches email, LinkedIn, and phone
- Real-time updates
- Doesn't break because you accidentally updated a prompt

The outcomes for us internally:
- 10 paid tools became 2 (Warmly and Claude Code)
- LinkedIn Ad CTR 4x'd. CPC down 50%
- Outbound went from 0.1% conversion to 3-10% depending on the play

Want in?

Two ways in: 

1/ comment "TAM" and I will send you the guide on context graphs. 

2/ Or book on our site, write "Give me that TAM" in the how-did-you-hear field, and we'll build your first dynamic audience for free.

According to Gmail I am a literal heathen. They launched an "improve word choice" feature & essentially every single sentence I write seems to be underlined.

Come at me AI. I'll have a higher cold email reply rate than you 'n ur grammar any day.

Is this happening to others?

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