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

I analyze your outbound data before telling you what’s broken | CEO, B2B Catalyst

I've spent 8 years building outbound systems for B2B companies. Teams of just the founder to 50 SDRs.

Over the years I realized success isn't nearly as random as it looks. 

There's a specific hierarchy of constraints, and if you don't solve them in the right order, your outbound fails.

The problem is that methodology usually takes months of manual consulting work.

Recently I compressed it with AI.

I fed 21 sales call transcripts, 585 cold call records, every script, deck, and playbook a company had into the system.

It found a two-layer messaging problem nobody had diagnosed.

Wrong product frame combined with wrong awareness level. 

That alone explained why cold calls weren't converting.

They had 6 script iterations that accumulated over months of gut-feel revision. None of them were working. 

The system identified which proof points were actually landing on calls, and zeroed in on a new approach built from their own data.

It took an evening.

I'm publishing the full methodology next week, prompt templates, benchmarks included. Free.

But first, I want to run it for 3 more companies. For free.

What I need: your last 30 days of email sends and replies, cold call recordings, and discovery calls. That's it. 15-20 minutes of exports.

Signal enrichments on your companies and contacts are nice to have, but not needed.

What you get back: a constraint map, messaging diagnostic, rep coaching briefs, and talk tracks revision suggestions. In days.

DM me "sprint" if you want in. I'm taking 3.

🌊 Alan Zhao

🎆 Brand Marketing | 📈 Organic Growth Marketing | 📺 Building a media empire on a shoestring budget | DM me if you want to be on our podcast 🎙

We're building the GTM Brain: a stateful, self-learning decision system that observes buyer behavior, builds a world model of the market, and decides what to do in real time.

I left Warmly briefly to work as an SDR. Cold calls, rejections, the grind. What I saw: reps drowning in data, starving for judgment.

The problem was never execution. AI made execution infinite. You can send unlimited emails, generate infinite personalized copy, index entire markets in hours.

It was decision quality.

Pipeline got harder to build, not easier.

The GTM Brain is a self-learning decision system that captures decision traces so every win becomes a playbook and every loss becomes a lesson.

Outside of tech, I’m a bachata instructor and host bachata events in San Francisco. It's something I'm extremely passionate about. 

Most people think they can’t dance — solo or with a partner — but it’s one of life’s hidden gems to be able to express ourselves through movement while building a connection with a dance partner, socially.

I think social dancing is becoming a real movement, and I want to help lead it — and spread it positively.

Follow my dance journey: https://www.instagram.com/alan_j_zhao/

Follow my SF bachata classes & socials: https://www.instagram.com/sensual_soiree_sf/

Co-Founder, CRO

Alan Zhao (Click-Through King) 👑

I've been automating our own GTM at Warmly with with Warmly + Claude Code Agent SDK and here's what you need to do:

1. Integrate all your systems. For us it's HubSpot (CRM activity stream), Slack (internal discussions on deals), Sybill (call recording), BuiltWith (technographics), Warmly, (signals, chat conversations, enrichment/web research). Outreach for sequencing. APIs or bust for vendors

2. Use Warmly's TAM Agent to find the short list of high intent ICP companies and perfect buying committee contacts (no interns, just buyers). 500 accounts, 1500 contacts. Pull into Claude Code.

3. Use Claude Code to build territory mapping for AEs and SDRs. 15 per AE, 100+ per SDR. Map email inboxes. Just prompt this and save as an .md file the territory mapping. Then map this to Hubspot via the integration 

4. Use Claude Code to query my systems in step 1 and build the full timeline on each of the accounts. "Closed lost, who visited the website, when did we engage last, what pages are they looking for, what was discussed on last demo call"

4. Use Octave API to write the perfect email outreach with full context from Step 3. Send this automatically to Outreach with tags and using custom fields for subject and email body.

5. Automatically sync the contacts directly to LinkedIn Ads. 

Results: 
- Ads: 50% reduction in CPC, 3x improvement in CTR for the exact same ad creative after a week of running.
- Emails: Will let you know next week. Aleksandar Lepidovski running it right now!

Okay here's the problems you run into:

1. You are going to iterate a lot with prompting Claude Code and context degrades quickly when you use MCPs. Claude code does its best to auto-compact but I've noticed that once it gets to 85% context window the memory degradation is already severe.

2. It takes a long time to pull the full context on the accounts once you get a short list of accounts to do deep research on. And by the time the context pulls you realize you missed something or claude didn't pull it right... so you burn through tokens (good thing claude code tokens are cheap for now)

3. Agents are stateless, which means once you close the session it loses all the context, so you need a way to build memory into the system if you want to run this job again. You'll use .MD guideline files for now and you try your best to use claude.md files to stitch together where to look, but you have no idea if the AI is reading in the right context and guideline files before it runs the job. So you pray. 

4. You have no idea how to encode this into your existing human and workflow systems and how to scale it. Human systems are more deterministic (gets the job done) but do not compound alongside foundational model improvements. 

5. You realize that shit data in means shit outputs and that's a whole can of worms that has nothing to do with LLMs. You don't want to manage this system even though it's the foundation.

You start looking for Agent Harnesses for GTM (check the comments)

Alan Zhao

Cofounder, Head of Product, Marketing, & AI @ Warmly.ai | Building the GTM Brain | #1 Context Graphs for GTM Agents & Humans

Software might be on its last legs. Microsoft down 11% in a day. Salesforce down 20% from the start of the year.

But there's one play left: infrastructure for agents, not humans.

We just published Part 1 of a 3-part series on AI infrastructure for GTM:
- Context Graphs (the data foundation)
- Agent Harnesses (the coordination layer)
- Long Horizon Agents (what emerges when you have both)

Here's what most GTM companies are missing..

Rich Sutton's "Bitter Lesson" from 2019 proved that general methods leveraging computation consistently outperform handcrafted human knowledge.

Deep Blue needed grandmasters and opening databases.
AlphaZero learned chess from scratch and crushed it.

The same pattern is playing out in GTM right now.

Most "AI tools" today are just human-designed workflows with AI sprinkled in.

You're shifting complexity away from the part that scales (the model) into the part that doesn't (bespoke scaffolding).

The test to see if you're building true AI-native solutions and not drag and drop that will be scaled out:

If model capability doubles next year, does your system get dramatically simpler without major refactors?

If no, you built human understanding into the harness. 

Context graphs are the foundation that makes the second path possible.

Not workflows. Not fixed subagent hierarchies.

A world model lets agents dynamically spawn subagents, retain the right context, and decide how to solve problems. Humans in the loop will confirm and guide but not dictate.

The companies building agent infrastructure now will compound.
The ones encoding their assumptions into scaffolding will plateau.

Full guide on GTM context graphs in the comments!

Part 2 and 3 will be released soon

taplio

The Battle

Scott Martinis

Alan Zhao (Click-Through King) 👑

Followers

Posts

Engagements

Likes

Performance ScoreScott Martinis's LinkedIn Performance

Performance ScoreAlan Zhao (Click-Through King) 👑's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Scott Martinis

Alan Zhao (Click-Through King) 👑

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Scott Martinis's LinkedIn Performance

Performance ScoreAlan Zhao (Click-Through King) 👑's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreScott Martinis's LinkedIn Performance