https://sergei.pro/en - instead of many words. They say B2B = boring2boring. I believe it’s wrong. I proved that B2B brand marketing can be as entertaining as a Nike ad.

I am a strategy leader with a focus on change. As a B2B Brand Marketing executive with over 15 years of experience leading global projects, I execute brand identity campaigns and promote product growth. I am a storyteller who aims to create bold work that strikes a chord with people and turns tech products into popular brands. I’m always driven by creativity but firmly rooted in strategy.

I have a unique experience working with hypergrowth companies, taking them to the next level and promoting tech products globally. I am especially strong in communicating complex, cutting-edge technologies (such as fintech and AI) to wider audiences using simple human insights.

Vast international experience: USA, Western Europe (UK, the Netherlands), Asia (China, Singapore).

My top collaborations:
•	Transformed brand identities for over 30 products across 15 categories in collaboration with top global communication giants, such as McCann, Leo Burnett, and Grey Group.
•	Synthesized marketing strategies for Mastercard, Microsoft, and Samsung.
•	Relaunched the Unlimint brand, introducing an innovative identity while executing the brand’s first global awareness campaign across eight markets (APAC, EMEA, LATAM, North America).
•	Launched Roundtrip, an online booking tool for business travel, including brand positioning, identity development, and video content creation.

Core skills:
•	Strategic thinking, ability to plan and execute marketing vision
•	Huge experience in the development of marketing campaigns from scratch/orchestrating brand launches
•	Strong experience managing company budgets and relationships with multiple suppliers (external creative agencies, production companies, etc.)
•	Experience in building in-house creative and production teams 
•	Proven ability to develop a creative and collaborative culture
•	Demonstrated success in a matrix organization by building and leveraging relationships across the company
•	The ability to attract, inspire, and nourish diverse talent
•	A strong storyteller and creative thinker
•	Highly skilled in consumer research, audience identification, segmentation studies, insights generation

More about me and my projects: https://sergei.pro/en

In my everyday life, outside of my professional career, I'm an avid movie enthusiast, a dedicated follower of MUBI and Netflix.

Sergey Denisov

🌊 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

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Alan Zhao (Click-Through King) 👑

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