Senior B2B demand generation & growth marketer with 6+ years’ experience building demand engines that drive pipeline for enterprise and mid-market tech. Expert in building full-funnel strategies across paid, ABM, and content. Highly commercial and sales-aligned; focused on optimizing the MQL to SQL conversion bridge through experimentation and buyer-centric messaging.

Callum Moates

Yurii Filipchuk 🇺🇦 -- e/acc

Founder @ Stealth AI |TechStars AI Startup Weekend SF

I build Principle, a simulation engine that stress-tests business decisions before you commit capital.

I also run partnerships and sponsorships at Techstars Startup Weekend SF and Catalyst Bay. We're a community of 10,000 founders doing IRL events in San Francisco.

Chaotic Good is my operating system. Move fast, challenge conventional thinking, put powerful tools in more hands. I believe that's how you actually make the world better. Big believer in pay-it-forward culture. If you have an idea on how we can help you or you want to help us, reach out.

The LLMs you choose say something about you. I'm team Claude for work. NotebookLM and Gemini for research. ChatGPT and Groq for personal life questions.

Previously CEO of Party.Space. Spotify was my first client, then Google, Zapier, Grammarly, UC Berkeley. Raised $2M from top European VCs.

I advise early-stage founders on fundraising and GTM. Been on both sides of the table. Invested through CYFRD: 15 deals, 2 exits.

San Francisco. Born in Kyiv.

Community Lead: Vibes & Sponsorships | Pitching Mentor

At Techstars Startup Weekend SF AI, we're hosting a fast-paced, 3-day event where tech enthusiasts come together to bring AI startup ideas to life. My role is to create an energetic and welcoming atmosphere, build connections with important sponsors, and guide participants in making their pitches clear and impactful.

Google DeepMind just ran their first Startup Session.

Got the invite from Matt Ridenour - thanks for putting this together and MCing the whole thing.

Direct access to the teams building the models. That's rare.

What they showed:

1/ Austin Sendek on materials science - his team's GNoME project discovered 2.2 million new crystal structures. That's roughly 800 years of materials knowledge generated by AI. Wild number.

2/ Genie 3 - a generative world model trained on internet videos. You describe an environment, it builds a playable 3D world in real time at 720p. Already shipping as Project Genie for AI Ultra subscribers.

3/ Anshul Ramachandran on Antigravity - DeepMind's agent-first IDE. An AI Editor, Agent Manager and Agent-Controlled Browser working together. Task-level coding, not line-by-line.

4/ Nano Banana - their image generation model that pulled 10M+ new Gemini users and 200M+ edits in the first weeks. Now powering the whole Genie world-building pipeline.

And Paige Bailey generated Hindu electro pop live on stage with Lyria. Totally awesome!

Great seeing old friends like Naji Barnes-McFarlane!

Google've been always supporting startups. Good to see them opening the lab doors.

Yurii Filipchuk

AI Simulation Platform for Business Decisions | Chaotic Good 🇺🇦

The state of GenAI video no longer surprises me🤖

So we started making our own. Episode 1 of "LockedIn" is out. Who else gets frustrated receiving AWS/GCP bills?

Where should we channel the creative energy next -- something more satirical or slightly educational?

P.S. Those worms are adorable and they deserve their own show. Someone talk us out of it.

literally me when I missed a day of OpenClaw madness

Founder @ Principle | Strategic Foresight Engine | Chaotic Good

We act like AI showed up yesterday.

1951 - Christopher Strachey wrote a checkers program on the Ferranti Mark 1. A room-sized machine playing board games. That was the first AI.

1966 - MIT built ELIZA. A chatbot pretending to be a psychotherapist. People got emotionally attached to it. 58 years before ChatGPT.

1972 - MYCIN diagnosed blood infections better than most doctors. An AI system. In the seventies.

By the 1980s, companies were spending millions on expert systems that mimicked specialist knowledge. Then the hype died. Funding dried up. They called it the "AI winter."

We've been through this cycle before.

When was the first time you used a product and thought "wait, is this AI?"

early ai cases 

Everyone says legacy tech companies can't reinvent themselves. IBM didn't reinvent itself – it executed self-destruction while it still had the cash to survive it.

IBM's market value has tripled since Arvind Krishna became CEO in 2020. Wall Street called it a turnaround.

Wrong.

This was controlled demolition followed by industrial-scale reconstruction.

What's actually happening?

Most legacy CEOs manage decline gracefully. Krishna did the opposite. During the pandemic, while competitors froze, IBM borrowed massive cash, spun out a third of its revenue and staff, launched aggressive M&A, and added $3B annually to R&D.

The common narrative: "IBM is cutting costs to survive."

Actual reality: IBM was reallocating capital from legacy cash cows to future growth engines while volatility provided cover.

This is the volatility catalyst.

Krishna understood what others missed: Volatility doesn't slow tech adoption – it accelerates it. When capital gets expensive, technology stops being "nice to have" and becomes survival-critical.

Most CEOs spread painful changes across years. Krishna bunched them together during maximum chaos.

Two paths for legacy companies:

Path A (Traditional): Cut 5% staff per year for 6 years. Slow bleeding. Culture dies. Arrive weak.

Path B (Krishna): Cut 33% in one volatile year. Market expects chaos anyway. Use cover to add $3B to R&D. Arrive lean and funded.

Path B has 4x higher survival probability.

IBM deployed Gen AI to 8,000 of their 40,000 developers. Result: 45% productivity increase.

The lazy analysis: "They'll cut 4,000 jobs."

What actually happened: They served markets that were previously too expensive to address. AI doesn't shrink companies – it expands what they can profitably do.

Most legacy CEOs ask: "How do I protect what we have?"

Krishna asked: "How do I disrupt ourselves before someone else does – while we still have the cash flow to survive it?"

Legacy companies don't die from lack of innovation. 

They die from innovating too slowly while managing decline.

What's your excuse for not moving forward?

Dropping a new episode of LockedIn. Inspired by a real story this time!

Hamudi Naanaa and Volodymyr Panchenko hit Anthropic's Tier 4 token limit mid-hypergrowth. 4 users to 1,400 in 3 days. 2b tokens a day! 

Their words: "A two-day response cycle doesn't match the speed we're operating at -- for us, it's 1–2 hours."

They switched to Gemini overnight. A constraint forced it.

What's the ceiling your team hasn't hit yet -- but will?

taplio

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