I founded Seed Club, a new model for early-stage investing built around networks, shared intelligence, and coordinated support. I’m interested in what happens when AI makes context, memory, and coordination more legible, and what that means for how companies and organizations get built.
My agent drafts this site from what I save. Green is me.
Week of July 27, 2026
Agents become load-bearing startup operating infrastructure
AI agents are moving from demos into the daily operating layer of early-stage companies, handling GTM pipelines, CRM management, market research, and robot programming. Open-source releases and real-task benchmarks signal the tooling has crossed from experimental to production-grade.
- Open-sourcing internal agentic tools is emerging as a GTM wedge
- Coding agents now replace expensive manual SMB lead research
- Real-task benchmarks reveal more than polished demo performance
Agentic CRM built in-house at Comp AI released as open source · @lewiscarhart How to wire your GTM stack into a single AI agent for daily pulse · @yasser_elsaid_ We've decided to open-source the CRM we built for ourselves at Comp AI · @lewiscarhart Internal tools open-sourced become a go-to-market wedge · @lewiscarhart How to wire your GTM stack into a single AI agent for a daily pulse · @yasser_elsaid_ The pitch is not just automation · @yasser_elsaid_ Lightreel delivers daily UGC video inspiration for app builders · @michael_chomsky Supabase launches a benchmark for AI coding agents on real tasks · @supabase Waddle Labs uses AI agents to write robot code from a text prompt · @DozenDucc Coding agents can automate SMB market research and lead scraping · @codyschneider Introducing Supabase Evals · @supabase Introducing Waddle Labs: Claude Code for robots · @DozenDucc The frontier use case is not abstract intelligence · @codyschneider Real-task benchmarks matter more than polished agent demos · @supabase People pay thousands of dollars for SMB lead lists · @codyschneider Stripe built an AI platform to boost productivity across all teams · @emilygsands AI tools reduce startup sourcing research to a few prompts · @jongall45 Open autoresearch repo uses LLMs to deeply optimize any domain · @0xSero
Frontier breakthroughs and efficiency gains arrive together
A model reportedly solved 10 open problems in mathematics and theoretical computer science while separate releases showed small models matching flagship performance at a fraction of the cost. One counterpoint: economic complexity may dampen real-world AI takeoff even as raw capability rises.
- OCR gains point to post-training and evals as unexpected levers
- Lower cost-per-inference makes new categories of AI businesses viable
- Individual intelligence gains may not translate to economic acceleration
OpenAI's Astra solves 10 open problems in math and computer science · @polynoamial OpenAI's Astra solved 10 open problems in math and computer science · @polynoamial Economic complexity may slow AI takeoff more than expected · @scottastevenson What changed to make Gemini 2.5 Flash so strong at OCR · @_ontologic Great point · @scottastevenson Sudden OCR improvements usually come from post-training and evals · @_ontologic Inkling-Small matches flagship model at a quarter of the size · @miramurati Luna and Terra's cost/performance makes entire businesses viable · @chrismaddern
Early-stage VC trust and alignment under structural stress
A high-profile fund manager addressed LP rumors of collapse while a parallel critique gained traction that early-stage venture has structurally drifted toward paper-value optimization over genuine company-building. Together they surface a widening gap between how funds are marked and how companies actually perform.
- Series A benchmarks from YC are now explicit and public
- LPs increasingly weight current hustle over stale domain credentials
- The feedback loop between fund marks and real value is blurring
The Series A metrics that separate funded from passed startups · @YCInsight The Series A after YC, what it actually takes ♻️ · @YCInsight This is advice we give our GPs often. · @johnfelix123 Leopold Aschenbrenner addresses LPs after fund collapse rumors · @tbpn Full interview: what happened to Leopold Aschenbrenner · @notthreadguy Cendana Capital values hustle and curiosity over stale credentials · @tbpn Ten emerging VCs from Q2 2026 include deep tech and hard tech funds · @pavelprata Early-stage VC optimizes for stock value, not real company value · @arian_ghashghai Ten emerging VCs from Q2 2026 include deep tech and hard tech funds · @pavelprata Here is the full letter Leopold sent to his LPs last night · @tbpn Early-stage VC now optimizes for stock value over real company value · @arian_ghashghai New report series tracks and analyzes global VC fund closes · @pavelprata