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.
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Week of June 22, 2026
AI economic value migrates below the model layer
The competitive question has shifted from model capability to where margin actually concentrates. Workflow orchestration, enterprise flywheels, and edge distribution are all contending as the real prize, while model providers face commoditization pressure from multiple directions.
- Embedded workflow lock-in may outlast any model-level advantage
- Enterprise flywheels capturing tacit knowledge could prove more durable than model leads
- Edge providers capturing economic value have strong incentive to keep it private
Applied AI value may accrue to workflow orchestration layers · @i_zerbib Applied AI value may accrue to workflow orchestration layers · @levie Enterprise AI moats may come from embedded workflow lock in · @alexolegimas Enterprise AI shifts toward proprietary model flywheels · @AravSrinivas AI stack specialization could mirror cloud's giant winners · @masonnystrom Frontier AI labs face pricing pressure at the edge · @hypersoren Enterprise AI may spread faster through chat than seat licenses · @_simonsmith AI startup moats are diverging across labs data and distribution · @aashaysanghvi_
Frontier model access shifts to government approval gates
Government approval gates emerged for GPT-5.6 access on security grounds, as a massive distillation attack on Claude attributed to Alibaba confirmed that capability extraction is a live threat. Federal AI policy simultaneously hardened toward restricting Chinese frontier model access globally.
- Gated rollout creates a two-tier market of approved and non-approved users
- Distillation attacks may become the primary vector for capability transfer between rivals
- Regulatory trajectory mirrors the protocol-level battles crypto already fought
Security restrictions could shut Chinese frontier models out globally. · @teortaxesTex Federal AI policy shifts toward tighter and murkier control · @deanwball OpenAI unveils GPT-5.6 lineup with three model tiers · @OpenAI AI labs face the same regulatory battles crypto already fought · @ccatalini U.S. moves to approve GPT-5.6 access customer by customer · @ns123abc OpenAI asked to stagger GPT-5.6 launch over security fears · @steph_palazzolo Anthropic says Claude faced a massive model distillation attack · @MTSlive
Agents split enterprise AI into two distinct problems
Building with agents divides into two fundamentally different challenges: restructuring internal operations versus rebuilding products as agents, and conflating the two is a key failure mode. Internally, agent adoption is already visibly compressing white-collar roles and dissolving traditional team structures at leading firms.
- Role boundaries between engineering, product, and design are dissolving
- Sharing successful agentic workflows across a team remains unsolved
- Executives treating AI as a compliance checkbox are misreading the transition
Agent adoption splits between internal operations and products · @ankrgyl AI teams may reorganize around product lifecycle archetypes · @bcherny Executives warned AI will remake companies, not tick a box · @Steve_Yegge Teams still lack good ways to share agent workflows · @dwr Teams still lack good ways to share agent workflows · @dwr Agentic workflows could compress white collar labor demand · @_The_Prophet__ Meta product teams replace process with internal AI agents · @nikhyl
Moats thin as mega fund capital distorts every stage
Conventional defensibility is weakening to where founder reputation has become the primary moat signal, with teams outweighing decks in early-stage evaluation. Mega fund over-capitalization is simultaneously lowering bars across all stages, inflating rounds throughout the funding stack rather than specifically targeting seed.
- Sitting out a bubble may carry more career risk than joining it
- Seed fund strategy is shifting toward diversification and option value
- A large liquidity wave may be approaching across major private companies
AI startup moats may come from multiplayer systems, not models alone · @illscience Startup moats weaken as investors fixate on teams · @zamdoteth Seed funds shift toward broad portfolios and option value · @masonnystrom Venture firms brace for a new wave of startup liquidity · @Samirkaji New research examines how active mega funds are in seed · @pavelprata Venture incentives can reward joining bubbles over sitting out · @TurnerNovak Mega funds may be inflating startup rounds across every stage · @gdibner Venture capital may split between swarms and permanent capital · @joeljohn