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 June 8, 2026
Intent-centric OS and data firewalls reshape platform power
Apple's announced shift toward intent-centric interfaces that construct UI on demand threatens the app ecosystem model. Platforms blocking LLM data access are spawning decentralized crawling marketplaces as a countermeasure.
- On-demand interface generation could eliminate third-party apps entirely
- Permissionless data markets emerge wherever platforms erect LLM firewalls
AI agent costs exploded, forcing outcome-based pricing models
The shift from chat to agents drove costs far beyond early estimates, as recursive agent spawning multiplied token consumption. Firms that price for outcomes over token volume can capture labor-scale revenue, but only by treating every token and hour as margin.
- Token spend at scale blurs the line between software and services
- Open question: which firms can actually measure outcome quality reliably
Real autonomy is finding work, not executing tasks
The defining feature of a truly autonomous loop is not task execution but the ability to propose work without a human prompt. Self-improving systems that search proactively over potential improvements against stated objectives represent the next capability threshold.
- Proactive explorer agents differ fundamentally from reactive task agents
- Self-improvement applies at the organizational level, not just software
Individual AI assistants give way to team orchestration
The market needs an orchestration layer spanning an entire team's workflow, combining work management, agent assignment, and shared context. Codified, programmable workflows are replacing knowledge-based skills as the reliable unit of agent execution.
- Shared MCP servers and context compound value across teams
- Codified workflows require less model intelligence, enabling more reliable execution