How to build a portable memory for AI agents
Once models are cheap and interchangeable, the valuable part of an AI setup is your context. A one-minute explainer on keeping that memory in files you control, outside any one vendor.
Writing
Essays on agentic commerce, AI systems and running an AI-native company.
AI cost per task: why AI feels pricier as it gets cheaper
Frontier AI runs cost more every year, but at fixed quality AI cost per task is falling about 13x a year. Why both are true, and the rate I'd plan agents on.
Zuckerberg being the savior of humanity wasn’t on my bingo card for 2026
Zuckerberg's AI glasses vision, the UN's AI standards debate, and who gets to decide the future of AI.
I got bitter lessoned
Sol-6 and Opus 5.5 broke my dev process. I'm ripping out the heavy software factory I spent three months perfecting and going agile: continuous testing on staging, frontier models at higher reasoning, and no more independent judges.
The constraints are human now
AI capability is no longer the scarce input. What's actually holding back adoption: organizational buy-in, trusted context, action authority, energy, permission to build, and economic controls.
Agents are making a second computer surprisingly useful
Why I use Linux machines alongside my main computer: overnight work, more memory, separate access and remote connections through Tailscale.
AI makes mistakes, it's stochastic, here's how I manage those
AI is fundamentally probabilistic and will make mistakes. Seven ways I manage that, from human review to fresh-context judges to shrinking the blast radius of any single error.
Here's my current AI stack
Here's my current AI stack: open source, a dedicated memory system, multi-agent access, spec judges, evals, and as much of the process in code as possible.
Git-owned knowledge base: markdown in git is not a hack
A git-owned knowledge base is markdown in a repo you control. A YC launch listed that as a hack. You want a record you can diff, refuse, and take with you.
33 workflows, five layers — what a real harness looks like from the inside
The piece I wrote on harnesses described five component layers that every production agentic system needs: orchestration and planning, an execution environment, validation and quality control, context and memory management, and logic and interaction.
Launching Shop CLI
Shop CLI: A Tool Built for AI Agents, Not Humans
How AI Agents Reshape Business Relationships
Not all business relationships do the same job. Research shows which ones survive the agentic economy, and which were always just expensive due diligence.