Notes on AI agents and MCP
Short, plain notes about building AI agents and MCP servers that work in real businesses: what works, what breaks, and why.
June 13, 2026
Write it down for the machine
There's now a plain text file every serious coding agent reads before it touches your repo: AGENTS.md. As of early 2026 it's read natively by Claude Code, OpenAI's Codex CLI, Cursor, Aider, Devin, GitHub Copilot, Gemini CLI, Windsurf, and Amazon Q — the closest thing the industry has to a universal instruction format for agents. It's the highest-leverage hour you can spend on AI coding right now, and almost nobody does it. Here's what goes in it and why it works.
- methodology
- ai-native
June 12, 2026
Give your coding agent the error, then get out of the way
The biggest difference between a coding agent that's useful and one that's maddening usually isn't the model. It's whether you closed the loop. An agent that writes code and stops is guessing. An agent that runs the code, reads the actual error, and tries again until the tests pass is in a different league — fix rates jump past 90% in a couple of iterations. The agent can only fix what it can see, so the highest-leverage thing you can do is give it eyes. Here's exactly how.
- methodology
- agents
June 10, 2026
Why your agent's pull request gets rejected
Researchers studied 33,000 pull requests written by AI coding agents, and about 29% never got merged. The interesting part is why: not mostly because the code was wrong, but because the PR was a bad collaboration artifact — too big, touching too many files, bundling unrelated changes, failing CI, and explaining itself poorly. Getting code accepted turns out to be a different skill than writing it, and it's exactly the skill agents don't have by default. Here's what that means for using them.
- methodology
- agents
June 10, 2026
Your AI provider is going to have a bad day
Two reminders landed this week. Anthropic is retiring Claude Sonnet 4 and Opus 4 from the API on June 15 — if you pinned those versions, your calls just start returning errors, with no automatic failover. And this morning, Gemini went down. Same lesson from opposite directions: the model under your product is a third-party service that will, on a schedule you don't control, change, vanish, or break. The fix isn't strategy. It's the boring resilience engineering most AI products skip.
- architecture
- methodology
June 9, 2026
Anthropic writes 80% of its code with AI. You're not Anthropic.
More than 80% of the code Anthropic merged to production in May was written by Claude. That number is about to be quoted in every 'developers are obsolete' argument and every pressure-to-keep-up meeting. So read it carefully, because it argues the opposite of what people think. It's the company with the best model, using that model on itself, reviewed by some of the best engineers alive. The percentage isn't the lesson. The thing that made 80% safe to ship is.
- methodology
- careers
June 9, 2026
You're about to manage a workforce of agents
A platform launched this month that lets companies recruit, onboard, manage, and even pay AI agents — across every major model — under one passport and one audit trail. Its tagline is 'your next hire isn't human.' Strip the marketing and there's a real shift underneath: the job is moving from using an AI tool to managing a team of them. That's a different skill than prompting, most people aren't ready for it, and the mental model you reach for decides whether it works.
- agents
- methodology