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  1. In the previous post I toured Herdr and how I lay it out: one space per folder, one tab per kind of work, agents in tall columns, shells in short stacks, all of it spread across a 5120×1440 ultrawide.

  2. One coding agent is a tool.

  3. Notes Repos as Shared Project Context

    The first thing most people put in a new repository is code.

  4. There is a version of a feature toggle that looks wonderfully simple in a pull request: if (features.newThing) { doNewThing(); } Then newThing turns out to be a data pipeline, a shipping promise, or a screen people have already started using.

  5. Agent-Ready Local Environments and MCP

    Getting a coding agent productive is less about the prompt and more about whether the machine in front of it can actually build, run, and reach the systems the work depends on.

  6. Recently I was digging around in the terminal and wanted an ls command that behaved like a fully opened tree view.

  7. There’s a particular kind of magic in watching a whole city move at once.

  8. The scariest thing about a genuinely capable coding agent is how quickly it commits.

  9. Run two coding agents against a single working tree and they will fight.

  10. Part 8 of 8: Durable AI for InterlinedList Back in Part 1, I said the whole series was one argument dressed up as eight posts.

  11. Part 7 of 8: Durable AI for InterlinedList Six posts in, and I’ve been dancing around a number.

  12. Part 6 of 8: Durable AI for InterlinedList Every serverless AI feature I’ve built hits the same wall the second someone wants it at scale.

  13. Part 5 of 8: Durable AI for InterlinedList I have a problem, and I bet you have it too.

  14. Part 4 of 8: Durable AI for InterlinedList Most of this series is me thinking out loud about features that don’t exist yet.

  15. Part 3 of 8: Durable AI for InterlinedList In Part 2 I talked myself into a durable worker sitting next to Vercel, reusing the lib/ code the app already trusts.

  16. Part 2 of 8: Durable AI for InterlinedList In Part 1 I talked myself into Temporal as the orchestration layer for the AI features I want to build.