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Articole: 16

  1. Spaces, Tabs, Panes, and Precise Words: Why I Break Agent Work Out the Way I Do

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    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. Herding Agents: How I Actually Use Herdr (on a Ridiculously Wide Screen)

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    One coding agent is a tool.

  3. Notes Repos as Shared Project Context

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

  4. Toggle Switches When the Thing Behind the Switch Is a Whole System

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    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

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    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. Twenty-ish Terminal Commands for Getting Around the File System

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

  7. Dashing Arrivals: Watch Every Bus, Train, and Ferry in Puget Sound Move in Real Time

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

  8. Ask, Plan, Confirm: Making Agents Stop Before They Start

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

  9. Giving Every Agent Its Own Branch: Git Worktrees for Parallel AI Work

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

  10. A Research Agent on a Budget Leash, and How I’d Sequence the Whole Build

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    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. Making LLM Features Cheap Enough to Actually Ship

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

  12. Tag Everything, Expand Anything, Without Re-Billing the Model

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    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. Where Did I Save That Article? Crawl, Cache, Retrieve

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

  14. The Cron That Double-Posts and the Calendar I Actually Want

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    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. A Generate Button That Survives a Timeout and Asks Before It Writes

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    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. Where Does Temporal Even Run When You’re All-In on Vercel?

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    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.