Deep Work Plan

Models matter. Context matters more. Give your agent a plan.

161 followers

Models matter. Context matters more. Give your agent a plan.

161 followers

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Deep Work Plan is spec-driven development where the repository itself becomes the harness: a durable plan, atomic tasks, acceptance criteria, and validation gates written into your repo — so coding agents run long-horizon work for hours without drift. Done is a contract, not a vibe: runs survive context resets, any agent resumes where the last left off. Works with any coding agent like Claude Code, Cursor, or Codex: you plan, agents execute with precision. Any repo, no lock-in. Open Source, MIT.

This is the 2nd launch from Deep Work Plan. View more

Deep Work Plan

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Models matter. Context matters more. Give your agent a plan.

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Launch tags:Open Source•Developer Tools•Artificial Intelligence

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Viktor.comAn AI coworker that actually does the work

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Deep Work Plan

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Hi Product Hunt 👋 The promise of coding agents was delegation. What most of us got was a second job: supervising. Check in every twenty minutes, re-explain the goal after every reset, catch the moment it starts solving something adjacent to what you asked. However long the run, you were in the loop — none of it was unattended. Turns out autonomy isn't a model setting. It's a structure. Models matter. Context matters more. That's Deep Work Plan. Two moves: 1) Make the plan the source of truth, not the chat. A goal, atomic tasks, per-task acceptance criteria and a validation gate. The agent re-reads the plan at every step instead of remembering it, and done is decided by the gate, not by how the model feels. You steer once; the structure holds. 2) Make the repository the harness. Context, tools, guardrails and state as plain files any agent reads. Claude Code, Cursor, Codex, Copilot, Gemini, or next year's agent runs the same plan, no vendor to bet on. And here's what a structured plan actually buys you: speed you can trust. Every task has to prove itself at a gate before the next one starts, so drift stops being something you catch and becomes something the run catches. Changing course stays cheap: atomic tasks and on-disk state mean you edit what hasn't run, keep what has, resume from exactly there. The agent never waits for you to re-explain the goal, and you never face six hours of mystery diff. Progress shows up as small, provable steps. The structure isn't overhead on the execution. It's what makes the speed safe. It's MIT, open source. If you want to try it, paste deepworkplan.com/init.md content into your agent — that's the whole setup. If you're still supervising more than delegating, I'd genuinely love your take. How much unattended runtime are you getting from your agents today?

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Previous Deep Work Plan Launches

Deep Work PlanModels matter. Context matters more. Give your agent a plan.

Launched on June 17th, 2026