Plan work in a PRD, then assign the build
A developer asks a stronger model for a plan, turns it into tasks, and routes implementation to lower-cost agents.
- What they did
- They described a homegrown setup built around enforced TDD, multi-agent runs with git trees, persistent memory, and house-style hooks. Their usual flow is to have a top-tier agent draft a PRD, convert that document into a checklist of work, and then pass the coding to cheaper agents. They also said they are putting together a Python orchestrator that can invoke Haiku and other models through the API.
- How it went
- They did not report any concrete performance figures or business impact. The workflow is still under construction, with the orchestration layer not yet complete.
- Tips
- This style of handoff works best when your tooling can keep tasks narrow and track state across agents. Make sure the plan is approved before any implementation begins.
Try it yourself with Claude Code
Help me organize a build for [feature name] inside [codebase or folder]. Create a brief PRD that states the goal, boundaries, and what counts as done. Next, turn that PRD into a set of small, separate tasks with explicit completion checks, and place them in [file name]. Stop there and show me both documents for review before any code is written, changed, deleted, or submitted. Once I approve, proceed by assigning the implementation work to the lowest-cost model that can handle each task.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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