ClaudeRPID is a project template I built to fix the failure mode that makes AI coding agents frustrating: they write fast, but they forget. The whole template is organized around a single premise — lost context and outdated context are the only real enemies — and every rule in it is aimed at preventing one of those two.
The method
The workflow is a four-track cycle, RPID: Research → Plan → Implement → Debug. Each phase has to finish before the next begins, so design decisions are made and written down before a line of code exists, not reverse-engineered afterward. It turns the agent from something that sprints toward a guess into something that commits to a plan and then executes it.
Living documentation
The backbone is a set of documents that travel with the project and stay current — STATUS, DECISIONS, ARCHITECTURE, DATA_MODEL, and PLANNING. They’re not write-once artifacts; they’re the agent’s memory between sessions. When a new session starts cold, the context it needs is already on disk instead of lost to the previous conversation.
- A prompt library with a tailored prompt for each RPID phase.
- A GitHub Actions test gate so nothing merges without passing CI.
- Solo and team collaboration modes from the same structure.
- Opt-in profiles for language- and framework-specific tooling, so the core stays stack-agnostic.
What I learned
The interesting part isn’t the prompts — it’s that most of an agent’s mistakes are really context mistakes. Give it a structure that forces decisions to be recorded and kept fresh, and a lot of the “AI did something dumb” problems quietly disappear. The discipline lives in the scaffolding, not the model.