ralph-loop

You can automate a full-cycle development loop by executing a continuous Research, Plan, Implement (RPI) workflow that handles state management and self-correction until the task is complete without intermediate user prompts.

An autonomous RPI workflow executes research, planning, and implementation sequentially while maintaining progress in a `.rpi/.ralph-state.md` file, dynamically invoking sub-skills based on file system state to self-correct and iterate until completion.

Yes, you can build a new software feature autonomously by running a continuous RPI iteration loop that manages everything from initial research and spec creation to final implementation and testing without user intervention between steps.

To keep an AI agent working without intermediate prompts, use an autonomous iteration loop that manages task state and dynamically handles discovered work by iterating based on previous outputs and file system state.

Yes, the autonomous development loop supports self-correction by iterating based on previous outputs and file system state, allowing the AI to dynamically invoke sub-skills and handle discovered work autonomously until the task is fully completed.

You need an agentic workflow for complex software engineering tasks that require self-sufficient execution, ensuring continuous research, planning, and implementation iteration until a defined task is fully completed without intermediate user intervention.