ralph

Autonomous feature implementation is achieved by defining requirements in a prd.json file and running an autonomous loop script that generates and executes user stories iteratively. The system commits changes to git after each successful iteration.

An autonomous AI agent maintains context by persisting memory through version control, a progress.txt log, and the prd.json file. This ensures continuity across iterations by recording learnings and committing incremental changes after each cycle.

Yes, git is required to run autonomous feature development loops because the system uses version control to commit changes and record progress after each successful iteration. Git provides the memory persistence required for continuity across cycles.

The best way to ship end-to-end features autonomously is using a loop script that reads a prd.json, plans user stories, and implements them sequentially. It tracks progress via logs and version control to ensure incremental delivery.

Yes, an AI agent can plan and execute user stories sequentially by running an autonomous loop. The agent reads requirements from a prd.json, implements stories in order, and commits the changes after each iteration.

An autonomous loop for feature development should not be used if your project lacks a prd.json structure or git for version control. The system relies on these to track progress and persist memory across iterative cycles.