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Automating feature implementation involves breaking down features into user stories and executing them in a controlled, iterative loop. This ensures each component is completed and tested sequentially, reducing the risk of incomplete implementations.

Autonomous agent iteration is a process where features are broken into user stories and implemented individually in a controlled loop. It uses memory persistence via git, progress.txt, and PRD.json to maintain context across iterations.

Yes, a PRD.json file is required to provide user stories for the implementation process. The autonomous agent uses this file alongside git and log files to track progress and maintain context across iterations.

Yes, the autonomous agent loop supports implementing schema changes, backend logic, UI components, and dashboard views. It breaks these features into user stories and executes them sequentially.

The best way to track progress during autonomous user story implementation is by using git, progress.txt, and prd.json files. These tools maintain context, store learnings, and ensure each iteration is completed before moving forward.

An autonomous loop reduces the risk of incomplete implementations by ensuring each part of a complex feature is completed and tested before moving to the next. It maintains memory and context across iterations automatically.