Ralph pattern automates software development via autonomous PRD-to-code loops

Ralph is the "anti-context" solution to the LLM hallucination problem, effectively industrializing the "Ralph Wiggum" pattern of naive but persistent iteration.

• –Solves "context rot" by resetting the AI session for every task, ensuring each code change is made with maximum model intelligence and zero conversational baggage.
• –Moves the "source of truth" for memory out of the LLM context and into deterministic layers like Git history, `prd.json`, and `progress.txt`.
• –Tight integration with CLI-based verification (tests, linting, type-checking) allows the loop to self-correct until acceptance criteria are met.
• –The workflow shifts the human role from "active prompter" to "asynchronous reviewer," dramatically increasing individual developer leverage.
• –While powerful, it relies heavily on the quality of automated test suites; without a strong verification layer, the loop can effectively automate the production of "logical slop."