"Ralph Wiggum" AI Agent Explained (& How to Use It)

What It Covers

Ryan Carson explains Ralph, an AI coding loop using Claude Opus 4.5 that autonomously builds software features overnight by breaking work into small tasks with clear acceptance criteria and automated testing.

Key Questions Answered

• •PRD to JSON Conversion: Convert product requirement documents into JSON files with atomic user stories completable in one iteration within 168,000 token context limits, each with verifiable acceptance criteria the agent can test independently without human feedback.
• •Autonomous Loop Architecture: Ralph picks one incomplete user story, implements code, tests against acceptance criteria, commits changes, updates progress logs, and repeats automatically—mirroring how engineering teams use kanban boards to manage work units independently.
• •Agent Memory System: Use agents.md files in code folders for long-term learnings and progress.txt for short-term iteration notes, ensuring the AI gets smarter with each mistake and doesn't relearn the same lessons across iterations or future projects.
• •Cost and Setup: Complete feature builds run approximately 10 iterations at $3 per iteration ($30 total), accessible to non-technical users through open-source github.com/snarktank/ralph repository with step-by-step agent guidance for implementation.