Ralph Wiggum Explained: Stop Telling AI What You Want – Tell It What Blocks You
10 hours ago
- #Prompt Engineering
- #Automation
- #AI Development
- The Ralph Wiggum technique for Claude Code involves writing a prompt and letting AI work autonomously, but often results in incomplete or non-functional outputs.
- The issue lies not in the AI but in the criteria set for success; vague criteria lead to vague results.
- Instead of 'better prompts,' the focus should be on designing binary, verifiable constraints that the AI can clearly meet or fail.
- Constraints should be things a script can check, like build success or file existence, rather than subjective measures like 'good UX.'
- Examples of converting wishes into constraints include replacing 'works on iOS' with 'dotnet build -f net10.0-ios exits 0.'
- Setting tight, clear criteria reduces iteration count and cost, while vague criteria do the opposite.
- Limitations include aesthetic judgments, performance at scale, security vulnerabilities, business logic correctness, and integration complexity, which require human review.
- The key takeaway is that Ralph Wiggum is a loop with a termination condition; success depends on clear, binary constraints.