Last week, I discovered the Ralph Wiggum technique for Claude Code. Named after the perpetually confused Simpsons character, it lets Claude iterate on code autonomously until tests pass.
I gave it a real production task: refactor our healthcare app's authentication module (8 files, 1,200 lines, JWT handling, session management, password reset).
Started: 11 PM Friday
Woke up: 7 AM Saturday
Result: 47 commits, auth module fully refactored, test coverage improved from 62% to 87%
Cost: $23.14 in API credits
Time saved: 6-8 hours of my weekend
The Setup
claude
> /plugin install ralph-loop@claude-plugins-official
> /ralph-loop "Refactor auth module. Extract business logic from controllers.
Max 20 lines per function. Coverage 80%+. All tests must pass."
--max-iterations 100
Then I went to sleep.
What Actually Happened
Claude ran 47 iterations, each one:
- Making changes
- Running tests
- Reading failures
- Adjusting approach
- Trying again
When tests finally passed at iteration 47, it stopped with <promise>COMPLETE</promise>.
The Real Results
Worked:
- Business logic cleanly separated from controllers
- All 8 files refactored systematically
- Test coverage jumped to 87%
- Zero TypeScript errors
- Clean, consistent commit messages
Didn't work:
- Still had to review everything (found 2 edge cases it missed)
- Cost analysis wasn't perfect ($23 vs my estimate of $15)
- Some function names were... creative
The Prompt Makes Everything
My first attempt with a vague prompt ran for 30 iterations and produced garbage.
What worked:
- Clear success criteria (tests pass, coverage %, linting)
- Explicit constraints (max line length, style rules)
- Step-by-step process
- Definitive exit condition
What didn't:
- "Make it better"
- "Improve code quality"
- Subjective goals with no metrics
When to Use This (and When Not To)
Perfect for:
- Refactoring with good test coverage
- Adding tests to untested code
- Bug fixes with failing tests
- Code cleanup tasks
Don't use for:
- Anything without tests (Ralph has no feedback)
- Security-critical code (needs human review at each step)
- Subjective work (UI design, naming, documentation)
- Production data (run in isolated dev environments only)
The Bottom Line
This isn't AGI. It's an extremely capable pattern matcher with good self-correction when tests provide clear feedback.
For healthcare software with HIPAA requirements, I'm keeping autonomous loops in dev environments only. But for the right tasks? It's like having a junior developer who works 24/7 for $20/day.
Full writeup with detailed breakdown, failures, lessons learned, and exact prompts:
👉 Read the complete article on intelligenttools.co
Questions:
- Have you tried autonomous coding loops?
- What's your experience with Claude Code or similar tools?
- What guardrails would you add to this approach?
Drop your thoughts below - genuinely curious how others approach this.
Top comments (0)