Finding signal on Twitter is more difficult than it used to be. We curate the best tweets on topics like AI, startups, and product development every weekday so you can focus on what matters.
Ralph is an autonomous AI coding loop that ships features while you sleep.
Created by @GeoffreyHuntley and announced in his original post, it runs @AmpCode (or your agent of choice) repeatedly until all tasks are complete.
Each iteration is a fresh context window (keeping Threads nice and small). Memory persists via git history and text files.
I ran it for the first time and shipped a feature last night. I love it.
How It Works
A bash loop that:
Pipes a prompt into your AI agent
Agent picks the next story from prd.json
Agent implements it
Agent runs typecheck + tests
Agent commits if passing
Agent marks story done
Agent logs learnings
Loop repeats until done
Memory persists only through:
Git commits
progress.txt (learnings)
prd.json (task status)
File Structure
ralph.sh
The loop:
Make executable:
Other agents:
Claude Code: `claude --dangerously-skip-permissions`
prompt.md
Instructions for each iteration:
prd.json
Your task list:
Key fields:
`branchName` — branch to use
`priority` — lower = first
`passes` — set true when done
progress.txt
Start with context:
Ralph appends after each story.
Patterns accumulate across iterations.
Running Ralph
Runs up to 25 iterations.
Ralph will:
Create the feature branch
Complete stories one by one
Commit after each
Stop when all pass
Critical Success Factors
1. Small Stories
Must fit in one context window.
2. Feedback Loops
Ralph needs fast feedback:
`npm run typecheck`
`npm test`
Without these, broken code compounds.
3. Explicit Criteria
4. Learnings Compound
By story 10, Ralph knows patterns from stories 1-9.
Two places for learnings:
progress.txt — session memory for Ralph iterations
AGENTS.md — permanent docs for humans and future agents
Before committing, Ralph updates AGENTS.md files in directories with edited files if it discovered reusable patterns (gotchas, conventions, dependencies).
5. AGENTS.md Updates
Ralph updates AGENTS.md when it learns something worth preserving:
6. Browser Testing
For UI changes, use the dev-browser skill by @sawyerhood. Load it with `Load the dev-browser skill`, then:
Not complete until verified with screenshot.
Common Gotchas
Idempotent migrations:
Interactive prompts:
Schema changes:
After editing schema, check:
Server actions
UI components
API routes
Fixing related files is OK:
If typecheck requires other changes, make them. Not scope creep.
Monitoring
Real Results
We built an evaluation system:
13 user stories
~15 iterations
2-5 min each
~1 hour total
Learnings compound. By story 10, Ralph knew our patterns.
When NOT to Use
Exploratory work
Major refactors without criteria
Security-critical code
Anything needing human review
For a great video walkthrough of how to use Ralph, checkout the video from @mattpocockuk ...
