The Ralph Loop idea is simple: short autonomous runs, fresh context each time, strict verification in between.
It sounds almost too basic. It works because it avoids the long-session failure modes we keep seeing.
Minimal setup
You need three files:
- A spec file with goal, constraints, and done criteria.
- A task input file for the current iteration.
- A verify script that can fail hard on bad output.
Then run loop, verify, and only keep good changes.
Why this beats marathon sessions
Each iteration starts clean, so context poisoning does not accumulate. You also stay far from the dumb zone.
The model does one focused unit of work, not twenty mixed goals in one thread.
Where people get stuck
Most failures come from weak verification. If your checks are soft, the loop just ships bad work faster.
Strong back pressure is the point. Tests, lints, build, optional screenshots. No green, no merge.
Start small
Run this pattern on one feature branch first. Keep iteration scope tiny. One task that fits in a short session.
Once that is stable, increase autonomy. Do not start with a giant all-day loop.