Larity brings structure to prompt engineering — so you spend less time guessing, and more time shipping.
How it works
Start with whatever you have. A rough instruction, a copied snippet, a half-formed rubric. Larity does not care how polished the first attempt feels.
Every false positive and false negative appears immediately. No spreadsheet archaeology, no hopping between notebooks, no guessing where the regression came from.
The system suggests targeted prompt changes based on the misses. You can apply the idea, skip it, or keep editing manually without losing the trace of why the suggestion existed.
Scores, pass rates, and the history of revisions let you see whether you are still learning or just circling. When the gains flatten, ship and move on.
Prompt engineering works better when each revision is attached to evidence, not instinct.
Structured iteration beats endless prompt tweaking
Why Larity exists
Manual iteration burns time with no clean stopping point. You tweak, compare, second-guess, and end up losing a day on work that should have been measured sooner.
Without a visible score history, the seventh attempt only feels better. That is not enough when the cost of shipping a weak prompt is operational.
The misses from the last project tend to resurface in the next one. A shared iteration record turns edge cases into memory instead of folklore.
Know when the prompt is strong enough. Ship it. Keep the history. Move on to the next problem.
Start for free