Prompt Repair and Iteration
Explore prompt repair techniques to improve AI-generated code in vibe coding. Learn to identify when prompts need fixing, narrow scope, pinpoint exact issues, restate constraints, revise parts, and perform step-by-step improvements. This lesson helps you iterate effectively, making prompt engineering a controlled and efficient process for building reliable apps.
Even a well-written first prompt does not always produce a strong first output. The model may overbuild the feature, miss a required business rule, ignore a constraint, or modify behavior that should have stayed the same. That does not mean the attempt failed. Often, the next prompt needs to target the specific problem.
This is where prompt repair becomes useful. Prompt repair is the practice of improving the next request after we see what went wrong in the previous output. Instead of starting over every time, we study the result, identify the exact problem, and send a follow-up prompt that corrects the direction.
That matters because vibe coding is usually iterative. We rarely move from one perfect prompt to one perfect result. We move through rounds of review and correction. Once that is clear, the first practical step is learning how to recognize when a prompt needs repair at all.
When a prompt needs repair
Some follow-up prompts are simple improvements. Others are repairs. A repair is needed when the output is no longer close enough to the goal and needs stronger direction. We usually see this in a few common situations:
The model may do too much at once and make the result more complex than needed.
It may change the wrong part of the app and leave the real problem untouched.
It may get part of the request right, though miss a key rule or state.
It may ignore a limit we care about, such as keeping the page simple or not adding login yet.
Another common problem is that the output is technically related to the prompt, ...