Feed validation errors back into LLM retries for better structured output

A developer shares a technique to improve LLM structured output: when validation fails, include the error message and the model's bad output in the next prompt. This turns a blind retry into a targeted fix, boosting success rates without extra cost. The approach is demonstrated with a Python loop that appends error context to the message list.