Why AI debugging loops fail and how staged prompts can break them

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Developers often find that repeatedly pasting errors into an AI model yields confident patches that shift the problem elsewhere, leaving code messier and the root cause unclear. The author argues the issue is that a single "fix this" request bundles reproduction, localization, cause analysis, and regression checking together, causing the model to skip ahead and guess. The proposed remedy is to ask for one stage at a time, starting with reproducing the bug from a clean state and listing missing environment details first. Subsequent stages cover halving the search space through targeted checks, explaining the root cause with a code comment, and identifying other code that relies on the same faulty assumption. The post also promotes PromptAlo, a Chrome extension for saving and reusing such prompts across ChatGPT, Claude, and Gemini.

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