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# How to Debug AI Coding Agents When They Change the Wrong Thing

**[Towards Data Science](https://daily.dev/sources/tds)** · 14 min read · 1 upvotes · 0 comments

## Summary

AI coding agents often return vague success messages like 'fixed' without providing evidence of what they actually changed. This tutorial demonstrates a pattern for recording and verifying agent actions using a Python wrapper that logs every tool request and result. Using a CSS overflow bug in a pricing card as the example, it shows how to capture file reads, patches, build output, DOM measurements, and before/after screenshots. The run log exposes wrong selector attempts, skipped checks, and other failure modes invisible in the final code. The pattern generalizes beyond UI fixes to API bugs, test failures, database changes, and refactors by swapping the verification tool while keeping the same evidence structure.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/how-to-debug-ai-coding-agents-when-they-change-the-wrong-thing>

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Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#mcp](https://daily.dev/tags/mcp)

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