All my product bugs are fixed with vibecoding
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I like how fast vibecoding makes it to build, test, and patch things. A lot of product bugs that would have taken hours now disappear in minutes.
But I still hit a different class of bugs: the ones where the code is technically fixable, but the product decision is not obvious.
Should this edge case be handled in the UI or the backend? Is this a bug, or a missing product rule? Should the agent patch the symptom, or stop and ask what behavior we actually want?
That is where vibecoding gets interesting to me. It is not just about whether AI can write the fix. It is about whether we know what the right fix should be.
For people building with AI coding tools, which bugs still slow you down the most?
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The bugs that slow me down most are usually not syntax bugs. They are context and architecture bugs.
AI can patch an error quickly, but it may fix the symptom without understanding how that change affects authentication, data flow, permissions, billing, or another feature three steps away. That is why I try to define the expected behavior and acceptance criteria before asking it to make the fix.
For larger projects, I also have the agent inspect the surrounding system first, propose the root cause, and explain what could regress before touching the code. Vibe coding is fast, but judgment is still the part that determines whether the fix is actually right.