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Comment by waltbosz

7 days ago

My experience is it often generates code that is subtlety incorrect. And I'll waste time debugging it.

But if I give it a code example that was written by humans and ask it to explain the code, it gives pretty good explanations.

It's also good for questions like "I'm trying to accomplish complicated task XYZ that I've never done before, what should I do?", and it will give code samples that get me on the right path.

Or it'll help me debug my code and point out things I've missed.

It's like a pair programmer that's good for bouncing ideas, but I wouldn't trust it to write code unsupervised.

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waltbosz

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maerch  7 days ago

> My experience is it often generates code that is subtlety incorrect. And I'll waste time debugging it.

> […]

> Or it'll help me debug my code and point out things I've missed.

I made both of these statements myself and later wondered why I had never connected them.

In the beginning, I used AI a lot to help me debug my own code, mostly through ChatGPT.

Later, I started using an AI agent that generated code, but it often didn’t work perfectly. I spent a lot of time trying to steer the AI to improve the output. Sometimes it worked, but other times it was just frustrating and felt like a waste of time.

At some point, I combined these two approaches: I cleared the context, told the AI that there was some code that wasn’t working as expected, and asked it to perform a root cause analysis, starting by trying to reproduce the issue. I was very surprised by how much better the agent became at finding and eventually fixing problems when I framed the task from this different perspective.

Now, I have commands in Claude Code for this and other due diligence tasks, and it’s been a long time since I last felt like I was wasting my time.