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> ...okay on simple tasks, but actually misguides, confuses, and in fact breaks your flow of thought on anything beyond that.

Beyond the LLMs themselves, don't you think this is related to the data used for training? I mean, this echoes what you find as a developer on the wild, you can find answers to "all" simple things, much less discrete answers to complex stuff, and almost nothing for very complex stuff and/or specific programming domains.

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I think half the problem is the form factor of using it as an auto complete.

I might instinctively know what to write, hit tab, and miss what copilot actually wrote isn't what I wanted to write. For example, it might add when you meant to subtract from a list but my quick scan didn't catch it. So you originally miss it, bump into a bug when writing tests, and spend more time fixing it than if you had just typed it out to begin with.

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