Interesting to see the benefits and drawbacks called out.

In this regard, AI-generated code resembles an itinerant contributor, prone to violate the DRY-ness [don’t repeat yourself] of the repos visited.

So I guess previously people might first look inside their repo’s for examples of code they want to make, if they find and example they might import it instead of copy and pasting.

When using LLM generated code they (and the LLM) won’t be checking their repo for existing code so it ends up being a copy pasta soup.

Sentient Loom
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If you use AI to generate code, that should always be the first draft. You still have to edit it to make sure it’s good.

I totally agree, but I don’t hear any discussion about how to incentivize developers to do it.

If AI makes creating new code disproportionately easy, then I think DRY and refactoring will fall by the wayside.

Sentient Loom
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How do we currently incentivize developers to keep it DRY? Code review still exists.

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