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This seems to assume more code shipped equals more work done. I am still not convinced that this is necessarily the case. Sometimes it is. Sometimes it is not. You mentioned that reviews are now the bottleneck and that your familiarity with the code has decreased. That tradeoff might eat into the parallelization gains over time.
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Definitely not - the biggest risk with this increased speed is going full-bore in the wrong direction. A product mindset (and a critical eye to architecture) matters more now than ever.
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Most people hyping their AI use mention the short-term gains without taking into account how it affects overall long-term success. We are creatures of convenience.
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Considering most teams have only switched to heavy AI use in the past few months, the verdict is still out on this.

That said, I've had lots of success using AI to learn, refactor and clean up codebases.

I notice another trend were a lot of AI naysayers haven't really spent a ton of time getting intimately familiar with AI.

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