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Comment by StevePrefontain | Hacker News Reader

We are having trouble onboarding engineers with AI now. Some still struggle after their first year with very basic concepts/patterns we use and make the same mistakes again and again in their PRs because they just ask Claude to fix it and never internalize it. I think using LLMs feels good at first because you can get tickets out the door faster but you never develop enough knowledge to make a big impact or become an expert in the code or business.

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These would have been good hires before AI but now they struggle?

My guess is they would take longer to ramp up but then have a better understanding of the codebase and domain.

But there’s a lot of pressure to get up to speed as a new hire and it’s easy to move fast with AI

I imagine they are still good hires - however there is a real cognitive debt that happens when we code with LLMs in my experience.

It’s harder to internalise concepts because you don’t go through the struggle of understanding them and finding the mental links you need to remember later.

I notice this with people around me - all of them are doing more things, but I am also catching more issues when reviewing docs and code.

Obviously YMMV.

Honestly you should probably invest in baking the basic patterns and concepts of your codebase into shared skills that are applied to everyone's Claude sessions.

Or documentation that everyone could read and refer to

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