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In a similar vein, I remember people advocating for replacing new untrained hires with AI. After all, a competent senior engineer is needed to validate the contributions of the new hires anyway and they can do the same checking the AI code.

But then, how would you even train and replace those competent seniior engineers that do the filtering when they retire? The whole system was predicated on having a chain of new hires that gain experience in the process.






From what I could perceive, companies believe coding AIs will eventually learn to both code and teach better than seniors.

This is based on two assumptions:

- AI will get better. Developers using the system will transfer their knowledge to it.

- Seniors in a couple of years will be different. They should be those who can engage with the AI feedback loop.

Here's why I think it won't work:

- Senior developers learn more than they can produce. There is knowledge they never transfer to what they work on. Internalized knowledge that never materializes directly into code. _But it materializes indirectly_.

- Senior developer knowledge come from "schools", not just reading. These schools are not real physical locations. They're traditions, or ideas, that form a very long tail. These ideas, again, are not directly transferrable to code or prose.

- Juniors get embarrassed. You say "stop making this nonsense", and they'll stop and reflect, because they respect seniors. They might disagree, but a pea was then placed under their matress, and they'll think about "this nonsense" you told them to stop doing and why. That is how they get better. So far, AI has not demonstrated being able to do that.

The production of quality content is an aspect of one of those "schools of thought". You are supposed to bear the responsibility of passing the knowledge. Keeping lean codebases easy to understand is also a hallmark of many schools of thought. Working from fundamentals is another one of those ideas, etc.




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