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Comment by noir_lord | Hacker News Reader

Cynically they may be banking (however misguided it turns out to be) on model skill in aggregate growing faster than the skills of their staff decline at which point, bin the staff, use the model.

The hype from non-technical people about AI would make you think they already discovered AGI.

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>> model skill in aggregate growing faster than the skills of their staff decline at which point, bin the staff, use the model.

How people in tech are aware they're training their replacements?

Or are we quickly approaching an apex where the people running these companies realize AI cannot completely replace human developers?

I don't know, I find AI still misses the mark so much for stuff that's not happening inside a well constrained framework with very specific guardrails and boundary conditions. Every time I have agents build something half complex that I would be easily able to pull off myself (albeit not at their pace) I always ask if everything is correct and working and I get a resounding "yes!", then I test it and it's essentially a steaming pile of garbage which I then tell the agent and after which it goes "you're absolutely right to push back, this isn't good at all!" as if it was clear from the beginning. I don't know if we'll achieve real intelligence soon with these things but what we have now isn't there yet. It's incredibly useful but I don't think you can replace a good programmer with it, you can make a good programmer into an excellent one though!

Same goes for writing, anyone who has written long complex texts with LLMs knows that a ton of editing is required to make it half decent.

Even for my tiny toy projects, I notice a bug and I tell the LLM and it corrects it, most of the time, but I shudder at the amount of code it generates or changes.

If it has some subtle data corruption bug then you're hosed.

It's just crazy to me to think about running AI changes in production on a real product.

> Or are we quickly approaching an apex where the people running these companies realize AI cannot completely replace human developers?

The boosters are loud and the failures are made silent, until the failures become impossible to ignore. Tens to hundreds of millions of dollars spent on AI in enterprise software companies need to show RoI at some point, and the promises of executives leaning on AI's productivity improvements to make their accelerated release schedules need to actually make the releases. Its currently a very dangerous career move to publically apply critical thinking to LLM capabilities. I think the math sort of does itself.

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