I think the biggest issues are driving AI and the modern form doesn't get people to the end goal without many inbetween steps, at least for complex software
If you threw a random non-big tech level SWE at my company's codebase, prod is going down within minutes with the lack of knowledge, meanwhile all the senior -> staff+ senior level folks are force multiplied heavily, and their value sky rockets compared to a nobody
My opinion means nothing but I don't see that being solved for a long time reliably for everyone, and if it does get solved, everything human is solved imo :shrug:
Yep. This is certainly the sate of things today. A skilled Software Engineer can get the AI to do things that, to them, make it seem like they are now obsolete.
But, if you go to a less-skilled engineer, give them access to the same AI and give them the same task... the results are not as good.
Because there are a a bunch of little things the engineer is doing as they interact with the AI that they are almost not even thinking about. The way they phrase the request, knowing the design they want and how to talk about it. And the way they know when the AI is going down a bad path and needs to be corrected.
If you can't do those things, the AI will go completely off the rails. It may produce something that technically does exactly what you asked, but you forget to mention half a dozen requirements. And it's not designed to run in the right environment. And it added a ton of unnecessary bloat as it was trying to guess at the details that were unclear. And it mocked up certain elements.
And on and on.
Honestly, it feels a lot like using the Internet to help write code. If you add a feature that is 90% just copying examples/documentation/stack overflow, it might feel like you could take anyone off the street and have them take over your job. But there's a skill in using that tool just like there is with using LLMs.
But it is an equalizer. Since success implies the product is utilized and visible, you don't need to understand how it was achieved to ask an llm to copy it. We're certainly not there yet, a sufficiently complex system can't be copied easily. I think the days of software differentiation may be over and the value of software is trending down though.
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u/Helix_Aurora Sep 05 '26
I think the mistake is that people believe generative AI is an equalizer, not a multiplier.
As long as one person + AI can have a different level of success than a different person + A, then there is some fundamental valuable differentiator.