[JumpCrisscross]

> they are not agentic systems that can develop an entire solution from scratch given a specification, which in my experience is more typcical of the work that is being outsourced

If there is one domain where we're seeing tangible progress from AI, it's in working towards this goal. Difficult projects aren't in scope. But most tech, especially most tech branded IT, is not difficult. Everyone doesn't need an inventory or customer-complaint system designed from scratch. Current AI is good at cutting through that cruft.

[ehnto]

There have been off the shelf solutions for so many common software use cases, for decades now. I think the reason we still see so much custom software is that the devil is always in the details, and strict details are not an LLMs strong suit.

LLMs are in my opinion hamstrung at the starting gate in regards to replacing software teams, as they would need to be able to understand complex business requirements perfectly, which we know they cannot. Humans can't either. It takes a business requirements/integration logic/code generation pipeline and I think the industry is focused on code generation and not that integration step.

I think there needs to be a re-imaging of how software is built by and for interaction with AI if it were to ever take over from human software teams, rather than trying to get AI to reflect what humans do.

[netdevnet]

This, code is written by humans for humans. LLMs cannot compete no matter how much data you throw at them. A world in which software is written by AI will likely won't be code that will be readable by humans. And that is dangerous for anything where people's health, privacy, finances or security is involved