Not saying it's better or worse. But it's definitely different.

My first startup was building requirements management software for small businesses to solve that exact problem. Devs add things in all the time. It's usually referred to as 'gold plating' or scope creep.

The belief that AI can do all that without the gates is throwing away something useful where people get to understand how the system is changing. If you keep the gates but use AI to generate all the code you either slow AI down to the speed of humans or you end up with a massive backlog of stuff to review.

This is a hard problem.

They aren't going to be creating 100 liabilities/hour?[1]

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[1] Each line of code added is a liability. We appear to have forgotten that.

Another of the shallow arguments thrown around, similar to "we don't check compiler output so..."

People learn and improve. LLMs don't learn, they follow instructions to a degree.

A human has to wrestle with it to work how you want, ergo humans are necessary already.

You can't fire the LLM and hire a competent one. The few available is all there is, they're all copies of the same thing.

You don't have a team. If you think 10 LLMs = a team of 10 people, then you don't know what a team is, how different skills and views make a big difference to outcomes.

LLMs can't innovate. They can't come to you with a great idea they came up with. They don't have ideas.

If none of these things are worth anything in your particular case, then that's ok. But let's not actually lose our minds and forget why people are intrinsically better than machines.

There are only a few arguments to support using LLMs, all of which are from people who a) want to spend less on salaries or b) sell you LLMs.

Teams are often hierarchical where the leaders define everything and people under them have less things to say about it. Not much different than an LLM team.