There are two different crowds using "AI":

- One crowd is using to research algorithms, libraries, write boilerplate code, write test harnesses, introspect and integrate with APIs, do hands-off refactoring, and automating what would otherwise be boring tasks. They still think about architecture, best practices, understanding things in detail and the general shape of the solution is in their hands.

- Another crowd is curating prompts, setting up autonomous agents, creating tooling and guardrails around it, anything else but getting actually involved in how the sausage is made. They are working on meta tasks around the problem, in the hope the solution will write itself.

These two crowds are currently living in very different worlds, and getting very different results. We'll see what survives soon.

Are we including just technical people in these crowds?

Because there's a third crowd: everyone else/the general public that are standing up vibe coded websites and don't give a hoot how things work in the background or know as long as money is coming in. There are people that are using AI and thinking less and less causing their brains over the long term to become more inelastic.

We're in for a very, very painful future that will have mixed results. On one hand, you can boostrap things a lot quicker with less mental effort and it helps get up to speed without having to know some complex things (e.g. deep knowledge in coding). This can help us innovate on basic things faster, probably.

On the other ... people aren't going to learn. If something breaks in that state where they don't know how something works, what, we're just going to ask another AI to fix it? I don't know how I feel or think about that. On a long enough timeline, there are people that won't know how any of this was designed in the first place.

That's the world we actually live in. And that's what will survive despite crowd 1 and 2 that you mentioned above.

A lot of people doing the latter camp are people with the knowledge of the former camp, and who are sufficiently happy with the speed and guard rails to no longer worry about "molding the solution in their hands"

I'm not speaking from personal experience, this is what friends are doing at their startups

But I am not surprised at all, because the building blocks of major applications are all out there as boilerplate code - heck half the time AWS has the example you need for you, assuming you know what you want to stitch together and why

If you know the major AWS tool chains and how and why to use them and how to design a product in microservices, then theoretically Claude has no idea what the whole shebang is up to but happily writes all the parts

I don't think thats really it.

For me personally I am vaguely indifferent to programmers using LLMs to make more shitty code. My worry is the second and third order effects

For work currently, as an SRE, I'm being asked to maintain and look after slop as if its properly built and instrumented. Our platform has clear rules and conventions, and AI isn't following those.

For the wider world, I fucking hate that image/video generation is evaporating what is "real". For memes sure its great, but for bad actors it gives a brilliant way to say "its AI wasn't me" and then the debate moves away from "did person do bad thing" to "is it wrong to say that things are AI?"

I also worry about the debasement of value of human work. Looking at history, say of the weavers, it didn't work out to well for them when the powered loom came along.

I wouldn't say those are 'camps' without seeing some data in support of that.

True... I'm in the first crowd personally