Building the rendering pipeline, algorithms, maths, I've turned off even level 2. It is just more of a distraction than it's worth for that deep state of focus.
So I imagine at least some of the disconnect comes from the area people work in and its novelty or complexity.
This attribute plus a bit of human tribalism, social echo-chambering, & some motivated reasoning by people with a horse in the race, easily explains the discord I see in rhetoric around AI.
The fact is, I think the art of building well with AI (and I'm not saying it's easy) is to have a heterogenously vibe-coded app.
For example, in the app I'm working on now, certain algorithmically novel parts are level 0 (I started at level 1, but this was a tremendously difficult problem and the AI actually introduced more confusion than it provided ideas.)
And other parts of the app (mostly the UI in this case) are level 7. And most of the middleware (state management, data model) is somewhere in between.
Identifying the appropriate level for a given part of the codebase is IMO the whole game.
This part of your post I think signals that you are either very new or haven't been paying attention; single developers were outperforming entire teams on the regular long before LLMs were a thing in software development, and they still are. This isn't because they're geniuses, but rather because you don't get any meaningful speedup out of adding team members.
I've always personally thought there is a sweet spot at about 3 programmers where you still might see development velocity increase, but that's probably wrong and I just prefer it to not feel too lonely.
In any case teams are not there to speed anything up, and anyone who thinks they are is a moron. Many, many people in management are morons.
There may be certain fields where you can't even get to 5.
I could probably get to a 7 with some additional tooling and a second max 20 account, but I care too much about the product I'm building right now. Maybe for something I cared less about.
IMO if you're going 7+, you might as well just pick a statically typed and very safe (small surface area) language anyways, since you won't be coding yourself.
> of course some people think that you lose touch with the ground if you go above AI Level 2
I really think that this framing sometimes causes a loss of granularity. As with most things in life, there is nuance in these approaches.
I find that nowadays for my main project I where I am really leaning into the 'autonomous engineering' concept, AI Level 7 is perfect - as long as it is qualified through rigorous QA processes on the output (ie it is not important what the code does if the output looks correct). But even in this project that I am really leaning into the AI 'hands-off' methodology, there are a few areas that dip into Level 5 or 4 depending on how well AI does them (Frontend Design especially) or on the criticality of the feature (in my case E2EE).
The most important thing is recognizing when you need to move 'up' or 'down' the scale and having an understanding of the system you are building
Thanks for that list of levels, it's helpful to understand how these things are playing out and where I'm at in relation to other engineers utilizing LLM agents.
I can say that I feel comfortable at approximately AI level 5, with occasional forays to AI level 6 when I completely understand the interface and can test it but don't fully understand the implementation. It's not really that different from working on a team, with the agent as a team member.
I’m not sure I believe that Level 7 exists for most projects. It is utterly *impossible* for most non-trivial programs to have a spec that doesn’t not have deep, carnal knowledge of the implementation. It can not be done.
For most interesting problems the spec HAS to include implementation details and architecture and critical data structures. At some point you’re still writing code, but in a different language, and it migtt hurt have actually been better to just write the damn struct declarations by hand and then let AI run with it.