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kenjackson parent
I can read code much faster than I can write it.

This might be the defining line for Gen AI - people who can read code faster will find it useful and those that write faster then they can read won’t use it.

globnomulous
> I can read code much faster than I can write it.

I have known and worked with many, many engineers across a wide range of skill levels. Not a single one has ever said or implied this, and in not one case have I ever found it to be true, least of all in my own case.

I don't think it's humanly possible to read and understand code faster than you can write and understand it to the same degree of depth. The brain just doesn't work that way. We learn by doing.

kenjackson OP
You definitely can. For example I know x86. I can read it and understand it quite well. But if you asked me to write even a basic program in it, it would take me a considerable amount of time.

The same goes with shell scripting.

But more importantly you don’t have to understand code to the same degree and depth. When I read code I understand what the code is doing and if it looks correct. I’m not going over other design decisions or implementation strategies (unless they’re obvious). If I did that then I’d agree. Id also stop doing code reviews and just write everything myself.

globnomulous
Huh, I don't know x86 but I do plenty of shell-scripting and am surprised, and a little embarrassed, that it had never dawned on me: you're right; they are easier to read, at least with a view to understanding intent, than to write. In fact, are there shell-scripting languages of which this isn't true?
autobodie
I think that's wrong. I only have to write code once, maybe twice. But when using AI agents, I have to read many (5? 10? I will always give up before 15) PRs before finding one close enough that I won't have to rewrite all of it. This nonsense has not saved me any time, and the process is miserable.

I also haven't found any benefit in aiming for smaller or larger PRs. The aggregare efficiency seems to even out because smaller PRs are easier to weed through but they are not less likely to be trash.

kenjackson OP
I only generate the code once with GenAI and typically fix a bug or two - or at worst use its structure. Rarely do I toss a full PR.

It’s interesting some folks can use them to build functioning systems and others can’t get a PR out of them.

omnicognate
The problem is that at this stage we mostly just have people's estimates of their own success to go on, and nobody thinks they're incompetent. Nobody's going to say "AI works really well for, me but I just pump out dross my colleagues have to fix" or "AI doesn't work for me but I'm an unproductive, burnt out hack pretending I'm some sort of craftsman as the world leaves me behind".

This will only be resolved out there in the real world. If AI turns a bad developer, or even a non-developer, into somebody that can replace a good developer, the workplace will transform extremely quickly.

So I'll wait for the world to prove me wrong but my expectation, and observation so far, is that AI multiplies the "productivity" of the worst sort of developer: the ones that think they are factory workers who produce a product called "code". I expect that to increase, not decrease, the value of the best sort of developer: the ones who spend the week thinking, then on Friday write 100 lines of code, delete 2000 and leave a system that solves more problems than it did the week before.

mwcampbell
I aspire to live up to your description of the best sort of developer. But I think there might also be a danger that that approach can turn into an excuse for spending the week overthinking (possibly while goofing off as well; I've done it), then writing a first cut on Friday, leaving no time for the multiple iterations that are often necessary to get to the best solution. In other words, I think sometimes it's necessary to just start coding sooner than we'd like so we can start iterating toward the right solution. But that "unproductive, burnt out hack" line hits a bit too close to home for me these days, and I'm starting to entertain the possibility that an LLM-based agent might have more energy for doing those multiple iterations than I do.
autobodie
My experiences so far suggest that you might be right.
dagw
It’s interesting some folks can use them to build functioning systems and others can’t get a PR out of them.

It is 100% a function of what you are trying to build, what language and libraries you are building it in, and how sensitive that thing is to factors like performance and getting the architecture just right. I've experienced building functioning systems with hardly any intervention, and repeatedly failing to get code that even compiles after over an hour of effort. There exists small, but popular, subset of programming tasks where gen AI excels, and a massive tail of tasks where it is much less useful.

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