[devin]

"as most arguments don't apply to today's world" makes me want to roll my eyes so hard at you. The vast majority of problems we had with building complicated systems are all still just sitting there. People are speedrunning relearning things we've known about software engineering for decades.

The more things change, the more they stay the same.

[rootusrootus]

Between AI and the stock market (which of course relates directly to AI), I’ve lost count of the number of times I’ve heard lately another variation of “this time is different.” Sometimes so close to those words that I wonder why the person speaking them doesn’t feel a bit tingly. Great big warning signs all around.

[tokioyoyo]

The examples I gave, and the arguments that usually support them don’t really translate into “building complicated systems”. I was talking about the arguments in support of variable naming flamewars, etc.

I’m not proponent of AI generating everything without any supervision as of now. But willing to change my mind when it gets better.

Most software engineering jobs are not cutting-edge tech, or research, or solving unsolved problems. Integrations, APIs, figma-to-react pipelines, devops and etc. is what people get hired for. All those can be done much faster in the same-or-better quality by an experienced person with the supplement of AI. It’s hard to imagine any company would go against the grain and slow things down on purpose.

[devin]

So I accept that “nonsense arguments are nonsense”, but with some minor differences of opinion. Naming of things matters insofar as you care as a human to actually conceptualize the system you’re building. You can call all of this stuff minutiae, and on some level I kind of agree, except for the general vibe of _caring about the quality of the stuff you produce_. That is something that still matters whether it “works”. Like, yes you can get an LLM to gen some junk, but _is it any good_ is still something you are in charge of.

As far as “boring systems are boring”, I can tell you from experience that I work on a pretty boring system, and AI is not all that meaningful in terms of its impact, and it’s not for a lack of trying.

Can it help me create a migration and add an endpoint and such? Sure. But those aren’t the hard problems. They never were.

It’s funny that you think the idea of slowing down is such a bad one, but it is another well-established truth. Slow is smooth, and smooth is fast. This notion of break/fixing your way to prosperity by way of 10,000 ill-conceived PRs is a fool’s game.

[tokioyoyo]

I'm sorry, you might be right. But this simply doesn't reflect my daily reality. All I can say is, nobody in my org is creating 10,000 PRs. But everyone is using Claude Code for virtually all commits. We've been doing it since about Opus 4.5ish. So far, so good.

Generally we've modified our timelines heavily, systems are working as intended, company is still making money. There are some AI-authored commits that had mistakes that we didn't catch, but I'm sure this could've been an issue even if all were human-authored. I know first-hand multiple other companies who are doing exactly the same thing.

I agree with "slow is smooth, and smooth is fast" for mission critical systems. But super majority of systems are, indeed, not mission critical.

[devin]

I think we're probably talking past one another a little bit. I use LLMs. Daily, even. I've been doing so since around the same time. The vast majority of people in my organization are doing the same.

I have watched some projects absolutely explode in LOC added, number of PRs, etc. but I think the more interesting question is: how much of it is directly being done to add customer value, how much of it is churn, etc. you might get some interesting answers.

As so frequently seems to be the case for you and I, we kind of agree but then you drop something that just does not compute for me: "slow is smooth, and smooth is fast" is not specific to "mission critical" systems, it is generally applicable.

As I said in a previous comment, I work on a fairly boring system. Its "criticality" is debatable, but in general we make the same kinds of boring guarantees to our users that even mediocre SaaS products offer: a few 9s of uptime, zero-downtime deploys, etc. AI has made aspects of working on this system easier, but in terms of API surface, how users are using it, how to safely advance its state without breaking existing callers, data migrations across services, and so on, very little has changed.

[therealdrag0]

I have the same experience. Slow is smooth with AI is still productivity improvement.

[LtWorf]

But is it enough of an improvement to justify the cost? (Since the current raises are probably just the beginning)

[therealdrag0]

It depends :). It’s enough I pay for it for my silly side project. Historically we’ve paid a lot for software tools. IDEs and even documentation used to be pretty expensive. AI seems at least on par with those.