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Comments (71)

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  zug_zug
  The complexity stuff is all absolutely true.However I think it's aggrandizing what human engineers actually do with remarks like "Engineers own tradeoffs." My experience is that certainly less than half of the employed software engineers don't actually give a real analysis to questions like:"Given these constraints, this team, this business, this infrastructure, this budget, these risks, and the expected evolution of the product, what is the most appropriate way to implement X, today?"Thus I think AI is more able to replace the average engineer more than this article admits, however the inadequacy of "average engineering" will be much more apparent now: codebases can become large/complex enough to be unwieldy in months now when it used to take 5 years [a timescale where accountability is effectively impossible].
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  cobbal
  Lost me at the first assumption. People can argue about how useful AI is, but it's obviously not essential because we somehow managed to write code without it a few years ago. I would even say the code was better back then.The two tasks of writing code and engineering software cannot be separated without damaging the integrity of the mental model of the engineer. Having architects who didn't interact with the code always produced map/territory mismatches.
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  a2ff6eeb0
  AI can also generate the architecture for you based on the requirements, and ask the necessary clarifying questions.It's not as good at system design as writing code, yet. But it feels like it's better than most of my coworkers.I think in a few months, system architecture will have its Claude Code moment, and humans will be outclassed.
• wyum
  Software complexity grows superlinearly, if not exponentially as you add components.There are things an engineer can do to flatten the curve - that is OP's complexity management idea - but complexity growth can never be linear as long as you are adding to the software.I made a model/theorem for this that I posted on X: https://x.com/i/status/2027771813346820349Code generation has exposed that verification is the central problem of software engineering. And I think it always has been.Defining what is "correct" can be hard enough, let alone building a system that lends itself to verification, let alone spending the time to verify. Releasing software and letting users find bugs is therefore a very efficient strategy, because it spreads the burden. But you have to ride the line between losing users and getting enough feedback to find and fix the bugs that matter.As we confront whether AI might take our jobs, I take some comfort in the idea that the world might be too complex for even the largest, best trained AI we can imagine. At a certain point, you need to simulate the whole world (or some substantial portion of it) and the cost/benefit of trying to do all that with compute may not be worth it versus using the real world (that is, humans) as your verifier.
• softwaredoug
  Sometimes these tradeoffs involve half a dozen over a few lines of code. And that’s where I’m hesitant to let an agent work. It’ll do fine with creating correct code. And you can somewhat constrain it to think about one other thing. But it loses track, ignores constraints, cheats, and do you layer complexity on top to prevent this? Or just look at a dozen lines of code to fix it?
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  thi2
  I started to look around the site and opened this: https://hack8s.com/409/ziglings-all-exercises-solve-v0-16-0The site just goes into a reload loop on iOS?
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  karim79
  Always reminds me of why OOP came about in the first place; it was a way to manage complexity and led to much better and grander software. Now nobody talks about OOP because abstractions are built into just about everything.
• ryandvm
  The real wild shit I'm seeing and having trouble reconciling with continuing my career in this field is that there seems to be a majority contingent of C-suite out there that is absolutely obsessed with force-feeding their organizations AI.As an software engineer, I will readily admit that LLMs have greatly increased my output - especially on the menial work.But now we have leadership telling everyone to "use moar AI" on everything, everywhere. I literally have observed folks dropping into incident Slack chats saying things like, "hey all - i asked Claude about this issue and then i had it write a solution. here's the PR." This feels like the kind of thing that should be a fire-able offense, but instead they're getting shout-outs from the CEO.Hell, the next time I go on vacation, I think I could put Claude Code on YOLO mode for 2 weeks and I'd probably come back to find I'd been promoted.I do not know how this is going to end, but I have a feeling it's going to get way darker before it gets better.
• coredev_
  Thanks, might be the best blog I've read in 2026. AI can of course do architecture as well but oh boy will you have a bad time when your application breaks and neither you or AI can fix it.
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  raevn
  One question missing from the list, and it’s the first one I tend to ask… do we really need this? I’m not sure I’ve ever seen an agent pushing back on a request.
• zerolayers
  AI writing code is a force multiplier and amplifies an orgs existing practices. In other words, if you lack structure and are a fan of chaos engineering, then that gets way worse. On the other hand, if you already have god workflows and an overall structure, it'll help you get things done more quickly.
• wouldbecouldbe
  Its about creating a programmatic tool or game that solves something or creates joy to someone or a group. Thats it. The rest is just a way to make to above goal cheaper or easier to accomplish
• dzonga
  pretty good article.I wish everyone in our industry read 'No Silver Bullet, & Grug-brained Developer'.a lot of complexity - is about what can we do now, with what we have.
• vb-8448
  I agree, but to manager the complexity you need far less swe.
• brvier
  Remember who bought it ? And you expect a better product ? Nahh, really ?
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  intrasight
  All modern engineering is about managing complexity
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  imhoguy
  Is it only me who gets eye pop by just how the font is rendered on that website?
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  threethirtytwo
  These software engineering analogies are getting tiresome.People are shouting “yeah the hard part was never writing code, it was managing complexity” as a sort of last hurrah before AI engulfs them.This is reality: not only can AI write code. It can manage complexity.Prompt: read the article in this thread then execute its principles on my codebase. Write a harness and programmatic procedures that will trigger you to respond with the articles philosophy to code changes. Be vigilant and monitor every aspect constantly.I would say for the above prompt, AI is about 60 to 70 percent as a good as a human now. A year ago it was 20 percent. The gap is closing.
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  skiing_crawling
  It is revisionist to say that software engineering was never about writing code. It was, in fact, a huge component, and it also wasn't easy. Sure most code is glue but even the glue was tedious and the actual hard and novel parts still aren't really done that well by AI (yet).It's less about writing code now but we're lying if we try to pretend it was a distraction and not a big part of the real work.And every claim about what the job actually is or was all along has an implied (for now) at the end of it.
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  junior44660
  The article is AI generated and there's nothing new in it. Just a bait for boomers. Hacker News version of what Gen Z calls "coal posting".
• mermadicsolutio
  [flagged]
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  bananaflag
  I have no idea why people believe AI will not be good at all the other things. It's a general reasoning machine, it surely can reason on many things beside the actual code.I've been hearing this "writing code is not what being an enginner is" mantra for years like some sort of gotcha. (It was prevalent even before AI, and I think people underestimated a lot how many people were simply incapable of writing code even given all the specs and design choices.)