Comment by truncate

1 month ago

>> Bad engineers continue being bad, good engineers continue being good.

I don't know if good engineers can necessarily continue to be good. There is limit to how much careful consideration one can give if everything is on an accelerated timeline. Regardless good or not, there is limit on how much influence you have on setting those timelines. The whole playing field is changing.

It's deeper. We used to mock architects that stepped back and stopped coding, because they generated trash.

There's a cycle that is needed for good system design. Start with a problem and an approach, and write some code. As you write the code, you reify the design and flesh out the edge cases, learning where you got the details wrong. As you learn the details, you go back to the drawing board and shuffle the puzzle pieces, and try again.

Polished, effective systems don't just fall out of an engineers head. They're learned as you shape them.

Good engineers won't continue to be good when vibe-coding, because the thing that made them good was the learning loop. They may be able to coast for a while, at best.

  • Reminds me of Gall’s Law from his book Systemantics.

    A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system.

    https://en.wikipedia.org/wiki/John_Gall_(author)#Gall's_law

    • I find that the learning and iteration tends to lead to a simplified system, if you're willing to look hard enough at the shapes needed.

      When there's a lot of complexity, it's often repetitive translation layers, and not something fundamental to the problem being solved.

  • You don’t need to write code by hand to learn from iterations and experiments. I run more experiments and try out more different solutions than I ever could before, and that leads to better decisions. I still read all the code that gets shipped, and don’t want to give that up, but the idea that all craft and learning is lost when you don’t is a bit silly. The craft/learning just moves.

    • How much calculus do you think you could pick up skimming a textbook without doing exercises?

      We mocked these "architects" from experience. We knew that if you weren't feeling the friction yourself, you wouldn't learn enough to do good design.

      Maybe you don't care about engineering great systems. Most companies don't. It's good for profit. This isn't new, though AI enables less care.

      10 replies →

> if everything is on an accelerated timeline

Good engineers are also capable of managing expectations. They can effectively communicate with stakeholders what compromises must be made in order to meet accelerated timelines, just as they always have.

We’ve already had conversations with overeager product people what the ramifications are for introducing their vibe coded monstrosities:

  - Have you considered X?
  - Have you considered Y?

Their contributions are quickly shot down by other stakeholders as being too risky compared to the more measured contributions of proper engineers (still accelerated by AI, but not fully vibe-coded).

If that’s not the situation where you work, then unfortunately it’s time to start playing politics or find a new place to work that knows how to properly assess risk.

An old comic I like:

- I've taken a controversial new pill that accelerates my brain.

-- So you're smart now?

- I'm stupid faster!

That being said, being stupid faster can work if validation is cheap (and exists in the first place).

Turns out "eh close enough" for AGI is just stupidity in an "until done" loop. (Technically referred to as Ralphing.)

Hmmm, I think I disagree with this.

I estimate that I'm now spending about 10 to 30 hours less time a week in the mechanical parts of writing and refactoring code, researching how to plumb components together, and doing "figure out how to do unfamiliar thing" research.

All of those hours are time that can now be spent doing "careful consideration" (or just being with my family or at the gym or reading a book, which is all cognitively valuable as well).

Now, I suppose I agree that if timelines accelerate ahead of that amount of regained time, then I'm net worse off, but that's not the current situation at the moment, in my experience.

  • Maybe we do different things. Not that you are wrong about spending less time on things that you don't care about, but at the same time all that mechanical things helps you build a really good mental model of your product from high level design to individual classes. If I already have a good mental model of that I can direct AI to make really good changes fast, if I don't I will get things done ... but it does end up with less than ideal changes that compounds over time.

    What you said: "figure out how to do unfamiliar thing" -- is correct, and will get things done, but overall quality, maintainability or understanding how individual pieces work...that's what you don't get. One can argue who care about all that as AI can take care of that or already can. I don't think its true today at-least.

    • I guess I just don't really agree that doing the tedious mechanical things is all that helpful for building the necessary mental model. I mean, I do think it was useful (indeed, necessary) for me to actually type out very similar lines of code over and over again when I was building up the programming skillset, but I really think the marginal value of that is just very low for me at this point. I worry a lot about how we're going to train the next generation of people without there being any incentive to do this part of the process! But for me, I already did that part.

      What I find is actually necessary for me to have a mental model of the system is not typing out the definitions of the classes and such, but rather operating and debugging the system. I really do need to try to do things, and dig into logs, and figure out what's going on when something is off. And pretty much always ends up requiring reading and understanding a bunch of the implementation. But whether I personally typed out that implementation, or one of my colleagues, or an AI, is less important.

      I mean, I already had to be able to build a mental model of a system that I didn't fully implement myself! I essentially never work on anything that I have developed in its entirety on my own.

  • Yeah! I mean, who needs to LEARN how to to these things properly when you can just let an autocorrect on steroids hallucinate the closest thing to “barely working”. Right?

    10 to 30 hours saved on not learning new things! Hurray!

    • I genuinely don't understand what you're talking about with this comment. Learn how to do what things properly? I've been writing software for two decades... I'm not primarily in a learning phase, I'm in a doing phase. I'll take advantage of tools that save me time and energy in my work (for the right price). Why wouldn't I?

      What do you mean by "barely working"? I can now put more iterations into getting things working better, more quickly, with less effort. That seems good to me.

      10 to 30 hours a week is 25% to 75% of my time working. Seems like a pretty good trade?

      I do understand that the calculation is different for people who are new to this. And I worry a lot about how people will build their skills and expertise when there is no incentive to put in all the tedious legwork. But that just isn't the phase of my career that I'm in...

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When there is all that crap out there, good engineer may simply just carry out, call it good and leave the industry. Personally seeing the proliferation of wibe coded apps has made me hesitant of publishing and promoting my AI free apps.