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The growing divide between AI hype and software engineering reality

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Re: The growing divide between AI hype and software engineering reality

#91

Post by ma2kx »

lelanthran wrote: post #43
ma2kx wrote: post #33

I really want to agree but the arguments he brings up make that extremely hard > Also, it seems that many don’t want to learn but instead expect to have all understanding outsourced to LLMs. Many seniors have noticed this and have stopped teaching juniors as the seniors don’t like the feeling of having their time wasted by teaching people who don’t want to learn. Or may be it is because now a junior dev is expected t…

> stop saying “please” to an LLM. It does not have any feelings. > Yes, but I still prefer a nice tone. Like why should I change my manners just because it has no feelings? If anything the statistic predicts a friendlier answer when I say "please". It's a probabilistic generator. If you set the tone of the conversation it will follow it. Try inserting a few jokes, puns etc into a conversation and you'll see that it r…

In my opinion its just psychological hygiene. Even though its just a statistical predictor, treating it harshly just conditions me in treating other entities also harsh.

> Try inserting a few jokes, puns etc into a conversation and you'll see that it responds kn kind.

A couple days ago I was setting up new SSH keys encrypted with Ubikey but because I feared losing them and lock me out I evaluated some backup plan with 2FA. Turned out in in my homelab arent that much alternative options, a fingerprint without Linux drivers, an old Galaxy S9 on pmOS without working camera etc. After some ruling out many solutions I proposed a butthole recognition because your butt is in your pants where a face can be recorded by security cams. It recognized the joke and honestly it wasnt the worst answer. It's reply felt like your CEO makes a really bad joke and you have to answer something in order to avoid awkward silence.

Re: The growing divide between AI hype and software engineering reality

#92

Post by pllbnk »

karmakurtisaani wrote: post #49

Tangentially related, I'm starting to think LLM assisted coding will increase the jobs in software engineering. Think about it: code is cheap now. You'll have accountants realizing they can create scripts to automate their work flow, so they hack together something. These scripts will become the backbone of the accounting pipeline of a company. Now someone needs to productionalize and maintain these scripts, but the…

I think that technologies will continue to commoditize and arrive at the global mean (median?), so the need for accountants to have the vocabulary just disappear. They will say what they want and it will be coded, deployed, with CDNs and firewalls and whatnot, the domains will be bought. We are not that far from this state already.

So, I don't buy this Jevons paradox idea for software engineering. I think these explanations that as the software development process becomes more efficient, the need for software developers will increase is incorrect in the context of LLM adoption. Instead, I think it should be phrased as the LLMs become more efficient and widespread, the need for LLMs will increase. Reduction in developer demand will be tangential.

And I am saying this wishing this wasn't true being a developer myself.

Re: The growing divide between AI hype and software engineering reality

#93

Post by prewett »

This is sort of tangential to most of the comments, but his comments on temperature made me wonder if humans have a similar sort of temperature. If you put me in the same conditions, I'm likely to make the same response as I did before (unless I managed to observe some bad consequences). I think other people would consider me fairly predictable. But I bet people like artists have a higher temperature. Maybe one of the things psychodelics do is raise the temperature, so you follow less strong neural pathways.

Re: The growing divide between AI hype and software engineering reality

#94

Post by sshine »

bryanlarsen wrote: post #78
sshine wrote: post #59

Earlier quoted context omitted.

> the speed means that you get more defects and issues You forget to account for the rate of error correction. You can just choose how many bugs you want now: https://nolanlawson.com/2026/08/16/you-can-just-choose-how-m...

That excellent post talks about searching for bugs in extant code, but a similar maxim applies to new code: With AI, you can choose your position on the speed/quality trade-off curve. You can vibe code crap, you can guide/review more closely and get a higher quality product more slowly. And that choice can extend past non-AI coding: with AI you can produce software even more slowly but even higher quality than you di…

> with AI you can produce software even more slowly but even higher quality than you did in the past before AI

I hadn't thought about it before, but this is precisely what I did in one project.

After replacing a webhook that I've been monkey-patching for ten straight bugs, I had enough of an idea of how the software worked and what edge cases to look out for to reproduce the software without the bugs and with a well-modelled, well-tested foundational client library.

After testing the foundational client library with all the methods I know (unit tests, property tests, mock tests, integration tests, and live tests), I had a race condition in my live tests that accidentally turned into a fuzz test of the live service the client connects to, and discovered a bug in the server.

The actual webhook has been brewing for a long time. For weeks I've just casually added more tests. Nothing interesting happened. I've went live with it now, and nothing comes up. So on to make a load test with mock endpoints.

I love how AI makes advanced, extensive testing techniques (and TDD) take little enough time to justify using them all.

As someone who taught CS for some years, it is very satisfying to finally come to a point where "we're not testing" cannot be justified from an economic perspective, it is purely a cultural (or lack of cultural) decision, and a lack of knowledge of any testing techniques beyond unit testing.

Re: The growing divide between AI hype and software engineering reality

#95

Post by pydry »

skeledrew wrote: post #82
woodruffw wrote: post #28

Earlier quoted context omitted.

I generally agree with this. One of the strangest things about LLM driven engineering is holding two seemingly contradictory positions in your head: they’re both better than the median developer, and they’re also much worse at producing artifacts that are comprehensible to humans. I often find myself throwing away large amounts of LLM driven code not because it’s bad, but because it doesn’t fit within my attention sp…

> much worse at producing artifacts that are comprehensible to humans This has always been the case. Just try making sense of the output of any assembler/compiler/transpiler. Why do we think differently about generated source code?

The two metaphors for vibe coding I keep seeing are:

* it's like a compiler => you can trust it

* it's a revolution like the spinning jenny => what came before is fast becoming an obsolete hobby

It's not just that these metaphors are bad, they are absurd if you think about then for just a few seconds.

Re: The growing divide between AI hype and software engineering reality

#96

Post by pydry »

handoflixue wrote: post #5
slowin wrote: post #3

I think this post (and the OSS projects that he mentions that ban AI) are very reactionary. > But the idea that AI has or will surpass humans any time soon in either capabilities or efficiency is simply not true AI is already better than most developers. I'm not sure what alternative reality people are remembering, but human coders for the most part have been really awful at writing code. I think the average PR from…

Yeah, it's a bit absurd. There's so many empirically measured benchmarks where LLMs clearly exceed human capabilities and efficiencies!

it's too bad none of them actually correlate with making good software.
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