YHK - yet another hacker news clone

Totally agreed that we're not looking at the correct metric right now. Increasingly, code quality will be determined by outcomes.

Velocity to solution is default for almost everyone else, especially one-off or low impact / low consequence of failure projects.

Blaming workers is always an excuse by poor management.

2. A lot of it wasn’t. Low quality code/speed serves a purpose for point solutions and scripts etc. That’s not the same thing as writing a core system and if the user doesn’t put any credentials in for an S3 bucket then it falls back to giving information about your own S3 bucket (as I’ve seen just this week).

3. Plenty of companies you can discern the difference between mission critical systems versus “business” systems where if it falls over it’s annoying but not the end of the world.

I've been doing development, in one way or another, since the 90s. I've worked with dozens of teams from enterprises to startups. Hundreds of developers. The quality of work has been all over the place, but the majority was not great.

I'm arguing that what people today call "AI slop" is already higher quality than what most developers created historically, and the fact that tests and documentation pretty much come for free now means that the floor has been raised.

The quality of AI generated code is not great. Yes, it will get better. It's already better than 65%+ of what regular devs can do AND it is faster to produce, iterate, and release.

You can't just rewrite everything. So over many years people are touching small parts of the pie.

If it works it isn't low quality.

So much "bad" enterprise code evolved into that state over years or even decades of small changes. Meanwhile, last year I got to watch an LLM-authored codebase speedrun itself into a similar state in only a couple months. And I would say that the enterprise code was actually better. It at least did its job fairly reliably. The LLM codebase was riddled with defects, so much so that it ate up all our time and our feature delivery rate ground to a halt.

There are two observations that really eat at me:

1. Studies seem to indicate that agentic coding uses 2-10x as many lines of code to accomplish the same task.

2. One of the only really well-established empirical results in software engineering is the strong association between LOC and defect rate.

It's astounding to me that people can see coding get solved and not think every single one of these tasks won't be solved too.

Why in the hell do you not think these things aren't going to be completely automated?

Fable and Astra can one-shot video games with compelling novel game loops. They can do systems programming, distributed systems, robotics. I haven't found a weak point.

Seedance 2.5 can make video better than the manual labor of VFX artists, 3D artists, and animators.

Nano Banana and GPT Image can do a better job than graphics designers.

LLMs just solved a Millennium Prize Problem, and there are probably more that will fall in the coming weeks.

Just wait. All of these things will be solved.

There is no "stopping point".

Edit:

Don't anticipate that 2036 will look anything like 2026.

Will Smith spaghetti doesn't stay that way forever. Trillions of dollars will be spent on solving these problems. They will be solved.

Really doubt we are near that being solved with non-technical folks + LLMs. I'm seeing people gleefully rebuilding products with the exact same blind spots in their understanding/logic using LLMs. Claude, etc are not seemingly able to "AGI" around goofy asks. The CSS looks a little nicer than their legacy products though, lol.

I doubt many people here are brave enough to claim their code does what is supposed to do in every conceivable case. Maybe you have high confidence in the correctness of parts of the code. Correctness of an application is murky though. Things we build are never fully correct, merely correct enough. Like maybe you're responsible for the UI in a web app and you're using your expertise to ensure it gracefully handles display across browsers and a gamut of screen sizes/form factors. But are you also verifying how it works when localized with an RtL script? Are you checking every change you make against CJK?

The refactor ended up adding 22,000 loc.

I went in there and quickly read through it, laughed my ass off. Reverted the work tree. Micromanaged a new refactor. Net lines of code for something really elegant and easy to reason about was -3k loc in the project.

In case you are wondering why vibe coders are doing 30k loc a day, this is why.

My experience is a little different. For higher abstraction languages the output is largely acceptable in my work. I always consider that LLMs don't know what I don't tell them and they have limited context to work from. Coding issues I often identify:

* Efficiency. Marginal by default. Coding efficiency problems often appear because LLMs dont usually consider the entire codebase or future plans (although they do guess at some futures). Sometimes they write/name things in ways that are lazy/wasted cycles. Most of the time, they don't.

* Security. Marginal by default. I say they do pretty good. Considering all the failure modes, not so much.

* Maintainability. Marginal by default. Mostly due to the careful consideration of modularity, upgrade paths, etc. while often taking wildly different approaches to solutions without having specific broad instructions. Even then, there can be big gaps in quality.

* Observability. Not acceptable by default. There's usually some consideration and can often one-shot.

* Portability. Not acceptable by default. Good, if you specify what those targets are. Regardless, testing validates this above the coding and models are very good at hitting functional test targets. This is less of an issue in something like Java ofc.

I finally gave up and read documentation for 15 minutes and solved the problem.

I will never push AI generated code to production without understanding it, and this is why I only generate small code snippets and copy/paste most of the time.