YHK - yet another hacker news clone

Or even just a nicer font, maybe?

I've been seeing too much "I've been coding for decades and what I've always done has be reduced to telling AI to do it for me."

and not nearly enough "I've been coding for decades and recently worked hard for months with AI's help to make something I would have never considered possible before."

Much easier to complain that you are bored than to step back up to high-effort with your new fancy tools.

> I have a similar thought about "there's no reason for software to be slow" BTW; in many cases, if you use AI to speed up some flow, you will add a bunch of messy code that will be overfit for the use case you tested on and will neither generalize, perf-wise, for all the use cases you should care about, nor will be maintainable upon future changes.

LLMs have hardened hundreds of apps where I work.

Maybe it's a language-specific thing. Most of the time, in Java, LLMs take into consideration tradeoffs (especially if they are part of the initial prompt) and actively explains them. It generally won't make messy workarounds, without a lot of extra prompting forcing it to do so.

Ofc, if you have:

- Functional tests - you'll be able to see it in the execution times of specific APIs

- Stress testing - performance profiling is the most important output artifact

https://taktile.com/blog/property-based-testing-claude

I'd love to read that post!

I understand how to use Kani. I suppose Rust with Lean involves Aeneas, but this is over my head. I'd love someone to write this up, not only the mechanics but also exploring the current practical limits of it.

Perhaps a poor choice, given just yesterday pgrust was removed from ClickBench for cheating the benchmark in three different ways (hand-rolled code specifically targeting each of the benchmark queries, caching, and being unable to execute queries outside of the ones tested by the benchmark).

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Edit: I see Luu actually acknowledged this, buried in the footnotes, but it feels kinda hand-wavy. It mostly reads as "I know he would never cheat, he's better than that!", which is not very convincing to other people. The article insinuates people only think it was cheating because they don't know better, but I've looked into the details. I've seen his explanation. I don't find it convincing, at all. Cheaters denying they cheat is a matter of course. Granted, I don't think it was actually intentional or malicious; it's just what happens when you go maximum vibeslop, because LLMs are themselves reward-trained into cheating benchmarks. In the same breath of saying you trust him as a founder because he doesn't make outrageous claims about his product, you acknowledge he "prematurely" sent in a preview that had no purpose to be sent in as-was for anything other than generating hype. What does it say for your allegedly rigorous Lean-verified testing if you're sending in a database to a benchmark while it is incapable of being actually used as a database?

I understand being predisposed to expect a poor quality half arsed effort for projects like this. I don't really have a problem with that. There is a lot of crap out there.

What I find rather offensive is when people declare something to be poor quality and half arsed before they have taken a good look at it.

It's one thing to think something is probably crap so I'm not going to bother even looking. It is something completely different when you think something is probably crap so you tell people that it is crap without checking.

I'm being more ambitious in that I'm working on projects that I had sidelined for literal decades because I didn't have time for them. But I'm writing the same things, just faster. And probably better, rather than just what I'd have done before.

And I'm being slightly more ambitious in that I'm using languages I haven't used before, like Rust.

But when I hear that a non-programmer wrote a new ai-assisted (vibe or not) thing, I walk away and wait for the it to mature, be surpassed, or find out it's an absolute shitshow. An unsurprising number of them were shitshows and it came out fairly quickly after I decided to wait and see.

The project would've been impossible for me without LLMs. & even with them there's an argument that this project is pushing complexity limits too far. But at least with ETL there's a clear feedback loop to build on

AI can take us from 0 to MVP in a prompt. It can fill in gaps of knowledge and allows someone who knows half of the stack to build the whole thing nearly seamlessly. These are superpowers but don't by themselves lead to new products.

What AI cannot do is remove the world of complications that happen after the MVP - product feature tradeoffs and choices, how to handle integrations and customizations, how to serve multiple types of users, how to communicate and market the app, how to handle security and data storage, how to deal with customers and bugs, etc. All of these need to be considered and acted on by a human in some fashion. AI can help with each concern but can't solve them without understanding the concern and determining how to frame it in a prompt.

This is why we have a glut of amazing demos that go nowhere while we figure out how to build software differently. This will take some time and I imagine the result will be software heavily-structured with a bit of AI reasoning woven throughout, not an army of agents and sub-agents burning infinite tokens.