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Ask HN: How to deal with shipping AI-written code you don't understand?

3•rzk•1h ago
I saw this LinkedIn post from a Meta engineer and it resonated with me:

https://www.linkedin.com/posts/ali-hamie_im-an-engineer-at-meta-and-i-never-felt-share-7517317918666211328-7C8N

> I'm an engineer at Meta and I never felt this uncomfortable doing my job. I'm writing code these days and it all feels like a black box. This new standard of shipping with AI is moving so fast that if we're going to spend our time checking each line of code, it's going to take forever. That means you can end up with systems you've built where you don't truly understand how all the code works. You understand the high level, but not every detail. And maybe this is becoming the new standard. It goes against every instinct of being a software engineer. I'm used to understanding what I'm building. Now I'm trying to figure out how much I need to understand before I'm comfortable moving forward. Are other engineers feeling this too?

How are you handling this?

Comments

pluc•1h ago
The solution is more AI. Throw another agent in to watch your logs, then throw in another agent to watch that agent.

Quality is no longer an objective. If it breaks, rebuild it and tell it not to break.

voidUpdate•1h ago
It's agents all the way down!
pluc•1h ago
<that scene from the Matrix with hundreds of Agent Smith>.gif
paid_dot_expert•1h ago
Sort of. What if you asked your second agent to fuzz test the work of the first agent, adversarial code review, or make a video to explain all the code.
ORDINAND_PIZZA•1h ago
wow, “quality is no longer an objective” is a wild idea that feels dangerously negligent.

quality is all we have, it’s what makes us different from these agents.

quality is perplexing to agents because it requires a strange loop into asking why. there’s not always a clear answer. but i think the power is in the ambiguity.

if we don’t know why (or don’t care) then what happens if we all adopt this attitude at scale?

pluc•1h ago
The entire industry is dangerously negligent, we just have better tools and stronger incentives now. Why spend 3h code-reviewing a PR when you know if it breaks you just tell your agent to watch out for that specific scenario? Which executive will see that as time well spent?
spacedcowboy•1h ago
I’m slowly coming around to the idea that if it works, I’m good with that. I never used to personally check all my colleagues work, either, I just trusted that they’d done a good job.

That’s not to say I blindly trust an LLM - my project is an autovectorising compiler. I have it write a bazillion tests, and I have real, non-trivial programs that it compiled. I have it run a ‘gate’ before releases that takes literally hours on 5 different architectures. To say this code is tested is … masterful understatement.

I think what helps is a long planning session, going into details, working out corner cases, designing test-cases, you know work and effort. Once that’s done it’s easier to let it work through the night and do a major production feature.

I still review the code, but hand on heart I couldn’t say I’d reviewed everything, sometimes I miss something in a complicated check-in. I try to keep checkins small and contained, but sometimes that’s not easy to manage alongside the “don’t break stuff” rule as well.

So it comes down to: I’ve been working on this for 6 months or so, and so far this has worked out for me. You know, kind of like getting used to a colleague’s idiosyncrasies over a period of time.

I will say that in my experience the code quality is fairly high. Maybe that’s down to the effort put in ahead of time in the planning stages, I don’t know, but I don’t seem to suffer from the ‘slop’ that people complain of. YMMV.

yulaow•1h ago
I am not in META but for what I read on blind, assuming it is true, they are not spending any time in long planning sessions or in getting into details of the implementation plan at all, and they could not anymore considering how many PRs in parallel they are requested to manage
spacedcowboy•27m ago
Yeah, I'm retired. The only person I have to answer to regarding progress is me. I'm a stubborn son of a bitch when it comes to choosing quality over speed...

That doesn't mean I don't like progress mind :) This morning I got the preliminary results of a 'C' front-end to the compiler (it uses clang to compile to LLVM IR, then translates to our IR, then feeds that IR into the autovectoriser as if it had parsed the code itself). So for the exact same source code I now have:

     ┌─────────────┬────────────┬──────────────────────┬──────────┐
     │  Benchmark  │ clang -O2  │ xcc --par-auto (GPU) │ Speed-up │
     ├─────────────┼────────────┼──────────────────────┼──────────┤
     │ saxpy       │ 1,546 µs   │ 726 µs               │ 2.1×     │
     ├─────────────┼────────────┼──────────────────────┼──────────┤
     │ Mandelbrot  │ 394,238 µs │ 2,110 µs             │ 187×     │
     ├─────────────┼────────────┼──────────────────────┼──────────┤
     │ nbody       │ 37,090 µs  │ 1,035 µs             │ 36×      │
     ├─────────────┼────────────┼──────────────────────┼──────────┤
     │ perlin      │ 78,016 µs  │ 1,850 µs             │ 42×      │
     ├─────────────┼────────────┼──────────────────────┼──────────┤
     │ mandel_deep │ 73.2 s     │ 55.8 ms              │ 1,312×   │
     └─────────────┴────────────┴──────────────────────┴──────────┘
Those are some pretty fine speedups, from naive C, with no alterations from the standard "C" code - it automatically finds places that can be made data-parallel, tracks the data-hazards to make sure its safe to "GPU" and writes all the kernels, boilerplate and data-stream-management if necessary. Obviously the checksums have to match, so I know it did the work correctly too :)

Hacker News isn't interested - any post I make linking to the webpages is immediately blocked/dead so I'll wait until the C++ front-end is ready (some time next week) and announce it somewhere else. A compiler that takes standard C/C++ code and speeds it up by automatically finding data-parallel areas and scheduling them on the GPU with no programming overhead is pretty rare.

Oh, and it manages the local network as well, so you can run xcd on machines on your lan, or via the TB4/5 bridge between Macs and it'll schedule on other GPUs, just like it manages multiple GPUs on the local machine. It characterises both latency and compute-time to figure out which devices are worth scheduling on.

pinscope_dev•58m ago
I had same problem, but after a while I just accepted that is inevitable
edwin0•35m ago
The part that makes me uneasy is when the AI writes both the code and the tests. They might agree with each other and still miss the same thing. How are people here checking for that without doing the whole job twice?