Ask HN: COBOL devs, how are AI coding affecting your work?

Post by icedchai » Mon, Jan 19, 2026, 3:35 PM UTC

lopezb wrote: post #42

deaddodo wrote: post #22

Earlier quoted context omitted.

AI isn’t particularly great with C, Zig, or Rust either in my experience. It can certainly help with snippets of code and elucidate complex bitwise mathematics, and I’ll use it for those tedious tasks. And it’s a great research assistant, helping with referencing documentation. However, it’s gotten things wrong enough times that I’ve just lost trust in its ability to give me code I can’t review and confirm at a glanc…

I can't comment on Zig and Rust, but C is one of the languages in which LLMs are best, in my opinion. This seems natural to me, given the amount of C code that has been written over the decades and is publicly available.

Post by genghisjahn » Mon, Jan 19, 2026, 3:37 PM UTC

Quothling wrote: post #45

deaddodo wrote: post #22

Earlier quoted context omitted.

AI isn’t particularly great with C, Zig, or Rust either in my experience. It can certainly help with snippets of code and elucidate complex bitwise mathematics, and I’ll use it for those tedious tasks. And it’s a great research assistant, helping with referencing documentation. However, it’s gotten things wrong enough times that I’ve just lost trust in its ability to give me code I can’t review and confirm at a glanc…

AI is pretty bad at Python and Go as well. It depends a lot on who uses it though. We have a lot of non-developers who make things work with Python. A lot of it will never need a developer because it being bad doesn't matter for what it does. Some of it needs to be basically rewritten from scratch. Over all I think it's fine. I do love AI for writing yaml and bicep. I mean, it's completely terrible unless you prompt…

Post by mholm » Mon, Jan 19, 2026, 3:39 PM UTC

Quothling wrote: post #45

deaddodo wrote: post #22

Earlier quoted context omitted.

AI isn’t particularly great with C, Zig, or Rust either in my experience. It can certainly help with snippets of code and elucidate complex bitwise mathematics, and I’ll use it for those tedious tasks. And it’s a great research assistant, helping with referencing documentation. However, it’s gotten things wrong enough times that I’ve just lost trust in its ability to give me code I can’t review and confirm at a glanc…

AI is pretty bad at Python and Go as well. It depends a lot on who uses it though. We have a lot of non-developers who make things work with Python. A lot of it will never need a developer because it being bad doesn't matter for what it does. Some of it needs to be basically rewritten from scratch. Over all I think it's fine. I do love AI for writing yaml and bicep. I mean, it's completely terrible unless you prompt…

Post by tjwebbnorfolk » Mon, Jan 19, 2026, 3:45 PM UTC

hnlmorg wrote: post #49

egorfine wrote: post #24

Earlier quoted context omitted.

vibecoding != AI. For example: I'm a senior dev, I use AI extensively but I fully understand and vet every single line of code I push. No exceptions. Not even in tests.

Whilst I agree with your point, I think what sometimes gets lost in these conversations is that reviewing code thoroughly is harder than writing code. Personally, and I’m not trying to speak for everyone here, I found it took me just as long to review AI output as it would have taken to write that code myself. There have been some exceptions to that rule. But those exceptions have generally been in domains I’m unfami…

Post by drrotmos » Mon, Jan 19, 2026, 3:50 PM UTC

antonvs wrote: post #54

drrotmos wrote: post #40

Earlier quoted context omitted.

In my experience AI and Rust is a mixed bag. The strong compile-time checks mean an agent can verify its work to a much larger extent than many other languages, but the understanding of lifetimes is somewhat weak (although better in Opus 4.5 than earlier models!), and the ecosystem moves fast and fairly often makes breaking changes, meaning that a lot of the training data is obsolete.

The weakness goes beyond lifetimes. In Rust programs with non-trivial type schemas, it can really struggle to get the types right. You see something similar with Haskell. Basically, proving non-trivial correctness properties globally is more difficult than just making a program work.