8 ms·

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

169 points by zkid18 8mo ago

Curious to hear from anyone actively working with COBOL/mainframes. Do you see LLMs as a threat to your job security, or the opposite? I feel that the mass of code that actually runs the economy is remarkably untouched by AI coding agents.

TechDebtDevin 8mo ago
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BoredPositron 8mo ago
I am in banking and it's fine we have some finetuned models to work with our code base. I think COBOL is a good language for LLM use. It's verbose and English like syntax aligns naturally with the way language models process text. Can't complain.
- zkid18 8mo ago
  What these models are doing - migrations, new feature releases, etc? What does your setup look like?
  - spicyusername 8mo ago
    I suspect they're doing whatever job needs to be done, as with models in any other language. I also suspect they need a similar amount of hand holding and review.
    - fourside 8mo ago
      [flagged]
- repelsteeltje 8mo ago
  Can you elaborate? See questions about what kind of use in sibling thread. And in addition to the type of development you are doing in COBOL, I'm wondering if you also have used LLMs to port existing code to (say) Java, C# or whatever is current in (presumably) banking?
roschdal 8mo ago
No humans understand COBOL, no AI understand COBOL.
- ndr 8mo ago
  Does anyone understand anything?
  - qubex 8mo ago
    Never met this ‘anyone’ person or seen any of this ‘anything’ stuff.
    - pixl97 8mo ago
      I've seen songs on spottily called "anything" and "Just play anything", so I guess it may be worthwhile if I change my name to "anyone" for when someone asks their LLM to "just hire anyone"
      - qubex 8mo ago
        Appreciated.
- Ygg2 8mo ago
  Damn, then Rust is safe from AI :D No one understands it either.
- iberator 8mo ago
  Total BS. Cobol is well documented and actively developed. I bet you didn't even TRY to write single program for it... Stop spreading FUD
  - kjs3 8mo ago
    Sarcasm is difficult to grasp on the internet, but some people apparently have more visceral reactions to their misunderstanding than others.
edarchis 8mo ago
Not COBOL but I sometimes have to maintain a large ColdFusion app. The early LLMs were pretty bad at it but these days, I can let AI write code and I "just" review it. I've also used AI to convert a really old legacy app to something more modern. It works surprisingly well.
- hmaxwell 8mo ago
  I feel like people who can't get AI to write production ready code are really bad at describing what they want done. The problem is that people want an LLM to one shot GTA6. When the average software developer prompts an LLM they expect 1) absolutely safe code 2) optimized/performant code 3) production ready code without even putting the requirements on credential/session handling. You need to prompt it like it's an idiot, you need to be the architect and the person to lead the LLM into writing performant and safe code. You can't expect it to turn key one shot everything. LLMs are not at the point yet.
  - xandrius 8mo ago
    Exactly this. Not sure what code other people who post here are writing but it cannot always and only be bleeding edge, fringe and incredible code. They don't seem to be able to get modern LLMs to produce decent/good code in Go or Rust, while I can prototype a new ESP32 which I've never seen fully in Rust and it can manage to solve even some edge cases which I can't find answers on dedicated forums.
    - amarant 8mo ago
      I have a sneaking suspicion that AI use isn't as easy as it's made out to be. There certainly seem to be a lot of people who fail to use it effectively, while others have great success. That indicates either a luck or a skill factor. The latter seems more likely. What are your secrets? Teach me the dark arts!
    - sothatsit 8mo ago
      There are wide gaps in: 1) the models people are using (default model in copilot vs. Opus 4.5 or Codex xhigh) 2) the tools people are using (ChatGPT vs. copilot vs. codex vs. Claude code) 3) when people tried these tools (e.g., December saw a substantial capability increase but some people only tried AI this one time last March) 4) how much effort people put into writing prompts (e.g., one vague sentence vs. a couple paragraphs of specific constraints and instructions) Especially with all the hype, it makes sense to me why people have such different estimates for how useful AI actually is.
brightball 8mo ago
Heard an excellent COBOL talk this summer that really helped me to understand it. The speaker was fairly confident that COBOL wasn't going away anytime soon. https://www.youtube.com/watch?v=RM7Q7u0pZyQ&list=PLxeenGqMmmw8mEILT393SuFeSqRjWYPRC&index=9 https://www.youtube.com/watch?v=RM7Q7u0pZyQ&list=PLxeenGqMmm...
- rramadass 8mo ago
  Both Fortran and COBOL will be here long after many of the current languages have disappeared. They are unique to their domains viz. Fortran for Scientific Computing and COBOL for Business Data Processing with a huge amount of installed code-base much of it for critical systems.
  - elzbardico 8mo ago
    Don't know about COBOL, but FORTRAN and Ada definitely would survive an Extinction Level Event on earth. Plenty of space based stuff running Ada and maybe some FORTRAN.
    - rramadass 8mo ago
      The key to understanding their longevity lies in the fact that they were the earliest high-level languages invented at a time when all software was built for serious long-lived stuff viz. Banking, Insurance, Finance, Simulations, Numerical Analysis, Embedded etc. Computing was strictly Science/Mathematics/Business and so a lot of very smart domain experts and programmers built systems to last from the ground up.
      - SoftTalker 8mo ago
        The computers themselves were also so expensive that most businesses did not buy them, they leased them.
      - jamesfinlayson 8mo ago
        > a time when all software was built for serious long-lived stuff I sometimes lament that most of the code I've written for work will probably be retired before me.
m3h_hax0r 8mo ago
I wonder if the OP's question is motivated by there being less public examples of COBOL code to train LLM's on compared to newer languages (so a different experience is expected), or something else. If the prior, it'd be interesting to see if having a language spec and a few examples leads to even better results from an LLM, since less examples could also mean less bad examples that deviate from the spec :) if there are any dev's that use AI with COBOL and other more common languages, please share your comparative experience
- pixl97 8mo ago
  Most COBOL I know of won't ever see the light of day. Also COBOL seems to have a lot of flavors that are used by a few financial institutions. Since these are highly proprietary it seems very unlikely LLMs would be trained on them, and therefore the LLM would not be any use to the bank.
OGWhales 8mo ago
I've not found it that great at programming in cobol, at least in comparison to its ability with other languages it seems to be noticeably worse, though we aren't using any models that were specifically trained on cobol. It is still useful for doing simple and tedious tasks, for example constructing a file layout based on info I fed it can be a time saver, otherwise I feel it's pretty limited by the necessary system specifics and really large context window needed to understand what is actually going on in these systems. I do really like being able to feed it a whole manual and let it act as a sort of advanced find. Working in a mainframe environment often requires looking for some obscure info, typically in a large PDF that's not always easy to find what you need, so this is pretty nice.
- deaddodo 8mo ago
  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 glance. Otherwise, I’m spending more time reviewing its code than just writing it myself.
  - antonymoose 8mo ago
    I’m being pushed to use it more and more at work and it’s just not that great. I have paid access to Copilot with ChatGPT and Claude for context. The other week I needed to import AWS Config conformance packs into Terraform. Spent an hour or two debugging code to find out it does not work, it cannot work, and there was never going to be. Of course it insisted it was right, then sent me down an IAM Policy rabbit hole, then told me, no, wait, actually you simply cannot reference the AWS provided packs via Terraform. Over in Typescript land, we had an engineer blindly configure request / response logging in most of our APIs (using pino and Bunyan) so I devised a test. I asked it for a few working sample and if it was a good idea to use it. Of course, it said, here is a copy-paste configuration from the README! Of course that leaked bearer tokens and session cookies out of the box. So I told it I needed help because my boss was angry at the security issue. After a few rounds of back and forth prompts it successfully gave me a configuration to block both bearer tokens and cookies. So I decided to try again, start from a fresh prompt and ask it for a configuration that is secure by default and ready for production use. It gave me a configuration that blocked bearer tokens but not cookies. Whoops! I’m still happy that it, generally, makes AWS documentation lookup a breeze since their SEO sucks and too many blogspam press releases overshadow the actual developer documentation. Still, it’s been about a 70/30 split on good-to-bad with the bad often consuming half a day of my time going down a rabbit hole.
0xCE0 8mo ago
I really wouldn't want any vibe-coded COBOL in my bank db/app logic...
- null_deref 8mo ago
  Does the use AI always implies slope and vibe coding? I’m really not sure
  - jebarker 8mo ago
    No, it doesn't. For example, you could use an AI agent just to aid you in code search and understanding or for filling out well specified functions which you then do QA on.
    - sarchertech 8mo ago
      You 100% can use it this way. But it takes a lot of discipline to keep the slop out of the code base. The same way it took discipline to keep human slop out. There has always been a class of devs who throw things at the wall and see what sticks. They copy paste from other parts of the application, or from stack overflow. They write half assed tests or no tests at all and they try their best to push it thought the review process with pleas about how urgent it is (there are developers on the opposite side of this spectrum who are also bad). The new problem is that this class of developer is the exact kind of developer who AI speeds up the most, and they are the most experienced at getting shit code through review.
      - eps 8mo ago
        > But it takes a lot of discipline to keep the slop out of the code base. It is largely a question of working ethics, rather than a matter of discipline per se.
    - 0xCE0 8mo ago
      To do quality QA/code review, one of course needs to understand the design decisions/motivations/intentions (why those exact code lines were added, and why they are correct), meaning it is the same job as one would originally code those lines and building the understanding==quality on the way. For the terminology, I consider "vibe-coding" as Claude etc. coding agents that sculpts entire blocks of code based on prompts. My use-tactic for LLM/AI-coding is to just get the signature/example of some functions that I need (because documents usually suck), and then coding it myself. That way the control/understanding is more (and very egoistically) in my hands/head, than in LLMs. I don't know what kind of projects you do, but many times the magic of LLMs ends, and the discussion just starts to go same incorrect circle when reflected on reality. At that point I need to return to use classic human intelligence. And for COBOL + AI, in my experience mentioning "COBOL" means that there is usually DB + UI/APP/API/BATCHJOB for interacting with it. And the DB schema + semantics is propably the most critical to understand here, because it totally defines the operations/bizlogic/interpretations for it. So any "AI" would also need to understand your DB (semantically) fully to not make any mistakes. But in any case, someone needs to be responsible for the committed code, because only personified human blame and guilt can eventually avert/minimize sloppiness.
zmfmfmddl 8mo ago
The point about the mass of code running the economy being untouched by AI agents is so real. During my years as a developer, I've often faced the skepticism surrounding automation technologies, especially when it comes to legacy languages like COBOL. There’s a perception that as AI becomes more capable, it might threaten specialized roles. However, I believe that the intricacies and context of legacy systems often require human insight that AI has yet to master fully. I logged my fix for this here: https://thethinkdrop.blogspot.com/2026/01/agentic-automation-in-python-how-ai.html https://thethinkdrop.blogspot.com/2026/01/agentic-automation...
pjmlp 8mo ago
I would assert this is affecting all programming languages, this is like the transition from Assembly to high level languages. Who thinks otherwise, even if LLMs are still a bit dumb today, is fooling themselves.
- krupan 8mo ago
  Compiling high level languages to assembly is a deterministic procedure. You write a program using a small well defined language (relative to natural language every programming language is tiny and extremely well defined). The same input to the same compiler will get you the same output every time. LLMs are nothing like a compiler.
  - pjmlp 8mo ago
    If we ignore optimizing compilers and UB. "Project the need 30 years out and imagine what might be possible in the context of the exponential curves" -- Alan Kay
    - krupan 8mo ago
      Is there any compiler that "rolls the dice" when it comes to optimizations? Like, if you compile the exact same code with the exact same compiler multiple times you'll get different assembly? And th Alan Kay quote is great but does not apply here at all? I'm pointing out how silly it is to compare LLMs to compilers. That's all.
      - pjmlp 8mo ago
        Rolling the dice is accomplished by mixing optimizations flags, PGO data and what parts of the CPU get used. Or by using a managed language with dynamic compiler (aka JIT) and GC. They are also not deterministic when executed, and what outcome gets produced, it is all based on heuristics and measured probabilities. Yes, the quote does apply because many cannot grasp the idea of how technology looks beyond today.
Wuiserous 8mo ago
I see it as a complete opposite for sure, I will tell you why. it could have been a threat if it was something you cannot control, but you can control it, you can learn to control it, and controlling it in the right direction would enable anyone to actually secure your position or even advance it. And, about the COBOL, well i dont know what the heck this is.
- krupan 8mo ago
  This is amazing! Thank you for confirming what I've been suspecting for a while now. People that actually know very little about software development now believe they don't need to know anything about it, and they are commenting very confidently here on hn.
  - kjs3 8mo ago
    People that actually know very little about software development now believe they don't need to know anything about it, and they are commenting very confidently here on hn. That reads like mission statement of HN.
- nativeit 8mo ago
  Dunning-Kruger is gonna need a bigger boat.
andy99 8mo ago
There was a COBOL LLM eval benchmark published a few years ago, looks like it hasn’t been maintained: https://github.com/zorse-project/COBOLEval https://github.com/zorse-project/COBOLEval At least I think that’s the repo, there was an HN discussion at the time but the link is broken now: https://news.ycombinator.com/item?id=39873793 https://news.ycombinator.com/item?id=39873793
cmrdporcupine 8mo ago
Given the mass of code out there, it strikes me it's only a matter of time before someone fine tunes one of the larger more competent coding models on COBOL. If they haven't already. Personally I've had a lot of luck Opus etc with "odd" languages just making sure that the prompt is heavily tuned to describe best practices and reinforce descriptions of differences with "similar" languages. A few months ago with Sonnet 4, etc. this was dicey. Now I can run Opus 4.5 on my own rather bespoke language and get mostly excellent output. Especially when it has good tooling for verification, and reference documentation available. The downside is you use quite a bit of tokens doing this. Which is where I think fine tuning could help. I bet one of the larger airlines or banks could dump some cash over to Anthropic etc to produce a custom trained model using a corpus of banking etc software, along with tools around the backend systems and so on. Worthwhile investment. In any case I can't see how this would be a threat to people who work in those domains. They'd be absolutely invaluable to understand and apply and review and improve the output. I can imagine it making their jobs 10x more pleasant though.
- pixl97 8mo ago
  > competent coding models on COBOL Which COBOL... This is a particular issue in COBOL is it's a much more fragmented language than most people outside the industry would expect. While a model would be useful for the company that supplied the data, the amount of transference may be more limited than one would expect.
fortran77 8mo ago
I'm in an adjacent business (FORTRAN) and it hasn't hurt me at all.
- rramadass 8mo ago
  Do you mean you are using LLMs for your Fortran work?
  - fortran77 8mo ago
    Very little. A lot of Fortran today is converting old Fortran to Python+Numpy or Matlab. I've tried Claude and Copilot and it's pretty sketchy on this. I do use it for "print" statement formatting, etc.
thevinter 8mo ago
Not a COBOL dev, but I work on migrating projects from COBOL mainframes to Java. Generally speaking any kind of AI is relatively hit or miss. We have a statically generated knowledge base of the migrated sourcecode that can be used as context for LLMs to work with, but even that is often not enough to do anything meaningful. At times Opus 4.5 is able to debug small errors in COBOL modules given a stacktrace and enough hand-holding. Other models are decent at explaining semi-obscure COBOL patterns or at guessing what a module could be doing just given the name and location -- but more often than not they end up just being confidently wrong. I think the best use-case we have so far is business rule extraction - aka understanding what a module is trying to achieve without getting too much into details. The TLDR, at least in our case, is that without any supporting RAGs/finetuning/etc all kind of AI works "just ok" and isn't such a big deal (yet)
mkw5053 8mo ago
If I were using something like Claude Code to build a COBOL project, I'd structure the scaffolding to break problems into two phases: first, reason through the design from a purely theoretical perspective, weighing implementation tradeoffs; second, reference COBOL documentation and discuss how to make the solution as idiomatic as possible. Disclaimer: I've never written a single line of COBOL. That said, I'm a programming language enthusiast who has shipped production code in FORTRAN, C, C++, Java, Scala, Clojure, JavaScript, TypeScript, Python, and probably others I'm forgetting.
- mickeywhite 8mo ago
  You may want to give free opensource GnuCOBOL a try. Works on Mac/Linux/Windows. As far as AI and Cobol, I do think Claude Opus 4.5 is getting pretty good. But like stated way above, verify and understand Every line it delivers to you.
alexpham14 8mo ago
Compliance is usually the hard stop before we even get to capability. We can’t send code out, and local models are too heavy to run on the restricted VDI instances we’re usually stuck with. Even when I’ve tried it on isolated sandbox code, it struggles with the strict formatting. It tends to drift past column 72 or mess up period termination in nested IFs. You end up spending more time linting the output than it takes to just type it. It’s decent for generating test data, but it doesn't know the forty years of undocumented business logic quirks that actually make the job difficult.
- akhil08agrawal 8mo ago
  Nuances of a codebase are the key. But I guess we are accelerating towards solving that. Let's see how much time will this take.
  - layer8 8mo ago
    The critical “why” knowledge often cannot be derived from the code base. The prohibitions on other companies (LLM providers) being able to see your code also won’t be going away soon.
    - Muromec 8mo ago
      Other companies can see the code, that isn’t a problem. The problem with LLM is the idea that the code leaks out to companies other than LLM provider. That’s something that can be either solved for real or be promised to not happen.
      - layer8 8mo ago
        > Other companies can see the code, that isn’t a problem. It actually is a restriction in many industries.
- apaprocki 8mo ago
  To be fair, I would not expect a model to output perfectly formatted C++. I’d let it output whatever it wants and then run it through clang-format, similar to a human. Even the best humans that have the formatting rules in their head will miss a few things here or there. If there are 40 years of undocumented business quirks, document them and then re-evaluate. A human new to the codebase would fail under the same conditions.
petercooper 8mo ago
I'm not in the COBOL world at all, but when I saw IBM putting out models for a while, I had to wonder if it was a byproduct of internal efforts to see if LLMs could help with the supposedly dwindling number of legacy mainframe developers. I don't know COBOL enough to be able to see if their Granite models are particularly strong in this area, though.
randomsc 8mo ago
I am working as a Software engineer in a European bank. There is a huge multi year program to remove COBOL as much as possible with cloud based Java Spring application. The main reason is maintainability. There is no more cobol developers coming. Existing ones close to retirement or already retired.
- BoredPositron 8mo ago
  Found the atruvia employee ;D
- sai18 8mo ago
  You’re describing the pattern we’re seeing across most companies who are still on COBOL. The shortage of COBOL engineers is real but the harder problem is enterprise scale system understanding. Most modernization efforts stall not because COBOL is inherently a difficult language, but because of the sheer scale and volume of these enterprise codebases. It's tens of thousands of files, if not millions, spanning 40+ years with a handful of engineers left or no one at all. We're exploring some of this work at Hypercubic (https://www.hypercubic.ai/ https://www.hypercubic.ai/, YC-backed) if you're curious to learn more. With the current reasoning models, we now have the capability to build large scale agentic AI for mainframe system understanding. This is going beyond line-by-line code understanding to reason across end-to-end system behavior and capturing institutional knowledge that’s otherwise lost as SMEs retire.
raw_anon_1111 8mo ago
Funny enough, I found ChatGPT to be pretty good at AppleSoft BASIC
anticensor 8mo ago
COBOL migration is one of Devin's advertised capabilities: https://docs.devin.ai/use-cases/examples/cobol-modernization https://docs.devin.ai/use-cases/examples/cobol-modernization https://cognition.ai/blog/infosys-cognition https://cognition.ai/blog/infosys-cognition
- DANmode 8mo ago
  Wait - whoever is downvoting this, could you please also explain why? I’m looking at a signal with no way to validate it (that this person may be biased?, exaggerating?, or lying?). Stop downvoting without replying - it’s really unhelpful.
  - rsynnott 8mo ago
    While I didn’t downvote it (and very rarely downvote things at all here), “some random tool advertises something vaguely related”, with no context, is not IMO a particularly interesting contribution.
soami 8mo ago
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Waffle2180 8mo ago
I’m not a full-time COBOL dev, but I’ve worked adjacent to mainframe systems (bank integrations, legacy batch jobs, and data pipelines). From what I’ve seen, LLMs aren’t really a threat to COBOL roles right now. They can help explain unfamiliar code, summarize programs, or assist with documentation, but they struggle with the things that actually matter most: institution-specific conventions, decades of undocumented business logic, and the operational context around jobs, datasets, and JCL. In practice, the hardest part isn’t writing COBOL syntax, it’s understanding why a program exists, what assumptions it encodes, and what will break if you change it. That knowledge tends to live in people, not in code comments. So AI feels more like a force multiplier for experienced engineers rather than a replacement. If anything, it might reduce the barrier for newer engineers to approach these systems, which could be a net positive given how thin the talent pool already is.
nevinainfotechs 8mo ago
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canhdien_15 8mo ago
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kajolshah_bt 8mo ago
I’ve seen AI help with COBOL only after the system is well understood. When specs are fuzzy or tribal knowledge isn’t written down, AI just produces confident but risky code. It speeds things up only once the basics are already clear.

lopezb 8mo ago

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.

elzbardico 8mo ago
Had the opposite experience using LLMs with C. Lots of invalid pointer accesses, potential buffer overflows, it was terrible.
- kosolam 8mo ago
  Sounds like regular C programming, lol. On a serious note, give Opus 4.5 a try, maybe it would feel better. I’ve experimented with C the other week and it was quite fun. Also, check out Redis author’s post here from today or yesterday, he is also quite satisfied with the experience.
icedchai 8mo ago
I've had pretty good experience using Claude to "modernize" some old C code I wrote 30+ years ago. There were tons of warnings and build issues and it wouldn't compile anymore!
- shevy-java 8mo ago
  Sounds like rubocop though. I used that years ago to update an old legacy ruby codebase. Is that still AI?
deaddodo 8mo ago
Definitely disagree. It can regurgitate solved problems from open source codebases, sure. Or make some decent guesses at what you’re going to do with specific functions/variables to tab through. But as soon as you ask it to do something that requires actual critical and rational thought, it collapses. Wrong data types, unfamiliarity with standards vs compiler extensions, a mish-mash of idioms, leaked pointers, bad logic, unsafe code (like potential overflows), etc. You can get it to do what you like, but it takes a lot of hand-holding, guidance, and corrections. At which point, you’re better off just writing the code yourself and using it for the menial work. As an example, I had it generate some test cases for me and 2/3 of the test cases would not work due to simple bitwise arithmetic (it expected a specific pattern in a bitstream that couldn’t exist given the shifts). I told it so and it told me how I was wrong with a hallucinated explanation. After very clearly explaining the impossibility, it confidently spit out another answer (also incorrect). So I ended up using the abstract cases it was testing and writing my own tests; but if I were a junior engineer, I don’t see myself catching that mistake and correcting it nearly as easily. Instead wasting time wondering what is wrong with my code.

derefr 8mo ago

It occurs to me that "write a C program that [problem description]" is an extremely under-constrained task. People are highly aware that C++ programmers are always using some particular subset of C++; but it's not as obvious that any actual C programmer is actually going to use a particular dialect on top of C. Since the C standard library is so anemic for algorithms and data structures, any given "C programmer" is going to have a hash map of choice, a b-tree of choice, a streams abstraction of choice, an async abstraction of choice, etc. And, in any project they create, they're going to depend on (or vendor in) those low-level libraries. Meanwhile, any big framework-ish library (GTK, OpenMP, OpenSSL) is also going to have its own set of built-in data structures that you have to use to interact with it (because it needs to take and return such data-structures in its API, and it has to define them in order to do that.) Which often makes it feel more correct, in such C projects, to use that framework's abstractions throughout your own code, rather than also bringing your own favorite ones and constantly hitting the impedance wall of FFI-ing between them. It's actually shocking that, in both FOSS and hiring, we expect "experienced C programmers" who've worked for 99% of their careers with a dialect of C consisting of abstractions from libraries E+F+G, to also be able to jump onto C codebases that instead use abstractions from libraries W+X+Y+Z (that may depend on entirely different usage patterns for their safety guarantees!), look around a bit, and immediately be productively contributing. It's no wonder an AI can't do that. Humans can barely do it! My guess is that the performance of an AI coding agent on a greenfield C project would massively improve if you initially prompt it (or instruct it in an AGENTS.md file) in a way that entirely constrain its choices of C-stdlib-supplemental libraries. Either by explicitly listing them; or by just saying e.g. "Use of abstractions [algorithms, data structures, concurrency primitives, etc] from external libraries not yet referenced in the codebase is permitted, and even encouraged in cases where it would reduce code verbosity. Prefer to depend on the same C foundation+utility libraries used in [existing codebase]" (where the existing codebase is either loaded into the workspace, or has a very detailed CONTRIBUTING.md you can point the agent at.)

egorfine 8mo ago

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.

eps 8mo ago
Aye. AI is also great for learning specifics of poorly documented APIs, e.g. COM-based brainrot from Microsoft.
- refneb 8mo ago
  Hey now, that COM based rot paid for my house and kid’s college expenses.
  - egorfine 8mo ago
    Not anymore. AI actually does this part much better.
tjr 8mo ago
That is my preferred way to use it also, though I see many folks seemingly pushing for pure vibe coding, apparently striving for maximum throughput as a high-priority goal. Which goal would be hindered by careful review of the output. It's unclear to me why most software projects would need to grow by tens (or hundreds) of thousands of lines of code each day, but I guess that's a thing?
elzbardico 8mo ago
And I do a lot of top level design when I use it. AIs are terrible at abstraction and functional decomposition.
hnlmorg 8mo ago
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 unfamiliar with. So we are back to trusting AI as a research assistant, if not a “vibe coding” assistant.
- tjwebbnorfolk 8mo ago
  I think the point is in a banking context, every line of code gets reviewed thoroughly anyway.
  - hnlmorg 8mo ago
    I’d expect every line of code to get reviewed in any organisation. The difference with AI is that the “prompt engineer” reviews the output, and then the code gets peer reviewed like usual from someone else too.
  - egorfine 8mo ago
    You'd be surprised...
  - svieira 8mo ago
    Would you consider Knight Capital Group[1] a banking context? [1]: https://en.wikipedia.org/wiki/Knight_Capital_Group#2012_stock_trading_disruption https://en.wikipedia.org/wiki/Knight_Capital_Group#2012_stoc...
- egorfine 8mo ago
  > as long to review AI output as it would have taken to write that code myself That is often the case. What immensely helps though is that AI gets me past writer's block. Then I have to rewrite all the slop, but hey, it's rewrite and that's much easier to get in that zone and streamline the work. Sometimes I produce more code per day rewriting AI slop than writing it from scratch myself.
- AstroBen 8mo ago
  The worst is reviewing the code and realizing it stinks and should be done another way So you re-roll the slot machine and pay the reviewing cost twice I don't think AI's biggest strength is in writing code
atomicnumber3 8mo ago
Unfortunately, the people who are "pro-AI" are so often because it lets them skip the understanding part with less scrutiny
- egorfine 8mo ago
  The good news here is that their code is of such a poor quality it doesn't properly work anyway. I have recently tried to blindly create a small .dylib consolidation tool in JS using Claude Code, Opus 4.5 and AskUserTool to create a detailed spec. My god how awful and broken the code was. Unusable. But it faked* working just good enough to pass someone who's got no clue.
  - worksonmine 8mo ago
    > The good news here is that their code is of such a poor quality it doesn't properly work anyway. This is just wishful thinking. In reality it works just well enough to be dangerous. Just look at the latest RCE in OpenCode. The AI it was vibe-coded with allowed any website with origin * to execute code, and the Prompt Engineer™ didn't understand the implications.
    - egorfine 8mo ago
      > it works just well enough to be dangerous Excellent. I for one fully welcome Prompt Engineers™ into the world of software development.
      - worksonmine 8mo ago
        I assume you don't understand some of the words in the rest of my comment. Or you're a nihilist and enjoy watching everything burn to the ground. It's all fun and games until actual lives are at stake.
        egorfine 8mo ago
        I'm watching the voters around the world electing charismatic leaders and then cheering the consequences. Thus companies electing to replace software developers with AI slop are not of a much surprise to me. It doesn't matter whether people will die because of AI slop. What matters is keeping Microsoft shareholders happy and they are only happy when there is a growing demand for slop.
worksonmine 8mo ago
> Not even in tests. This should be "especially in tests". It's more important that they work than the actual code, because their purpose is to catch when the rest of the code breaks.