11 ms·

An "oh fuck" moment in time

88 points by ghuntley 2y ago

PaulHoule 2y ago
My experience is sometimes it works amazingly well like you say, and sometimes it doesn't. LLMs are great at translations, like "convert this SQL to JooQ" or "convert this Chinese text to English". If you were going from Haskell -> Rust it might have trouble fighting with the borrow checker, or it might not if your memory usage patterns were straightforward or you can "RC all the things". Haskell's a particularly good target because less state means less complexity thinking about state.
- ghuntley 2y ago
  So very tempting to put it to the task. Any takers? Try converting https://hackage.haskell.org/package/megaparsec https://hackage.haskell.org/package/megaparsec to rust.
  - almostdeadguy 2y ago
    Just tried this using similar prompting to the original and it required several rounds of telling it about compiler errors before generating something that looked suspiciously like a _very_ basic version of "nom", without any of the state/position tracking or the nice error model in megaparsec. I suspect anyone talking about instances where doing something like this "just works" is a grifter/aspiring AI influencer.
- BalinKing 2y ago
  FWIW even with machine translations (on GPT-4o) I do get occasional hallucinations. Like, it'll add an additional sentence or relative clause that wasn't in the original. It'll still make sense in context, so the overall meaning is the same, but it's not what I'd expect from, say, a human translator. (For context, I know enough of both languages—English and Japanese—to be able to verify this myself.) It doesn't happen very often—maybe 1 out of 50 times?—but it's definitely a somewhat regular occurrence. And ofc, it's not just a result of the fact that every language is different and so the same meaning will need to be expressed differently—it's actually hallucinating bona fide content.
  - BalinKing 2y ago
    Oh, and IME it doesn't ask clarifying questions that a human translator would know are necessary (at least without explicit prompting to do so, which I admittedly haven't tried). So when translating from a high-context language like Japanese, it'll come up with a translation that works in some contexts but is meaningless in others. I figure this is related to the overconfidence issue that's prevalent with (current) LLMs.
jchw 2y ago
I don't care that much for the commentary about who will or will not make it. After all, I think that if AGI is really just around the bend, then we don't have to worry about programming jobs: they probably won't exist. But if it's not, then these tools will probably continue to improve at a rate that makes what we have today irrelevant. I believe that will happen with all of the image generation knowledge people are accumulating with Stable Diffusion derived models. That said, forgetting all of the AI doom or hype, this seems frankly incredibly cool. I haven't managed to find a great use case for AI code generation where it hasn't failed miserably (except for minor boilerplate uses, like with IntelliJ's LLM auto complete for Java), but actually, generating FFI libraries seems like a pretty kickass use case for automation. I dig this. I will definitely try it.
- XCSme 2y ago
  > we don't have to worry about programming jobs Maybe not writing the code itself, but creating a product/business still requires deciding how things will work, what technologies to use, what's the public API, etc. So instead of writing the code to do it, you still need someone to ask the AI to do it: "create a to-do list with login system, that has e2e encrpytion and stores the data in a NoSQL database", etc. So you still need some programming knowledge to use it, otherwise you don't know what to ask for.
  - chii 2y ago
    > otherwise you don't know what to ask for there's a perfectly working LLM for which you can query the answer! Ask it to tell you what are the important aspects of product XYZ.
ploynog 2y ago
With LLMs I am in this strange place where I read all of these amazing things that they supposedly all can do. And I have no doubt in my mind that they probably can. And then I ask ChatGPT a simple question such as: Here is a logic puzzle that I need some help solving: Samantha is a girl and has two brothers and four sisters. Alex is a man and also one of Samantha's brothers. How many brothers and sisters does Alex have? Assume that Samantha and Alex share all siblings. And I get back a very well written, multi-step response that leaves no doubt in anyones mind that: To solve this logic puzzle: Samantha has 2 brothers and 4 sisters. This means there are 7 children in total (Samantha, her 2 brothers, and her 4 sisters). Alex is one of Samantha's brothers. Since Samantha and Alex share all siblings, Alex has: 1 brother (the other brother besides himself). 4 sisters. Final Answer: Alex has 1 brother and 4 sisters. Maybe it's like with Apple and I am using it wrong. To get back to the "intern"-comparison. I could usually tell when an intern was struggling, there just were human telltale signs. When AI is wrong, it still presents its results with the confidence of someone who is extremely deep in the Dunning-Kruger hole but can still write like a year-long expect on the topic.
- doctoboggan 2y ago
  Have you tried asking it to do something useful rather than ask it to solve gotcha word problems? > I read all of these amazing things that they supposedly all can do. You seem to be implying people are confused (or lying?) about the things they are able to get LLMs to do. If you give it an honest effort to solve some real problems you are facing then you may be able to speak with more authority. Often it comes down to prompting skill. Try to read about different prompting approaches as that may help you. In general, you need to be specific about what you need, and you need to give all relevant details. Like the post author said, treat it like a junior programmer or an intern.
  - d0mine 2y ago
    It is basic reasoning. How do you expect it to produce useful programs with any consistency without it?
wobblyasp 2y ago
I'm confused. Assistants are so easy to use yet we should drop everything to "learn"/"adopt" them? Why not just wait until they're not complete dumpster fires then start using them?
- wobblyasp 2y ago
  > This wasn't something that existed, it wasn't regurgitating knowledge from Stackoverflow. It was inventing/creating something new. Except it was. It wasn't regurgitating the exact answer it gave you, but it was using the collective knowledge of StackOverflow/other code to generate the solution. Give your head a shake.
  - monsieurbanana 2y ago
    Of all the (valid) downsides of LLMs, this is maybe the weakest one. I'm not even sure what would qualify as "new" for you. Anything I've ever done at work could have been pieced together from StackOverflow. Anything you have ever done can most probably be pieced together from StackOverflow as well.
    - wobblyasp 2y ago
      I sincerely doubt it; but I also work in an Org that has highly internal code with none to poor documentation. Also, I never said it was a "downside". I'm simply stating that the author is exaggerating what the LLM is doing. It isn't creating novel code. I used LLMs all the time to spit out boilerplate when it makes sense.
  - portaouflop 2y ago
    Isn’t that what most developers do? Few are really inventing something new, afaict almost everyone is plugging together existing solutions to solve the same old use cases
    - wobblyasp 2y ago
      Again; made no comment about what people do day to day. Specifically commenting on the authors praise of the LLM doing "novel" work.
burkaman 2y ago
Does the library work? Also, this is an incredible achievement, but I don't understand this statement: > This wasn't something that existed, it wasn't regurgitating knowledge from Stackoverflow. It was inventing/creating something new. I mean you literally told it to copy an existing library. I understand the Haskell code is novel, but translation is not the same as inventing.
- echelon 2y ago
  > this is an incredible achievement If it was real, why aren't all the unicorns in this space worth $100B already?
  - f1shy 2y ago
    We could really make a valuation, considering that it can replace X % of developers… I think 100B is even low!
    - echelon 2y ago
      > I think 100B is even low! It could be. It also depends on whether there is a moat around the tech or if we'll have a dozen fungible clones. But I'd certainly expect more signal if these models could do as advertised.
- bilekas 2y ago
  Yeah, I have a problem with general statements like that ". It was inventing/creating something new." This simply is not the case as far as we know.. I'm yet to be convinced that anything under the hood is more than a clever predictive generator for now. It can appear to do really impressive things, but that's only while it's behaving correctly. All it takes is one bad line and the snowball effect of the problem is in motion. Lastly, it is true : > "the better the type system of the programming language and verbosity of compiler errors the harder LLM's go" The LLM has the best opportunity to succeed in this case. Nice to have but inventing, I doubt.
skywhopper 2y ago
It’s impressive, but I’m not sure I’d characterize a Haskell wrapper around C APIs as “something new that never existed before”.
- f1shy 2y ago
  Anything that is already in another languages, is nothing new, is just a translation.
alganet 2y ago
Making a wrapper is commodity knowledge (there is a ton of wrappers out there as examples, tons of literature about it). It's more about hard work than intelligence. Eventually, AI (as it is today) will run out of commoditizable knowledge. It is impressive, but there is a man inside the machine writing wrappers and talking about them to allow this magic to happen.
- f1shy 2y ago
  In fact there are already programs (w/o AI) that do that (wrappers) . Is called a groveller.
- ben_w 2y ago
  > It's more about hard work than intelligence I've seen people dismiss Musk, saying that it's not intelligence, it was luck. I've seen people dismiss intelligence in the general domain of "being successful", saying "grit" (or sometimes "common sense") is more important. Before Deep Blue, Chess was seen as something that needed human intuition; after, it was "just brute force search, but Go, now that's a real sign of intelligence"… until AlphaGo, after which that too was no longer claimed. "Kilo-girl-hours" used to be a measure of compute, back when "computer" was a profession rather than an appliance. > It is impressive, but there is a man inside the machine writing wrappers and talking about them to allow this magic to happen. https://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_giants https://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_g... And, to borrow a quote: If you immediately know the candlelight is fire, then the meal was cooked a long time ago. By this I mean: If an AI only counts as "intelligent" when it can reproduce everything in the entire path-history leading up to modern civilisation without dependence on training data (the way AlphaZero can specifically in the domain of Go), then point at which the AI bested us is comprehensively behind us.
  - alganet 2y ago
    It's the mechanical turk (not Amazon's, the medieval one) all over again. Instead of a small dude inside the machine, there is training data. Instead of pulls and levers connected to chess pieces, we have vectors and weights. If we scaled the turk to have millions of people inside, it would appear to be intelligent as well. I don't need it to reproduce everything. Just show me one convincing non-anectodal evidence that this is not another mechanical turk.
XCSme 2y ago
The problem with Windsurf is that it works great until it doesn't. And the time you spend checking and fixing its mistakes is longer than it would take for you to implement that yourself. Some of those cases are: * Sometimes the Accept changes button doesn't work * Sometimes it DELETES a lot of your code, without you noticing * Sometimes it duplicates code * Sometimes it gets stuck in a loop trying to fix an error, or it can't fix trivial errors * Sometimes it suddenly can not access your files. * Sometimes it adds "// ...rest of code goes here" comments instead of writing the code. In my experience, the best use-cases for AI assistants/LLMs are: * Generate boilerplate/scaffold for a new project * Refactor code (rename variables, functions, or slightly alter functionality like use "while loop instead of for") * Quick way to find the name/signature of an API/function without having to google the docs of that library (e.g. "add a new React MaterialUI list") I have used it for about 2 months, but in my experience it actually gets worse with time, not better. The problem now doesn't seem to be with the actual writing of code, but with the UI and how it applies the changes.
- ndileas 2y ago
  I definitely don't need an AI to write // TODO make this work. That's what I'm for!
  - XCSme 2y ago
    If this is what Claude was trained on. Maybe they could filter this out from the training data. Or somehow detect if it writes something like this, and do one more chain-of-thought expansion on it.
  - AnimalMuppet 2y ago
    I want to see an AI write // drunk - fix later.
- f1shy 2y ago
  Yeah. Is basically like claiming that current autopilot/automation in planes make pilots superfluous. Basically every part of the flight can/could be completely automated today, but still you need those 2 guys, for the event that something goes wrong. Now, before someone comes with a snarky “like in Korea”: that was one of thousands emergencies in the last couple of years, where that 2 humans made the difference. May some day need no pilots? Yes. Not today, no tomorrow.
IncreasePosts 2y ago
What adaptation is actually necessary for competent software developers? If it is as easy as writing what you want the llm to do, I'm pretty sure any competent software developer can learn that within a few days. And the necessity of precise prompting techniques will quickly diminish over time.
- jckahn 2y ago
  We'll need to adapt to lower salaries
  - f1shy 2y ago
    Maybe same salary, more output required, like it’s been when new technology allows for more/better work to be done in the same time.
  - Etheryte 2y ago
    I'm not convinced this is going to happen to competent engineers. I've done my fair share of consulting gigs and some of the best money was in fixing spaghetti that was so long gone that even the original team behind it struggled to move the needle. My gut feel is that with LLMs, this kind of work is going to be even more valuable than before.
    - ben_w 2y ago
      Today, yes absolutely. I won't bet on how quickly or slowly that will change, in part because I want it to be a slow change so I don't have to worry about learning a replacement trade.
  - wil421 2y ago
    Wasn’t there a prompt engineer salary posted on HN a while back for like $350k?
- mixmastamyk 2y ago
  Agreed, however devs are not allowed to learn things until after an interview. Miss a question during and don’t get hired, fixed-mindset style.
robomartin 2y ago
In some ways, refusing to use LLM's to assist with coding is like that funny commercial where they show a guy trimming grass one blade at a time using a nail clipper. Using LLM's responsibly is a massive force multiplier. You still have to know what you are doing or the result could be in a range between not maintainable to disastrous. In my experiments with LLM's one of the most obvious issues is project structure and organization, particularly in the context of future objectives. It is way too easy to have an LLM go in circles when analyzing ideas for project structures. I have seen them propose layouts that, while workable, are far from ideal. The same applies to code. It can write usable code faster than a human. However, and, again, in my experience, you are constantly refactoring the results. In all, this is a new tool and, yes, it is useful. It's amazing to me considering the idea that the whole thing is based on guessing the next token. It doesn't really understand anything, yet, you'd be hard-pressed to prove this to those who don't know how we got here. I've had a few of those conversations with non-coders using ChatGPT for a range of tasks. It's magic.
- chikere232 2y ago
  I'd much rather write my own code while thinking through the implications and pitfalls of it than have a virtual junior coder vomit out some code I have to check carefully. If I want to invest time in fixing some junior developer's probably broken code, I'd much rather do it with a real junior developer who has the potential to learn over time and become a not junior developer
  - robomartin 2y ago
    Well, this is likely going to be a polarizing topic for a while. I'll give you an example of something that I moved to LLM code generation. I have used Excel for probably more than two decades to generate certain types of code structures that are simply tedious to both write by hand and also maintain. One such example are lookup table definitions for state machines. Using Excel for this, once setup, makes it fast and infinitely more maintainable. Today, I can do this with LLM's in a heartbeat. The code is good and it is easy to maintain. Over the years I have written custom code generation tools for the same reason. Sticking with the state machine example, if you have 100 states and each state requires entry, during and exit handler functions, well, you have to take that lookup table and write 300 functions. In a language like C this means both the declaration and implementation skeleton. LLMs are good for this as well. Like I said, it's a tool in the toolbox. It can be used a million different ways.
the_arun 2y ago
> It's currently really hard for newbies to break into the software industry as it's still recovering from the en-mass layoffs two years ago. With coding assistants this good, now, and getting better daily I'm left wondering... This can definitely help with some of the tech debts. But I wonder how do we deal with changing requirements? Use Cases? Experiments & new directions from Product? Software has a life after building.
golly_ned 2y ago
This is a tired trope, that engineers who don’t use software assistants will be left in the dust and need to hop onboard asap. It’s really easy to learn how to use software assistants. Those engineers can hop on or off any time. It’s really hard to build up fundamental engineering skills.
- mouse_ 2y ago
  Thanks for putting this better than I could have.
- chii 2y ago
  Not really. Imagine if it was driving a truck instead. Anyone, realistically, could've learnt to do it. But if you don't already know how to drive one, you're never going to get hired as one. And by the time the truck driving jobs are the only jobs there is left, it's a tad late - you're already behind everyone else who's got some years of experience.
  - f1shy 2y ago
    I think it is a bad examples. It would be like: new trucks are automatic, while current manual. If you don’t learn to drive automatic, you can do that anytime, no problem, as long as you are proficient in driving manual.
- f1shy 2y ago
  I would argue even the opposite. And that is the reason I resist to using them (assistants). Just as people using GPS are loosing the orientation abilities, I’m afraid that excesive use of assistants may deteriorate our abilities.
  - uludag 2y ago
    To further this point, while the vast majority of people could go without such skills, there are jobs where such skills are valuable. So developing skills pretty much everyone has given up on allow one to carve a unique niche for themselves.
mouse_ 2y ago
Listen close, please. The end goal of AI coding assistants is not > convert this rust library at https://github.com/RustAudio/cpal/tree/master https://github.com/RustAudio/cpal/tree/master to a haskell library using ghc2024. The end goal is something more like > Build me a website where users can make and share a link to a text document like a shopping list and edit it collaboratively This guy thinks LLMs are so great, but if he grew up with LLMs, not only would he not have the skill set to competently ask the LLM to produce that output, he wouldn't have any idea the output he's trying to produce. OpenAI, Google, Microsoft are not trying to sell the idea of helping out your senior engineers. They are trying to sell the idea that any of your interns could be senior engineers, so that you no longer have to pay for expensive senior engineers.
- fragmede 2y ago
  > Build me a website where users can make and share a link to a text document like a shopping list and edit it collaboratively Between a human and a current-day LLM that would take a day, tops, to implement.
deadbabe 2y ago
The only advantage AI code assistants have over competent humans is speed in generating code. But speed doesn’t matter. When code is going to live for several years, no one will care if it took minutes to create vs a week. If you are an incompetent human, you might never be able to generate the same code some LLM generates. This will cause you to sing it’s praises and worship the LLM as your savior. In general, there is a correlation between weak developers and how hyped they are by LLM coding assistants.
- AnimalMuppet 2y ago
  > When code is going to live for several years, no one will care if it took minutes to create vs a week. No, but... if it took minutes instead of a week, that leaves you the rest of the week to create N more things. That matters, and may still matter in several years.
  - deadbabe 2y ago
    There are not N more things to create. It’s better to focus on making the things you do make as good as possible. And even if there were N more things, you’re creating NxN maintenance issues at an overwhelming rate.
2099miles 2y ago
TLDR: ai can be helpful, anyone who doesn’t use it hasn’t realized it’s helpful, SWE’s who disagree “are frankly not gonna make it” Review: great fun story, I agree with the first part of the take and I like the post and I like some ai tools, I disagree with the last bit. There are really good SWE’s who are in spaces where ai is not that useful. SWE is too big now, it’s too vague, ai doesn’t apply to all. You don’t need to use ai to survive, but I agree you should try it out and see before dismissing it. And retry it every so often cuz it’s developing and changing.
ixtli 2y ago
Binary, polarizing language for clicks. I've had a few mild versions of the "oh fuck" moment they're talking about in the past 1-2 years but outside of some specific cases (writing test data generators, scaffolding, etc.) LLMs havent massively changed the way I do things. They're cool and all but, c'mon. I've been programming for 25 years, 15 of which were professional. This is a majorly creative job and while I'm down for Butlarian Jihad as much as the next guy you need to actually have a machine which can be self-sufficiently creative to start talking about it.
karl_gluck 2y ago
Thanks for this -- have been using Cody a lot and just tried Windsurf on my hobby project. So far it seems immediately like a step up. Has anyone paid for it? The free version is doing good work.
ivjw 2y ago
This is no ingenious feat by any standard, except probably for someone in the Dunning–Kruger dip. https://gwern.net/creative-benchmark https://gwern.net/creative-benchmark I can't wait to see if AI can get past its centripetal plateau.
misiti3780 2y ago
what HN post were they referring to ?
bArray 2y ago
> N period on from now, software engineers who haven't adopted or started exploring software assistants, are frankly not gonna make it. Engineering organizations are right now are split between those who have had that "oh fuck" moment and are leaning into software assistants and those who have not. I'm looking at coders coming out of University who chat-GPT'd every coursework and they can't program their way out of a paper bag. I think what is being lost is the ability to solve non-chat-GPT-able problems. I'm having my 'oh fuck' moment, but I'm looking at the new coders. Maybe I am just super behind the progress train, and that programmers will become a thing of the past. Maybe we can setup some adversarial LLM training scenario and have LLMs that reliably code better than humans. My concern remains valid though, that there is now a generation being created that turns to an LLM rather than reasoning about a problem [1]. [1] https://www.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_sisters_use_of_chatgpt_for_homework_is/ https://www.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_...
neilv 2y ago
> Then took my kids down to the local pool. When I got back, I had a fully functional Haskell library with autogenerated C bindings, FFI to CoreAudio and my jaw was on the ground. With a tricky copyright declaration and licensing. A mechanical translation of Rust code under the copyright of ___? Maybe also involving stealing bits of Haskell code without attribution from material copyrights of ___, ___, and ___? Cleanroom engineering is a thing when it comes to "make me one like that, except I have copyright of it". The LLM laundering approach isn't that. Ripping off open source code isn't new. Various companies and individuals would do it. Occasionally they got caught. Microsoft/GitHub had to reassure companies that cared about LLM copyright violations, by indemnifying them. I guess so that open source projects ripped off would have to face the legal resources of Microsoft.
- coldpie 2y ago
  It turns out copyright doesn't apply if you violate all of it at the same time. Weird trick.
  - formerly_proven 2y ago
    Reminds me of the old "if you owe the bank a million dollars, you're in trouble, if you owe them a billion dollars, they're in trouble" bit.
- Joker_vD 2y ago
  All this AI-generated stuff really should just go into the public domain automatically. That'd immediately not only resolve any possible copyright disputes but also make AI usage much, much less appealing for the large orgs.
  - neilv 2y ago
    > All this AI-generated stuff really should just go into the public domain automatically. That'd immediately not only resolve any possible copyright disputes [...] I can't just take something of yours, and make it public domain.
kennywinker 2y ago
> convert this rust library … > This wasn't something that existed, it wasn't regurgitating knowledge from Stackoverflow. It was inventing/creating something new. But it was something that existed… it took a rust library and converted it to haskell. That’s not invention, that’s conversion
adamontherun 2y ago
I've found that having the coding assistant do large tasks like this unsupervised is the worst way to use it. Asking the assistant to do narrowly defined tasks and then checking the work is the only reliable way. I've been using Cursor since the summer and wrote up a few tips here https://betaacid.co/blog/cursor-dethrones-copilot https://betaacid.co/blog/cursor-dethrones-copilot
ryandrake 2y ago
It would never have occurred to me to ask an LLM to convert an entire library from one language to the other, with tests, and everything. I've started to think of them merely as smarter auto-corrects, like for when you forget the syntax or which order a functions arguments go in, you can just use copilot's inline chat to write "Convert this array of tuples to a dict" and it saves you the 20 seconds it takes to look up the syntax. Or "See above line where I deserialized a uint32 from a binary file. Do the same thing for all the other fields in the foobar struct". I just never even thought to ask it to simply build my whole app for me.
- disgruntledphd2 2y ago
  I've tried the entire app thing once seriously, and didn't get great results. In other cases, it's super helpful with smaller problems like parse this data out of this example of HTML. But I do agree that the code is pretty crap in most cases. I feel like if I was seriously doing this then I'd be mostly refactoring the generated code and writing tests.
uludag 2y ago
So I've been doing a lot of thinking and I've gone through a rollercoaster of feelings concerning AI and becoming redundant. Recently though, I've had a different "oh fuck" moment: what if the period of general global prosperity is coming to an end, that Fukuyama's end of history is coming to an end, that climate change won't come under control. Maybe I'll look back and wish that I could be a redundant SWE in a 2010s economy. With such a backdrop, how scary could AI really be?
- ben_w 2y ago
  > With such a backdrop, how scary could AI really be? On a personal level, sure. On a society-wide level… Even if the AI doesn't improve, consider that there are people who think the answers to every question can be found in the actual literal Bible, and then ask what such a personality would do when there's a small box that can opine confidently about basically everything and is right often enough to be competitive with people who stay in full time education until age 19 or 20. Or, if the Bible analogy doesn't appeal, consider how it took until the Renaissance for European society to seriously attempt to go past that of classical Rome and Greece.
- JohnMakin 2y ago
  > that climate change won't come under control. All signs point to this, or it's already reached a tipping point - certainly nothing we are already doing is reducing total carbon output, just slowing its acceleration. There was that one weird year in 2020 where emissions went down as the entire world stopped commuting - regardless of what you think about the realistic ability of new/unproven tech and regulations will be at preventing 3+ celsius change from industrial average by 2100 (catastrophe of biblical proportions) - if AI is indeed as critical to the economy/humanity's future as its proponents (marketers) say, the enormous amount of power and other resources that often don't get factored in, like the massive amounts of increasingly scarce water to cool the massive datacenters - will certainly make such efforts at reducing emissions extraordinarily unlikely, if not impossible, short of converting our entire power grid to sustainable energy, which there seems to be little to no political will for. It's grim, I'm extremely skeptical of optimism at this point on this particular topic. I am bracing for catastrophe at some point in my life (looking at the LA fires very near me, I would argue it's already here) and think the world governments would be wise to do so as well rather than pretend we're just going to magically figure it out at the last possible second. Not even to mention there are a lot of people, including people in power, who don't even believe climate change is happening at all. We're living in Don't Look Up.
TheBozzCL 2y ago
Dunno, man. I'm using Claude 3.5 via Cody on IntelliJ for work, or via Kagi for other cases. When it works, it works great - especially for easy, well-understood things like boilerplate code or the typical simple tasks that I don't bother memorizing because they were already available in search engines anyway. For anything more complex or esoteric, LLMs shit the bed pretty quickly. A recent example: I needed to implement a particular setup for an Argo CD ApplicationSet (default values plus a per-stage override, at the generator level). Every single suggestion by the LLM was wrong. I decided to dig into the documentation because I assumed there was no way this wasn't possible, and lo and behold - matrix generators are a thing, and my exact use case was an example in the doc. I asked the LLM about it and it knew what they were, so it clearly had indexed it before. It's far from the only issue - the most common one is the below-average quality of code in some cases, with plenty of wrong implementations strictly due to hallucinations. Then Cody has its own issues on top of that - not applying changes correctly is the most common one. Put that together with engineers that are in a rush or are using the LLM as a crutch... and I can see a future where devs with little experience can put together huge codebases that will be as brittle as a house of cards.
- fragmede 2y ago
  Which sounds pretty great because you could make a whole career off of being the contractor that comes in to fix it when the jr devs who only know LLM prompting can't fix it.
  - TheBozzCL 2y ago
    lol same kinda vibe as Fortran devs right now
mirawelner 2y ago
There is a psychology paper waiting to be written about humans perceiving intellect as the ability to communicate knowledge convincingly and thus being amazed by LLMs. I’m by no means immune to it
- ixtli 2y ago
  Its been a long time since i've been amazed by an HN comment in a positive way. This is a really, really good way of putting it. I'd go further: humans are willing to forgive shockingly grievous intellectual crimes (c.f.: hallucination, dangerous reasoning errors, etc.) if they are clearly communicated in the way you describe.
ben_w 2y ago
> N period on from now, software engineers who haven't adopted or started exploring software assistants, are frankly not gonna make it. Engineering organizations are right now are split between those who have had that "oh fuck" moment and are leaning into software assistants and those who have not. Mine was InstructGPT, a few months before the public release of ChatGPT. Everything that followed was an unsurprising extrapolation of what I saw in that moment. Question is, how far will it continue? That I cannot say. At least a factor of 3 from foreseeable compute improvements… unless a war is started over the manufacture of compute. But also, Koomey's law (energy) is slower than Moore's (unit cost + feature size), and if one presupposes that manufacture of compute is unbounded, then we rapidly hit limits of manufacture of power sources for the compute, and that in turn causes huge economic issues well before there's enough supply to cause mass unemployment… unless there's a lot of huge algorithmic improvements waiting to happen, because that might be enough to skip electricity shortages and go straight to "minimum and cheapest calories to keep human alive are more expensive than the electricity to run the servers that produce economic value equal to the most productive human". I have no confidence in any forecast past the end of 2028.
hfdersa 2y ago
If the output is so amazing why leave out a link to the generated library? Why leave out an explanation of why you needed, or how you’ll use, this Haskell audio api wrapper? In the absence of these this just feels like resume slop. If it is, do recruiters see “I asked a thing to do the work for me” as desirable in a potential hire? The original library’s license is Apache 2.0. Does that have any bearing on the authors opinion on sharing this generated code?
deleted 2y ago
[deleted]

88 points by ghuntley 2y ago

My experience is sometimes it works amazingly well like you say, and sometimes it doesn't. LLMs are great at translations, like "convert this SQL to JooQ" or "convert this Chinese text to English". If you were going from Haskell -> Rust it might have trouble fighting with the borrow checker, or it might not if your memory usage patterns were straightforward or you can "RC all the things". Haskell's a particularly good target because less state means less complexity thinking about state.

ghuntley 2y ago
So very tempting to put it to the task. Any takers? Try converting https://hackage.haskell.org/package/megaparsec https://hackage.haskell.org/package/megaparsec to rust.
- almostdeadguy 2y ago
  Just tried this using similar prompting to the original and it required several rounds of telling it about compiler errors before generating something that looked suspiciously like a _very_ basic version of "nom", without any of the state/position tracking or the nice error model in megaparsec. I suspect anyone talking about instances where doing something like this "just works" is a grifter/aspiring AI influencer.
BalinKing 2y ago
FWIW even with machine translations (on GPT-4o) I do get occasional hallucinations. Like, it'll add an additional sentence or relative clause that wasn't in the original. It'll still make sense in context, so the overall meaning is the same, but it's not what I'd expect from, say, a human translator. (For context, I know enough of both languages—English and Japanese—to be able to verify this myself.) It doesn't happen very often—maybe 1 out of 50 times?—but it's definitely a somewhat regular occurrence. And ofc, it's not just a result of the fact that every language is different and so the same meaning will need to be expressed differently—it's actually hallucinating bona fide content.
- BalinKing 2y ago
  Oh, and IME it doesn't ask clarifying questions that a human translator would know are necessary (at least without explicit prompting to do so, which I admittedly haven't tried). So when translating from a high-context language like Japanese, it'll come up with a translation that works in some contexts but is meaningless in others. I figure this is related to the overconfidence issue that's prevalent with (current) LLMs.

jchw 2y ago

I don't care that much for the commentary about who will or will not make it. After all, I think that if AGI is really just around the bend, then we don't have to worry about programming jobs: they probably won't exist. But if it's not, then these tools will probably continue to improve at a rate that makes what we have today irrelevant. I believe that will happen with all of the image generation knowledge people are accumulating with Stable Diffusion derived models. That said, forgetting all of the AI doom or hype, this seems frankly incredibly cool. I haven't managed to find a great use case for AI code generation where it hasn't failed miserably (except for minor boilerplate uses, like with IntelliJ's LLM auto complete for Java), but actually, generating FFI libraries seems like a pretty kickass use case for automation. I dig this. I will definitely try it.

XCSme 2y ago
> we don't have to worry about programming jobs Maybe not writing the code itself, but creating a product/business still requires deciding how things will work, what technologies to use, what's the public API, etc. So instead of writing the code to do it, you still need someone to ask the AI to do it: "create a to-do list with login system, that has e2e encrpytion and stores the data in a NoSQL database", etc. So you still need some programming knowledge to use it, otherwise you don't know what to ask for.
- chii 2y ago
  > otherwise you don't know what to ask for there's a perfectly working LLM for which you can query the answer! Ask it to tell you what are the important aspects of product XYZ.

ploynog 2y ago

With LLMs I am in this strange place where I read all of these amazing things that they supposedly all can do. And I have no doubt in my mind that they probably can. And then I ask ChatGPT a simple question such as: Here is a logic puzzle that I need some help solving: Samantha is a girl and has two brothers and four sisters. Alex is a man and also one of Samantha's brothers. How many brothers and sisters does Alex have? Assume that Samantha and Alex share all siblings. And I get back a very well written, multi-step response that leaves no doubt in anyones mind that: To solve this logic puzzle: Samantha has 2 brothers and 4 sisters. This means there are 7 children in total (Samantha, her 2 brothers, and her 4 sisters). Alex is one of Samantha's brothers. Since Samantha and Alex share all siblings, Alex has: 1 brother (the other brother besides himself). 4 sisters. Final Answer: Alex has 1 brother and 4 sisters. Maybe it's like with Apple and I am using it wrong. To get back to the "intern"-comparison. I could usually tell when an intern was struggling, there just were human telltale signs. When AI is wrong, it still presents its results with the confidence of someone who is extremely deep in the Dunning-Kruger hole but can still write like a year-long expect on the topic.

doctoboggan 2y ago
Have you tried asking it to do something useful rather than ask it to solve gotcha word problems? > I read all of these amazing things that they supposedly all can do. You seem to be implying people are confused (or lying?) about the things they are able to get LLMs to do. If you give it an honest effort to solve some real problems you are facing then you may be able to speak with more authority. Often it comes down to prompting skill. Try to read about different prompting approaches as that may help you. In general, you need to be specific about what you need, and you need to give all relevant details. Like the post author said, treat it like a junior programmer or an intern.
- d0mine 2y ago
  It is basic reasoning. How do you expect it to produce useful programs with any consistency without it?

wobblyasp 2y ago

I'm confused. Assistants are so easy to use yet we should drop everything to "learn"/"adopt" them? Why not just wait until they're not complete dumpster fires then start using them?

wobblyasp 2y ago
> This wasn't something that existed, it wasn't regurgitating knowledge from Stackoverflow. It was inventing/creating something new. Except it was. It wasn't regurgitating the exact answer it gave you, but it was using the collective knowledge of StackOverflow/other code to generate the solution. Give your head a shake.
- monsieurbanana 2y ago
  Of all the (valid) downsides of LLMs, this is maybe the weakest one. I'm not even sure what would qualify as "new" for you. Anything I've ever done at work could have been pieced together from StackOverflow. Anything you have ever done can most probably be pieced together from StackOverflow as well.
  - wobblyasp 2y ago
    I sincerely doubt it; but I also work in an Org that has highly internal code with none to poor documentation. Also, I never said it was a "downside". I'm simply stating that the author is exaggerating what the LLM is doing. It isn't creating novel code. I used LLMs all the time to spit out boilerplate when it makes sense.
- portaouflop 2y ago
  Isn’t that what most developers do? Few are really inventing something new, afaict almost everyone is plugging together existing solutions to solve the same old use cases
  - wobblyasp 2y ago
    Again; made no comment about what people do day to day. Specifically commenting on the authors praise of the LLM doing "novel" work.

burkaman 2y ago

Does the library work? Also, this is an incredible achievement, but I don't understand this statement: > This wasn't something that existed, it wasn't regurgitating knowledge from Stackoverflow. It was inventing/creating something new. I mean you literally told it to copy an existing library. I understand the Haskell code is novel, but translation is not the same as inventing.

echelon 2y ago
> this is an incredible achievement If it was real, why aren't all the unicorns in this space worth $100B already?
- f1shy 2y ago
  We could really make a valuation, considering that it can replace X % of developers… I think 100B is even low!
  - echelon 2y ago
    > I think 100B is even low! It could be. It also depends on whether there is a moat around the tech or if we'll have a dozen fungible clones. But I'd certainly expect more signal if these models could do as advertised.
bilekas 2y ago
Yeah, I have a problem with general statements like that ". It was inventing/creating something new." This simply is not the case as far as we know.. I'm yet to be convinced that anything under the hood is more than a clever predictive generator for now. It can appear to do really impressive things, but that's only while it's behaving correctly. All it takes is one bad line and the snowball effect of the problem is in motion. Lastly, it is true : > "the better the type system of the programming language and verbosity of compiler errors the harder LLM's go" The LLM has the best opportunity to succeed in this case. Nice to have but inventing, I doubt.

skywhopper 2y ago

It’s impressive, but I’m not sure I’d characterize a Haskell wrapper around C APIs as “something new that never existed before”.

f1shy 2y ago
Anything that is already in another languages, is nothing new, is just a translation.

alganet 2y ago

Making a wrapper is commodity knowledge (there is a ton of wrappers out there as examples, tons of literature about it). It's more about hard work than intelligence. Eventually, AI (as it is today) will run out of commoditizable knowledge. It is impressive, but there is a man inside the machine writing wrappers and talking about them to allow this magic to happen.

f1shy 2y ago
In fact there are already programs (w/o AI) that do that (wrappers) . Is called a groveller.
ben_w 2y ago
> It's more about hard work than intelligence I've seen people dismiss Musk, saying that it's not intelligence, it was luck. I've seen people dismiss intelligence in the general domain of "being successful", saying "grit" (or sometimes "common sense") is more important. Before Deep Blue, Chess was seen as something that needed human intuition; after, it was "just brute force search, but Go, now that's a real sign of intelligence"… until AlphaGo, after which that too was no longer claimed. "Kilo-girl-hours" used to be a measure of compute, back when "computer" was a profession rather than an appliance. > It is impressive, but there is a man inside the machine writing wrappers and talking about them to allow this magic to happen. https://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_giants https://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_g... And, to borrow a quote: If you immediately know the candlelight is fire, then the meal was cooked a long time ago. By this I mean: If an AI only counts as "intelligent" when it can reproduce everything in the entire path-history leading up to modern civilisation without dependence on training data (the way AlphaZero can specifically in the domain of Go), then point at which the AI bested us is comprehensively behind us.
- alganet 2y ago
  It's the mechanical turk (not Amazon's, the medieval one) all over again. Instead of a small dude inside the machine, there is training data. Instead of pulls and levers connected to chess pieces, we have vectors and weights. If we scaled the turk to have millions of people inside, it would appear to be intelligent as well. I don't need it to reproduce everything. Just show me one convincing non-anectodal evidence that this is not another mechanical turk.

XCSme 2y ago

The problem with Windsurf is that it works great until it doesn't. And the time you spend checking and fixing its mistakes is longer than it would take for you to implement that yourself. Some of those cases are: * Sometimes the Accept changes button doesn't work * Sometimes it DELETES a lot of your code, without you noticing * Sometimes it duplicates code * Sometimes it gets stuck in a loop trying to fix an error, or it can't fix trivial errors * Sometimes it suddenly can not access your files. * Sometimes it adds "// ...rest of code goes here" comments instead of writing the code. In my experience, the best use-cases for AI assistants/LLMs are: * Generate boilerplate/scaffold for a new project * Refactor code (rename variables, functions, or slightly alter functionality like use "while loop instead of for") * Quick way to find the name/signature of an API/function without having to google the docs of that library (e.g. "add a new React MaterialUI list") I have used it for about 2 months, but in my experience it actually gets worse with time, not better. The problem now doesn't seem to be with the actual writing of code, but with the UI and how it applies the changes.

ndileas 2y ago
I definitely don't need an AI to write // TODO make this work. That's what I'm for!
- XCSme 2y ago
  If this is what Claude was trained on. Maybe they could filter this out from the training data. Or somehow detect if it writes something like this, and do one more chain-of-thought expansion on it.
- AnimalMuppet 2y ago
  I want to see an AI write // drunk - fix later.
f1shy 2y ago
Yeah. Is basically like claiming that current autopilot/automation in planes make pilots superfluous. Basically every part of the flight can/could be completely automated today, but still you need those 2 guys, for the event that something goes wrong. Now, before someone comes with a snarky “like in Korea”: that was one of thousands emergencies in the last couple of years, where that 2 humans made the difference. May some day need no pilots? Yes. Not today, no tomorrow.

IncreasePosts 2y ago

What adaptation is actually necessary for competent software developers? If it is as easy as writing what you want the llm to do, I'm pretty sure any competent software developer can learn that within a few days. And the necessity of precise prompting techniques will quickly diminish over time.

jckahn 2y ago
We'll need to adapt to lower salaries
- f1shy 2y ago
  Maybe same salary, more output required, like it’s been when new technology allows for more/better work to be done in the same time.
- Etheryte 2y ago
  I'm not convinced this is going to happen to competent engineers. I've done my fair share of consulting gigs and some of the best money was in fixing spaghetti that was so long gone that even the original team behind it struggled to move the needle. My gut feel is that with LLMs, this kind of work is going to be even more valuable than before.
  - ben_w 2y ago
    Today, yes absolutely. I won't bet on how quickly or slowly that will change, in part because I want it to be a slow change so I don't have to worry about learning a replacement trade.
- wil421 2y ago
  Wasn’t there a prompt engineer salary posted on HN a while back for like $350k?
mixmastamyk 2y ago
Agreed, however devs are not allowed to learn things until after an interview. Miss a question during and don’t get hired, fixed-mindset style.

robomartin 2y ago

In some ways, refusing to use LLM's to assist with coding is like that funny commercial where they show a guy trimming grass one blade at a time using a nail clipper. Using LLM's responsibly is a massive force multiplier. You still have to know what you are doing or the result could be in a range between not maintainable to disastrous. In my experiments with LLM's one of the most obvious issues is project structure and organization, particularly in the context of future objectives. It is way too easy to have an LLM go in circles when analyzing ideas for project structures. I have seen them propose layouts that, while workable, are far from ideal. The same applies to code. It can write usable code faster than a human. However, and, again, in my experience, you are constantly refactoring the results. In all, this is a new tool and, yes, it is useful. It's amazing to me considering the idea that the whole thing is based on guessing the next token. It doesn't really understand anything, yet, you'd be hard-pressed to prove this to those who don't know how we got here. I've had a few of those conversations with non-coders using ChatGPT for a range of tasks. It's magic.

chikere232 2y ago
I'd much rather write my own code while thinking through the implications and pitfalls of it than have a virtual junior coder vomit out some code I have to check carefully. If I want to invest time in fixing some junior developer's probably broken code, I'd much rather do it with a real junior developer who has the potential to learn over time and become a not junior developer
- robomartin 2y ago
  Well, this is likely going to be a polarizing topic for a while. I'll give you an example of something that I moved to LLM code generation. I have used Excel for probably more than two decades to generate certain types of code structures that are simply tedious to both write by hand and also maintain. One such example are lookup table definitions for state machines. Using Excel for this, once setup, makes it fast and infinitely more maintainable. Today, I can do this with LLM's in a heartbeat. The code is good and it is easy to maintain. Over the years I have written custom code generation tools for the same reason. Sticking with the state machine example, if you have 100 states and each state requires entry, during and exit handler functions, well, you have to take that lookup table and write 300 functions. In a language like C this means both the declaration and implementation skeleton. LLMs are good for this as well. Like I said, it's a tool in the toolbox. It can be used a million different ways.

the_arun 2y ago

> It's currently really hard for newbies to break into the software industry as it's still recovering from the en-mass layoffs two years ago. With coding assistants this good, now, and getting better daily I'm left wondering... This can definitely help with some of the tech debts. But I wonder how do we deal with changing requirements? Use Cases? Experiments & new directions from Product? Software has a life after building.

golly_ned 2y ago

This is a tired trope, that engineers who don’t use software assistants will be left in the dust and need to hop onboard asap. It’s really easy to learn how to use software assistants. Those engineers can hop on or off any time. It’s really hard to build up fundamental engineering skills.

mouse_ 2y ago
Thanks for putting this better than I could have.
chii 2y ago
Not really. Imagine if it was driving a truck instead. Anyone, realistically, could've learnt to do it. But if you don't already know how to drive one, you're never going to get hired as one. And by the time the truck driving jobs are the only jobs there is left, it's a tad late - you're already behind everyone else who's got some years of experience.
- f1shy 2y ago
  I think it is a bad examples. It would be like: new trucks are automatic, while current manual. If you don’t learn to drive automatic, you can do that anytime, no problem, as long as you are proficient in driving manual.
f1shy 2y ago
I would argue even the opposite. And that is the reason I resist to using them (assistants). Just as people using GPS are loosing the orientation abilities, I’m afraid that excesive use of assistants may deteriorate our abilities.
- uludag 2y ago
  To further this point, while the vast majority of people could go without such skills, there are jobs where such skills are valuable. So developing skills pretty much everyone has given up on allow one to carve a unique niche for themselves.

mouse_ 2y ago

Listen close, please. The end goal of AI coding assistants is not > convert this rust library at https://github.com/RustAudio/cpal/tree/master https://github.com/RustAudio/cpal/tree/master to a haskell library using ghc2024. The end goal is something more like > Build me a website where users can make and share a link to a text document like a shopping list and edit it collaboratively This guy thinks LLMs are so great, but if he grew up with LLMs, not only would he not have the skill set to competently ask the LLM to produce that output, he wouldn't have any idea the output he's trying to produce. OpenAI, Google, Microsoft are not trying to sell the idea of helping out your senior engineers. They are trying to sell the idea that any of your interns could be senior engineers, so that you no longer have to pay for expensive senior engineers.

fragmede 2y ago
> Build me a website where users can make and share a link to a text document like a shopping list and edit it collaboratively Between a human and a current-day LLM that would take a day, tops, to implement.

deadbabe 2y ago

The only advantage AI code assistants have over competent humans is speed in generating code. But speed doesn’t matter. When code is going to live for several years, no one will care if it took minutes to create vs a week. If you are an incompetent human, you might never be able to generate the same code some LLM generates. This will cause you to sing it’s praises and worship the LLM as your savior. In general, there is a correlation between weak developers and how hyped they are by LLM coding assistants.

AnimalMuppet 2y ago
> When code is going to live for several years, no one will care if it took minutes to create vs a week. No, but... if it took minutes instead of a week, that leaves you the rest of the week to create N more things. That matters, and may still matter in several years.
- deadbabe 2y ago
  There are not N more things to create. It’s better to focus on making the things you do make as good as possible. And even if there were N more things, you’re creating NxN maintenance issues at an overwhelming rate.

2099miles 2y ago

TLDR: ai can be helpful, anyone who doesn’t use it hasn’t realized it’s helpful, SWE’s who disagree “are frankly not gonna make it” Review: great fun story, I agree with the first part of the take and I like the post and I like some ai tools, I disagree with the last bit. There are really good SWE’s who are in spaces where ai is not that useful. SWE is too big now, it’s too vague, ai doesn’t apply to all. You don’t need to use ai to survive, but I agree you should try it out and see before dismissing it. And retry it every so often cuz it’s developing and changing.

ixtli 2y ago

Binary, polarizing language for clicks. I've had a few mild versions of the "oh fuck" moment they're talking about in the past 1-2 years but outside of some specific cases (writing test data generators, scaffolding, etc.) LLMs havent massively changed the way I do things. They're cool and all but, c'mon. I've been programming for 25 years, 15 of which were professional. This is a majorly creative job and while I'm down for Butlarian Jihad as much as the next guy you need to actually have a machine which can be self-sufficiently creative to start talking about it.

karl_gluck 2y ago

Thanks for this -- have been using Cody a lot and just tried Windsurf on my hobby project. So far it seems immediately like a step up. Has anyone paid for it? The free version is doing good work.

ivjw 2y ago

This is no ingenious feat by any standard, except probably for someone in the Dunning–Kruger dip. https://gwern.net/creative-benchmark https://gwern.net/creative-benchmark I can't wait to see if AI can get past its centripetal plateau.

misiti3780 2y ago

what HN post were they referring to ?

bArray 2y ago

> N period on from now, software engineers who haven't adopted or started exploring software assistants, are frankly not gonna make it. Engineering organizations are right now are split between those who have had that "oh fuck" moment and are leaning into software assistants and those who have not. I'm looking at coders coming out of University who chat-GPT'd every coursework and they can't program their way out of a paper bag. I think what is being lost is the ability to solve non-chat-GPT-able problems. I'm having my 'oh fuck' moment, but I'm looking at the new coders. Maybe I am just super behind the progress train, and that programmers will become a thing of the past. Maybe we can setup some adversarial LLM training scenario and have LLMs that reliably code better than humans. My concern remains valid though, that there is now a generation being created that turns to an LLM rather than reasoning about a problem [1]. [1] https://www.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_sisters_use_of_chatgpt_for_homework_is/ https://www.reddit.com/r/ChatGPT/comments/1hun3e4/my_little_...

neilv 2y ago

> Then took my kids down to the local pool. When I got back, I had a fully functional Haskell library with autogenerated C bindings, FFI to CoreAudio and my jaw was on the ground. With a tricky copyright declaration and licensing. A mechanical translation of Rust code under the copyright of ___? Maybe also involving stealing bits of Haskell code without attribution from material copyrights of ___, ___, and ___? Cleanroom engineering is a thing when it comes to "make me one like that, except I have copyright of it". The LLM laundering approach isn't that. Ripping off open source code isn't new. Various companies and individuals would do it. Occasionally they got caught. Microsoft/GitHub had to reassure companies that cared about LLM copyright violations, by indemnifying them. I guess so that open source projects ripped off would have to face the legal resources of Microsoft.

coldpie 2y ago
It turns out copyright doesn't apply if you violate all of it at the same time. Weird trick.
- formerly_proven 2y ago
  Reminds me of the old "if you owe the bank a million dollars, you're in trouble, if you owe them a billion dollars, they're in trouble" bit.
Joker_vD 2y ago
All this AI-generated stuff really should just go into the public domain automatically. That'd immediately not only resolve any possible copyright disputes but also make AI usage much, much less appealing for the large orgs.
- neilv 2y ago
  > All this AI-generated stuff really should just go into the public domain automatically. That'd immediately not only resolve any possible copyright disputes [...] I can't just take something of yours, and make it public domain.

kennywinker 2y ago

> convert this rust library … > This wasn't something that existed, it wasn't regurgitating knowledge from Stackoverflow. It was inventing/creating something new. But it was something that existed… it took a rust library and converted it to haskell. That’s not invention, that’s conversion

adamontherun 2y ago

I've found that having the coding assistant do large tasks like this unsupervised is the worst way to use it. Asking the assistant to do narrowly defined tasks and then checking the work is the only reliable way. I've been using Cursor since the summer and wrote up a few tips here https://betaacid.co/blog/cursor-dethrones-copilot https://betaacid.co/blog/cursor-dethrones-copilot

ryandrake 2y ago

It would never have occurred to me to ask an LLM to convert an entire library from one language to the other, with tests, and everything. I've started to think of them merely as smarter auto-corrects, like for when you forget the syntax or which order a functions arguments go in, you can just use copilot's inline chat to write "Convert this array of tuples to a dict" and it saves you the 20 seconds it takes to look up the syntax. Or "See above line where I deserialized a uint32 from a binary file. Do the same thing for all the other fields in the foobar struct". I just never even thought to ask it to simply build my whole app for me.

disgruntledphd2 2y ago
I've tried the entire app thing once seriously, and didn't get great results. In other cases, it's super helpful with smaller problems like parse this data out of this example of HTML. But I do agree that the code is pretty crap in most cases. I feel like if I was seriously doing this then I'd be mostly refactoring the generated code and writing tests.

uludag 2y ago

So I've been doing a lot of thinking and I've gone through a rollercoaster of feelings concerning AI and becoming redundant. Recently though, I've had a different "oh fuck" moment: what if the period of general global prosperity is coming to an end, that Fukuyama's end of history is coming to an end, that climate change won't come under control. Maybe I'll look back and wish that I could be a redundant SWE in a 2010s economy. With such a backdrop, how scary could AI really be?

ben_w 2y ago
> With such a backdrop, how scary could AI really be? On a personal level, sure. On a society-wide level… Even if the AI doesn't improve, consider that there are people who think the answers to every question can be found in the actual literal Bible, and then ask what such a personality would do when there's a small box that can opine confidently about basically everything and is right often enough to be competitive with people who stay in full time education until age 19 or 20. Or, if the Bible analogy doesn't appeal, consider how it took until the Renaissance for European society to seriously attempt to go past that of classical Rome and Greece.
JohnMakin 2y ago
> that climate change won't come under control. All signs point to this, or it's already reached a tipping point - certainly nothing we are already doing is reducing total carbon output, just slowing its acceleration. There was that one weird year in 2020 where emissions went down as the entire world stopped commuting - regardless of what you think about the realistic ability of new/unproven tech and regulations will be at preventing 3+ celsius change from industrial average by 2100 (catastrophe of biblical proportions) - if AI is indeed as critical to the economy/humanity's future as its proponents (marketers) say, the enormous amount of power and other resources that often don't get factored in, like the massive amounts of increasingly scarce water to cool the massive datacenters - will certainly make such efforts at reducing emissions extraordinarily unlikely, if not impossible, short of converting our entire power grid to sustainable energy, which there seems to be little to no political will for. It's grim, I'm extremely skeptical of optimism at this point on this particular topic. I am bracing for catastrophe at some point in my life (looking at the LA fires very near me, I would argue it's already here) and think the world governments would be wise to do so as well rather than pretend we're just going to magically figure it out at the last possible second. Not even to mention there are a lot of people, including people in power, who don't even believe climate change is happening at all. We're living in Don't Look Up.

TheBozzCL 2y ago

Dunno, man. I'm using Claude 3.5 via Cody on IntelliJ for work, or via Kagi for other cases. When it works, it works great - especially for easy, well-understood things like boilerplate code or the typical simple tasks that I don't bother memorizing because they were already available in search engines anyway. For anything more complex or esoteric, LLMs shit the bed pretty quickly. A recent example: I needed to implement a particular setup for an Argo CD ApplicationSet (default values plus a per-stage override, at the generator level). Every single suggestion by the LLM was wrong. I decided to dig into the documentation because I assumed there was no way this wasn't possible, and lo and behold - matrix generators are a thing, and my exact use case was an example in the doc. I asked the LLM about it and it knew what they were, so it clearly had indexed it before. It's far from the only issue - the most common one is the below-average quality of code in some cases, with plenty of wrong implementations strictly due to hallucinations. Then Cody has its own issues on top of that - not applying changes correctly is the most common one. Put that together with engineers that are in a rush or are using the LLM as a crutch... and I can see a future where devs with little experience can put together huge codebases that will be as brittle as a house of cards.

fragmede 2y ago
Which sounds pretty great because you could make a whole career off of being the contractor that comes in to fix it when the jr devs who only know LLM prompting can't fix it.
- TheBozzCL 2y ago
  lol same kinda vibe as Fortran devs right now

mirawelner 2y ago

There is a psychology paper waiting to be written about humans perceiving intellect as the ability to communicate knowledge convincingly and thus being amazed by LLMs. I’m by no means immune to it

ixtli 2y ago
Its been a long time since i've been amazed by an HN comment in a positive way. This is a really, really good way of putting it. I'd go further: humans are willing to forgive shockingly grievous intellectual crimes (c.f.: hallucination, dangerous reasoning errors, etc.) if they are clearly communicated in the way you describe.

ben_w 2y ago

> N period on from now, software engineers who haven't adopted or started exploring software assistants, are frankly not gonna make it. Engineering organizations are right now are split between those who have had that "oh fuck" moment and are leaning into software assistants and those who have not. Mine was InstructGPT, a few months before the public release of ChatGPT. Everything that followed was an unsurprising extrapolation of what I saw in that moment. Question is, how far will it continue? That I cannot say. At least a factor of 3 from foreseeable compute improvements… unless a war is started over the manufacture of compute. But also, Koomey's law (energy) is slower than Moore's (unit cost + feature size), and if one presupposes that manufacture of compute is unbounded, then we rapidly hit limits of manufacture of power sources for the compute, and that in turn causes huge economic issues well before there's enough supply to cause mass unemployment… unless there's a lot of huge algorithmic improvements waiting to happen, because that might be enough to skip electricity shortages and go straight to "minimum and cheapest calories to keep human alive are more expensive than the electricity to run the servers that produce economic value equal to the most productive human". I have no confidence in any forecast past the end of 2028.

hfdersa 2y ago

If the output is so amazing why leave out a link to the generated library? Why leave out an explanation of why you needed, or how you’ll use, this Haskell audio api wrapper? In the absence of these this just feels like resume slop. If it is, do recruiters see “I asked a thing to do the work for me” as desirable in a potential hire? The original library’s license is Apache 2.0. Does that have any bearing on the authors opinion on sharing this generated code?

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