[sasaf5]

Early 2023, when everyone started using chat GPT for coding, I thought it would be a big boost because it enabled us to quickly employ a large number of people in a project regardless of language or framework.

An year into the project I am forced to revise my opinion. When browsing my code-base I often stumble in abstruse niche solutions for problems that should not have existed. It was clearly the work of someone inexperienced walking through walls in an AI-fuelled coding frenzy.

Having an oracle that knows all answers is useless if you don't know what to ask.

[AlwaysRock]

> It was clearly the work of someone inexperienced walking through walls in an AI-fuelled coding frenzy.

Isnt this what code reviews are for? I catch a decent amount of code that looks AI generated. Typically, some very foreign pattern or syntax that this engineers never used nor is common in the codebase. Or something weirdly obtuse that could be refactored and shows a lack of understanding.

Normally I ask something like, "Interesting approach! Is there a reason to do it this way over (mention a similar pattern in our codebase)?" or if it's egregious, I might ask, "Can you explain this to me?".

This feel similar to early career engineers copy pasting stack overflow code. Now its just faster and easier for them to do. It's still fairly easy to spot though.

[steve1977]

> Isnt this what code reviews are for?

Wouldn't you need to have people with a proper understanding of the programming language and framework to do the code reviews?

[fhd2]

You would. And if the juniors don't really _write_ code in the languages you use, if they don't make mistakes and do research themselves, it'll take them a lot longer to learn them sufficiently to be able to do those reviews.

Listening to people talk in Japanese, I picked up enough to have some idea what they're talking about. I can't speak the language beyond some canned phrases. I certainly wouldn't claim to know Japanese. And I definitely wouldn't get a job writing books in Japanese, armed with Google Translate.

For programming, my solution to this right now is lots of pair programming. Really gives you a good idea of where somebody is at, what they still need to learn, and lots of teaching opportunities. I just hired a junior and we spend about 8 hours a week pairing.

[AlwaysRock]

Yeah. Are we assuming 100% of the people working on this project are incompetent? I thought OP was talking about new people joining a project producing low quality code that was likely generated by AI.

Code reviews, done by existing more senior members of the project/team, should prevent this. If it isnt then the project has more issues than AI generated code.

[vouaobrasil]

> Isnt this what code reviews are for?

There is no substitute to doing something correctly in the first place. The problem is that in the real world, deadlines and lack of time will always cause the default solution to be accepted a small percentage of time even when it is not ideal. The increasing creep of AI will only exacerbate that and most technophiles will default into thinking of a new and improved AI tool to help with the problem, until it will be AI tools all the way down.

No thanks.

[CuriouslyC]

I would agree with there being no substitute for doing something correctly the first place, but I would argue that in this case the "first place" is hiring/training better so your employees don't try to throw unrefined AI shit at the walls, but instead take the output of AI and hone it before creating a PR.

If you have an engineering culture that doesn't emphasize thorough code review (at least of juniors, leads and architects emergency-pushing is a different story) that's a problem. In addition to catching bugs, that's a major vector for passing on knowledge.

[vouaobrasil]

I agree with you, no doubt there. But still, technology often offers the path of least resistance. So even if you want to hire better people, what of all the people who will grow up training themselves with Copilot? Yes, you can filter them out but it will be harder and harder to find good people. And then, companies will want to go after the bottom line: what if they can get a bigger and more complex product out there with AI assistance but with code that is more unreliable in the long term?

I tell you, it's spiralling out of control. Besides, even if you're doing the hiring, you may not have control if there is a profit motive. Us technical people cannot control the race to the bottom line, especially over the period of decades.

[ungreased0675]

>Isnt this what code reviews are for?

A foundational concept of quality control is to not rely on inspection to catch production defects. Why not? It diffuses responsibility, lets more problems get to the customer and is less efficient than doing it correctly to start with.

[throwup238]

Code review isn’t inspection, that would be testing - whether automatic or manual.

Code review is the feedback mechanism that allows quality control to improve the process, teaching the engineers how to do it right in the first place.

[arrowsmith]

> It's still fairly easy to spot though.

Or maybe it's far more common than you realise, and you're only spotting the obvious ones.

[AlwaysRock]

Sure. If its generating 85% code that passes a code review and 15% of code that doesnt... I'll take those percentages. That is certainly higher than the average early career engineers pr.

[bcrosby95]

It's harder to read code than write it. It's even harder to read code than use an LLM to write it for you.

[AlwaysRock]

Yup. That is why code reviews are important... Read and understand the code that is going out before it goes out.

[adastra22]

Not all organizations can afford code reviews.

[AlexandrB]

If you're trying to do things efficiently you can't afford not doing code reviews. Only well-funded organizations can afford to write the same code twice after the first attempt has to be thrown out.

[nox101]

I work at a FANMG company and see the value of code reviews for th code we're working on. But, I shipped 20 commercial products before that with no code review, just play testing (games). Our velocity without code review was easily 2x what it is with. For those projects I think that would still be true whereas I'd never suggest getting rid of code review at my current job.

The point being I think it depends on the project, it's size, audience, lifetime, etc whether or not code review is a win. my gut says it usually is a win but not always

[PoignardAzur]

That's super weird.

At the one company I was where we did code reviews, they took at most one hour per day. The reviewer would go through the changes, ask for explanations when they didn't understand something, suggest small modifications to fit the codebase's style/structure/vibe, and move on.

They definitely didn't take 50% of our time. Half my time wasn't even spent coding, it was spent thinking about problems (and it was a workplace with an unusually high coding-over-thinking ratio, because of its good practices).

[331c8c71]

> At the one company I was where we did code reviews, they took at most one hour per day. > They definitely didn't take 50% of our time.

Imo introducing code reviews might very well decrease the velocity by 50% even if the actual time spent on code reviews is much less.

I see at least two reasons for this: 1) increased need for synchronization/communication 2) increased subjective frictions and mental overhead (if only for task switching).

Code reviews are not special in this respect, similar effects can be caused by any changes to the process.

[KronisLV]

> They definitely didn't take 50% of our time.

It probably also depends on the people that you're working with. I can easily imagine the velocity plummeting when the person reviewing your code loves to nitpick and bicker and ask for endless further changes with every next round of alterations that you do.

Doubly so if they want to do synchronous calls to go over everything and essentially create visible work out of code that already worked and was good enough in the first place.

I'm not saying that there aren't times like that for everyone occasionally, but there are people for whom that behaviour is a consistent pattern.

[CuriouslyC]

Code review matters when you have a product that has an indeterminate lifespan. When new people come on, they need to learn the codebase and code review both helps ensure a codebase that is easy for new devs to understand (because hard to understand code doesn't survive review) and also it provides an onboarding experience as new devs can be coached during code review.

"One and done" products like games where you're mostly fixing bugs and releasing new content without major overhauls to the underlying code probably only need code reviews for code that is complex/clever where bugs are likely to be hiding, beyond that QA is fine.

[dkersten]

Not just thrown out, but also the customer relations when the bugs affect customers, the investigation to find the cause of the bugs, the migrations to fix any bad/corrupted data because of the bugs. Code review is a far cheaper way to catch errors, bad code, footguns and places where bugs might creep in than letting them into production and having them impact customers. Code reviews also help keep code tidier and cleaner which makes future understanding and changes easier. Small companies can’t afford to omit code reviews.

[rixed]

I don't understand. Is code review supposed to avoid writing coffee twice?

[aaronbrethorst]

I recommend drinking coffee before requesting a code review or posting on an online forum.

[seattle_spring]

Can you elaborate on some scenarios you are describing? The only organization I can imagine that can't do code reviews would be organizations of 1. I don't even see how performing code reviews could ever be a net negative in terms of money nor overall productivity.

[ben_w]

Not OP, but I've been in a few organisations with many devs but also where I was the only iOS dev — the other devs being Android, back-end, or web.

I would have preferred to have someone to collaborate with at each of those places.

[sensanaty]

Even if you're not working in the same language/framework/whatever, you can still do code reviews. You might not know all the syntax and high-level details, but even just an overview of the logic happening in the code is already better than 0 review of any kind

[sensanaty]

Even if you're not working in the same language/framework/whatever, you can still do code reviews. You might not know all the syntax and high-level details, but even just an overview of the logic happening in the code is already better than 0 review of any kind

[oytis]

I think it should be possible (and encouraged) for an Android developer to know enough about ios to do review and vice versa.

[JTyQZSnP3cQGa8B]

Or pair-programming reviews. It doesn't matter if you don't know a language, it's still very useful.

[kragen]

usually 'organization' excludes projects consisting of just one person, and if there are two people working on a project that involves writing code, the cheapest amount of that code for both of them to be familiar with is never zero, though it is often less than 100% of all the code they write. so i don't think that 'not all organizations can afford code reviews' is true, interpreted in the usual way. maybe you can be more specific about the scenario you're thinking of?

[adastra22]

As mentioned in the other comments, code reviews are typically not done in the game industry, for example, or other write-once, never read scenarios. Very early stage startups typically don’t have formal code reviews either.

[kragen]

while that is true, and some of it is rational, other times it's just another stupid way people waste money and fuck up their projects. because even in a startup or a game there is code that people waste time debugging alone, or waiting for the one guy who knows it to get back from vacation, or out of bed

reviews don't have to be formal to be reviews

[AlwaysRock]

Those organizations shouldn't complain about code quality.

[littlestymaar]

No organization can afford not having code reviews.

[adastra22]

No blanket statements apply to all organizations.

[littlestymaar]

“No organization can work in absence of oxygen” proves you wrong.

[debarshri]

I recently was stumbled upon a code change done by a colleague who just followed the suggestion as is from Copilot, where it recommend `func (string, string) (error, struct)` whereas everywhere in the code we use `func (string, string) (struct, error)`

When I asked him what prompted him to do that, he said copilot suggest it so I just followed. I wonder if you could hijack copilot's results and inject malicious code as many end users does not understand lot of the niche code it generates sometimes, you could manipulate them to add the malicious code to the org's codebase.

[vintermann]

The insidious thing is that quite possibly, it "feels" there should be a couple of bugs like that because all the codebases it was trained on had a few.

It might even take the context of the typos in your code comments, and conclude "yeah, this easy to miss subtle error feels right about here".

[throwthrowuknow]

That is a problem but thankfully there is a lot of attention on training with highly curated high quality data right now because it is a known problem. Buggy code is still valuable training data if you use it as part of a question and evaluate the response against a corrected version of the code when training the model to perform a task like bug fixing.

[ben_w]

It's definitely possible to inject malicious code that humans don't spot, there was a whole competition dedicated to humans doing this in C well before LLMs: https://en.wikipedia.org/wiki/Underhanded_C_Contest

Now I'm wondering, can you put in a comment which the LLM will pay attention to such that it generates subtle back-doors? And can this comment be such that humans looking at the code don't realise this behaviour will be due to the comment?

[golergka]

This once again proves that C is the best language to write backdoors.

[AshamedCaptain]

Almost two decades ago, I saw a junior colleague (this was Java) try to add "static" to almost all of one specific class' methods and members, i.e. making them global instead of attached to each class instance . Obviously this completely broke the software, albeit it did build. When questioned during review, my colleague just shrugged and said "Because Eclipse suggested to do so".

Apparently, if you tried to access a class member without specifying a class instance, one of Eclipse's "auto-fix-it" suggestions was to make all members of that class static, and he just followed that suggestion blindly.

[stouset]

> A year into the project I am forced to revise my opinion. When browsing my code-base I often stumble in abstruse niche solutions for problems that should not have existed.

This is a widespread problem regardless of AI. Hence the myriad Stack Overflow users who are frustrated after asking insane questions and getting pushback, who then dig their heels in after being told the entire approach they’re using to solve a problem is bonkers and they’re going to run into endless problems continuing down the path their on.

Not that people aren’t on too fine a hair trigger for that kind of response. But the sensitivity of that reaction is a learned defense mechanism for the sheer volume of it.

[nottorp]

> Hence the myriad Stack Overflow users who are frustrated after asking insane questions and getting pushback, who then dig their heels in after being told the entire approach they’re using to solve a problem is bonkers and they’re going to run into endless problems continuing down the path their on.

The problem is, SO can't tell someone who asks an insane question from someone who asks the same question but has constraints that make it sane. *

So in time, sane people during unusual stuff stop asking questions and you're left with homework.

* For example, "we can't afford to refactor the whole codebase because some architecture astronaut on SO says so" is a constraint.

Or another nice one is "this is not and will never be a project that will handle google-like volumes of data".

[andybak]

> The problem is, SO can't tell someone who asks an insane question from someone who asks the same question but has constraints that make it sane.

Stack Overflow is not there to help you solve your use-case. It's there to create a body of knowledge that everyone can refer to. You need to spell out your specific reasons so that the question and answers become useful to others.

A lot of the friction on Stack Overflow comes from people thinking it's a free help website rather than an attempt to create a collaborative knowledgebase.

[shkkmo]

I think a lot of SO's problems comes from it trying to pretend it was building a knowledge base when it was really only ever a question and answer site.

It was nice to use early in its life when every answer was fresh. These days, the stale knowledge outweighs the fresh and the top answer is usually no longer correct.

If SO wants to be a knowledgebase, it needs to to be redesigned as it's current structure is not well suited to it.

[nottorp]

There's no more friction, I've stopped trying to give answers :)

I was dumb and was trying to help people, not build a 'knowledge base'.

[andybak]

> I was dumb and was trying to help people, not build a 'knowledge base'.

It is about helping people - but helping multiple people for the same effort it takes to help one person.

As we descend further into "Need help? Just ask on our Discord!" hell - it's a lesson that I wish resonated with more people.

[jrockway]

Remembering more than 4096 tokens is my superpower.

[ein0p]

How ‘bout remembering a million tokens? I’m not feeling too confident about that. Basically my only moat, if there is one, is that I’m able to rely on higher level cognition which LLMs don’t yet have, rather than just on associative memory alone.

[iwontberude]

Except these models with high token counts tend to forget the tokens at the beginning of the prompt anyways.

[margalabargala]

This is something that is true in 2024. I would not bet on it being true in 2030.

[xanderlewis]

I might, actually. Think of where electric cars were six years ago — 2018. Not much has changed. Or, at least, there are still fundamental problems to be solved.

In the same way I can imagine that by 2030 LLMs will still have memory problems and hallucinations. Although I’m sure by then we’ll have something better than pure LLMs.

[ben_w]

I've heard claims that context without forgetfulness has already been reached 2 months ago, but as I'm not a domain expert I don't trust that I can differentiate breakthroughs from marketing BS, and I definitely can't differentiate either of those from a Clever Hans: https://arstechnica.com/information-technology/2024/03/claud...

[riwsky]

but by then we'll have forgotten this conversation, so it nets out

[ein0p]

So do I, and worse. Look, all I’m saying is I’m thankful for this crutch that helps me deal with the limitations of my associative memory, so as long as it can’t think and can’t replace me entirely

[yonaguska]

bacopa and lions mane was night and day for my limited memory. But, the obvious, writing simpler code, keeping a notebook while working, etc, and really spending time breaking down problems into much smaller scopes, while simultaneously keeping copious notes on where I am in a given process helped immensely with dealing with peanut brained memory. sure, it's not quick, but my work is usually very readable and understandable for the future reader. I'm not convinced that a tool to help me overcome that memory barrier would actually help me write better code, maybe just write worse code faster. Of course, that's probably the corporate goal though.

[ein0p]

Lions mane didn't seem to do much for me. My memory is actually not that bad, though certainly I have seen people with _much_ better memory than mine. I still maintain contact with some of them I met in college, and then later in the various companies. It's just that I deal with so much information and so many streams of it, even writing it down would be a massive chore.

I would pay for a pre-packaged system which could _locally_ and _privately_ make sense of all the emails, PDFs, slack messages, web pages I saw, other documents shared with me, code, etc etc, and make it all easily queryable with natural language, with references back to the sources. Sooner or later someone will make something like that.

[ben_w]

I may remember more than 4096 tokens, but I probably only pay attention to 7 of them at any given moment: https://en.wikipedia.org/wiki/The_Magical_Number_Seven,_Plus...

[Symmetry]

The context heads of a LLM are more analogous to the sort of processing that goes on in, e.g., Brocca's Area of your brain as opposed to working memory. You can't have anything analogous to working memory as long as LLMs are operating on a strict feed forward basis[1]. And the fact that LLMs can talk so fluently without anything like a human working memory (yet) is a bit terrifying.

[1] Technically LLMs do have a forget that last toke and go back so I can try again operation so this is only 99% true.

[pwdisswordfishc]

No, you don’t. Seven, plus or minus two at best.

[xanderlewis]

I think humans have better general recall whilst lacking any kind of precision. After reading an entire book, I definitely can’t replicate much (if any) of the precise wording of it, but given a reasonably improbable sentence I can probably tell with certainty that it didn’t appear. LLMs are probably much more prone to believing they’ve read things that aren’t there and don’t even pass a basic sanity check, no matter how long the context window.

[jongjong]

>> Having an oracle that knows all answers is useless if you don't know what to ask.

That is a great point. The issue of not asking the right questions has been around as far as I can remember but I guess it wasn't seen as the bottleneck because people were so focused on solving problems by any means possible that they never had to think about solving problems in a simple way. We're still very far from that though and in some ways we have taken steps back. I hope AI will help to shift human focus towards code architecture because that's something that has been severely neglected. Most complex projects I've seen are severely over-engineered... They are complex but they should not have grown to hundreds of thousands of lines of code; had people asked the right questions, focused on the right problems and chosen the right trade-offs, they would have been under 10K lines and way more efficient, interoperable and reliable.

I should note though, that my experience with coding with AI is that it often makes mistakes for complex algorithms, or it implements them in an inefficient way and I almost always have to change them. I get a lot of benefit from asking questions about APIs and to verify my assumptions or if I need a suggestion about possible approaches to do something.

[osigurdson]

Agree. I use AI less now for coding than I did a year ago. I still use it a lot but it is a better teacher than a doer.

[crazygringo]

How do you know it was "AI-fuelled"? And what makes it a "frenzy"?

People have been committing terrible code to projects for decades now, long before AI.

The solution is a code review process that works, and accountability if experienced employees are approving commits without properly reviewing them.

AI shouldn't have anything to do with it. Bad code shouldn't be passing review period, no matter if it was AI-assisted or not. And if your org doesn't do code review, then that's the actual problem.

[eastbound]

> and accountability if experienced employees are approving commits without properly reviewing them.

You’re putting the entire responsibility on senior employees. So we need much more of them. In fact, we don’t need juniors, because we can generate all possible code combinations. After all, it’s the responsibility of the seniors to select which one is correct.

It’s like how hiring was made crap by the “One-click apply” on LinkedIn and all other platforms. Sure it’s easy for thousands of people to apply. Fact is, we offer quite a good job with high salary, and were looking for 5 people. We’ve spent a full year selecting them, because we’ve receive hundreds of irrelevant applications, probably some AI-generated.

It’s no use to flood a filter with crap, hoping that the filter will do better work because it has a lot of input.

[Incipient]

"give me a function to return the top 10 users" - copy paste "give me another to email a template to a list of users" - copy paste

AI makes it much easier to push out bad code, fast...in a "frenzied" way one could say.

[xanderlewis]

This is almost a special case of the very similar (and common) argument that ‘AI-generated misinformation isn’t bad; we’ve always had misinformation’.

The answer is also the same.

Volume. AI makes it trivially easy to generate vast amounts of it that don’t betray their lack of coherence easily. As with much AI content, it creates arbitrary amounts of work for humans to have to sift through in order to know it’s right. And it gives confidence to those who don’t know very much to then start polluting the informationsphere with endless amounts of codswallop.

[taneq]

> Having an oracle that knows all answers is useless if you don't know what to ask.

Honestly I find this to be the biggest advantage to using a coding LLM. It's like a more interactive debugging duck. By the time I've described my problem in sufficient detail for the LLM to generate a useful answer, I've solved it.

[ramones13]

I’ve had a project I’ve been doing for ~6 months learning python through Copilot+ChatGPT. It feels like any other project that accrues technical debt, but that debt is just a lot weirder. It was rough at first, but refactoring has gotten a lot better recently with bigger context sizes.

[gtirloni]

If you need Copilot to code in Python, have you really learned Python?

[anonzzzies]

Good one, however, like Google making memory worse, copilot seems to erode knowledge of programming quite quickly. Last week I was with a colleague at my house; when I hired him during covid he knew these things just fine, but after not having to type in a list comprehension for around 2 years now, when my Starlink was down for a bit, he couldn’t for the life of him create one; he asked Claude opus on his phone instead.

[Aerbil313]

For real. I have the same experience. I'm 19, freelance developer writing Python among other things. Except I never learned Python syntax, and maybe never will.

[raincole]

Does it really matter though? It sounds awfully like when a school teacher said you're not going to have an calculator in your pocket.

[swatcoder]

For a senior-level professional? Yes, it does matter.

I wouldn't be comfortable with an accountant who couldn't do practical arithmetic in their head, or a surveyor who didn't have a fluent grasp of trigonometry and the ratios or function values for common angles.

Of course -- I don't care about the people working for them as a bookkeeper or assistent. They can be button monkeys as much as their boss lets them, but I also wouldn't expect those folk to reach very high in their career. Not everyone's going to, and a disinterest in and lack of technical fluency is a darn good predictor.

Your teacher was giving good advice about building skills and internalizing knowledge, because those are what contribute to mastery of a craft; maybe you were just being too pedantic or cynical to hear it?

[wruza]

I think this advice is backwards, as is the problem. I’d trust an accountant’s mind or a builder’s eye if I knew that they are acting from experience. But you don’t wanna trust someone who believes in-their-head is superior or reliable and makes you good.

The core idea is no, calculating in your head doesn’t turn you into a pro. Being a pro makes calculating in your head safe enough to rely on until you get to your desk and double-check.

That said, I was an integrator half my life and seen some accountants, big and small. Everyone used a calculator, it’s right next to their mouse and there’s another one elsewhere. And no one ever tried to talk about numbers afk, except for ballparks. Most of the times they suggest to go and query a db together. I find it very professional.

[grobgambit]

I just trust my accountant will use excel and what they are doing isn't rocket science.

I have no interest interacting with someone who is going to get into how great the slide ruler is and how kids these days need to learn the slide ruler. When I was younger I thought this type of person was highly admirable but now older and wiser I see how full of shit they are.

[tivert]

>> If you need Copilot to code in Python, have you really learned Python?

> Does it really matter though? It sounds awfully like when a school teacher said you're not going to have an calculator in your pocket.

Yes. A younger me had teachers say that to me, and that younger me thought they were wrong.

But it turns out they were right, and younger me was wrong. Calculator dependence created a ceiling built from "educational debt" that many years later severely limited my mathematical ability.

The problem is focusing too much on getting the "answer," and losing sight of building the abilities that allow you to get there with your own mind. Eventually the need to manipulate your automated crutch turns into a bottleneck.

[Aeolun]

It’s also kind of annoying to intuitively get to the correct answer and have everyone claim they can’t distinguish between that and you using a calculator.

I wonder if that would be an issue if nobody had any.

[golergka]

> Calculator dependence created a ceiling built from "educational debt" that many years later severely limited my mathematical ability.

Can you explain how your problems with arithmetic affected your ability to reason and prove things? I struggle to see how the two are connected.

[tivert]

Isn't it obvious? If you can't do arithmetic without a calculator, it makes it hard to do algebraic manipulation. (Un)luckly a calculator that could do that arrived in my lap just in time. Then you get to calculus, and it was the same story. I eked by with a lot of furious typing, but the mental workload of that made it untenable towards the end and I wasn't really gaining much anyway because of that. It would have been far better if I'd just hadn't been allowed to use a calculator from the start.

It didn't affect my ability to reason and prove things, just as long those things don't strongly require the knowledge and skills I should have gotten from the calculator shaped gap in my education. I lack a lot of the background knowledge and/or familiarity and comfort with many skills that I should have.

[shadowfacts]

Yes, it does matter. While there are plenty of situations where it's foolish to forbid calculators, that's not universally true.

Forbidding calculators and requiring students to do mental math for absolutely everything is unnecessary. But requiring students to solve integrals by hand when they're learning about integrals? Entirely reasonable.

If your goal when teaching coding is to teach the mechanical process of writing code: sure, go ahead and use LLMs for that process. But if your goal is to develop a deeper understanding of how to code, then LLMs can very easily obscure that. The end goal is not always just the answer.

[KronisLV]

> But requiring students to solve integrals by hand when they're learning about integrals? Entirely reasonable.

I remember having to write code on a piece of paper in university.

Curiously, this lead to a lot of other students not really learning or caring about indentations and attempting to make code formatted in a generally readable way once they actually got access to IDEs and such.

They'd write it much like you would regular text on a piece of paper and would get absolutely stumped with unbalanced brackets whenever some nested structure would be needed.

Not only that, but somehow a lot of them didn't quite get around to using the various refactoring features of the tools, since they treated them like editors for writing text.

Did it help me memorize the basic constructs of the languages in question? Absolutely not, at least in the long term, since nowadays I have to jump between a lot of different languages and none of the syntax quite sticks, rather a more high level approach to problem solving.

LLMs just make that easier for me, letting me offload more work around language constructs and boilerplate, albeit requiring occasional intervention.

Maybe my memory just sucks.

[elicksaur]

AI is not replacing the same function as a calculator does when solving a math problem.

Using AI to “help” learn to program is replacing the person’s effort thinking through the problems fully and is ultimately going to stunt their learning.

[Uehreka]

This feels kind of like saying “why do I need to learn how to budget? The calculator will just do it for me.”

[int_19h]

A calculator is fine so long as you understand what the operations actually represent. Remembering the multiplication table is not important, but understanding what multiplication actually does is.

The problem with AI-assisted coding is that, applied uncritically, it circumvents this understanding. And without it, you won't even be able to judge whether the code that CoPilot etc spit out is correct for the task.

[Aeolun]

And have you ever stood in a store where your clerk needs the register to calculate what 200 - 50 ct is? It’s embarrassing!

[kragen]

yeah, at the moment anyway, because if you don't know what the syntax means, you can't tell when the code means something you don't want. that means you can't tell which copilot suggestions to accept and which ones to reject, and you can't debug your code; asking gpt-4 what's wrong with it only goes so far

imagine if the calculator in your pocket gave you subtly wrong answers most of the time

[SoftTalker]

If you need Copilot to code in Python do your really know how to program?

[Kostchei]

This is my new capability- I am not a coder or a programmer and I can get things built, in my own time, at my own speed, solo.

Would it be better code if someone with 3 years of university and 5 years of coding practice did it? Yes, very probably, but the gap seems to be narrowing. Humorously I don't know enough about good code to tell you whether what I build with llms is good code. Sometime I build a function that feels magical, other times it seems like a fragile mess. But I don't know.

Do I know "javascript" or "python" or the theory of good coding practice? No, not currently. But I am building things. Things that I have personal, very specific requirements for. Where I don't have to liaise or berate someone else. Where I don't have to pay someone else. Where I don't share the recognition (if there is any ever) of the thing, I and only I have produced- (with chatGPT, Gemini and most recently llama3).

Folks have been feeling superior for 70 years and earning a good living because they spoke the intermediary language of compute engines. What makes them actually special NOW is computer science, the theory- the languages, we have very cheap (and in the case of open source local models free) translators for those now. And they can teach you some computer science as well, but that is still time and practice.

I'm the muggle. The blunt. And I'm loving this glowy lantern, this psi-rig.

[solarengineer]

One of the lessons that one learns as a programmer is to be able to write code that one can later read back and understand. This includes code written by others as well as code written by oneself.

When it comes to production quality code that should capture complex and/or business-critical functionality, you do want an experienced person to have architected the solution and to have written the code and for that code to have been tested and reviewed.

The risk right now is of many IT companies trying to win bids by throwing inexperienced devs at complex problems and committing to lower prices and timelines by procuring a USD 20 per month Github Co-Pilot subscription.

You individually may enjoy being able to put together solutions as a non-programmer. Good for you. I myself recently used ChatGPT to understand how to write a web-app using Rust and I was able to get things working with some trial and error so I understand your feeling of liberation and of accomplishment.

Many of us on this discussion thread work in teams and on projects where the code is written for professional reasons and for business outcomes. The discussion is therefore focused on the reliability of and the readability of AI-assisted coding.

[Kostchei]

hmm. I ended up with a few 750+ line chunks of js, beyond the ability of chatgpt to parse back at me. So my go-to technique now is to break it into smaller chunks and make them files in a folder structure, rather than existing inside a single *.js So readability is an issue for me- even more so because I rely on ChatGPT to parse it back- sometimes I understand the code, but usually I need the llm to confirm my understanding. I'm not sure if this scales for teams. My work has sourcegraph, which should assist with codebases. So far it hasn't been particularly useful- I can use it to find specific vulnerable libraries, keys in code etc, but that is just search.

What I really need is things like "show me the complete chain of code for this particular user activity in the app and highlight tokens used in authentication" ... - something senior engineers struggle to pull from our hundreds of services and huge pile of code. And so far sourcegraph and lightstep are incapable of doing that job. Maybe with better RAG or infinite context length or some other improvement there will be that tool. But currently the combined output of 1000's of engineers over years almost un-navigable. Some of that code might be crisp, some of it is definitely of llm-like quality (in a bad way)- I know this because I hear people's explanation of said code and how they misremembered it's function during post mortems. Folks copy and pasting outdated example code from the wiki etc. ie making things they don't understand. I presume that used to happen from stackoverflow too. Engineers moving to llm won't make too much difference IMO.

I agree, your points are valid, but I see "prompt engineering" as democratization of the ability to code. Previously this was all out of reach for me, behind a wall of memorization of language and syntax that I touched in the Pascal era and never crossed. 12 hours to build my first node.js app that did something in exactly the way I had wanted for 30 years. (including installing git and vscode on windows- see, now I am truly one to be reviled)

[gtirloni]

Exactly. Your comment summarizes the situation perfectly.

[dkersten]

The problem I currently have with AI-generated code, as an experienced programmer who can read and understand the output, isn’t that the code quality is bad, but that it’s often buggy and wrong. I recently recommended in my company that if copilot is allowed to be used, the developers using it must thoroughly understand every line of code it writes before accepting it, because the risk of error is too high.

Copilot may work for simple scripts, but even for that where it mostly for things right, in my experience it still introduced subtle bugs and incorrect results more often than not.

[adastra22]

I've been coding Python for 15 years, but I probably couldn't code in Python now without Copilot, or a lot of reference docs. There's so much meaningless trivia and idioms I've purposefully pushed out of my mind so I can focus on other things. If copilot has my back, why do I need to remember that crap?

[ramones13]

I don’t need 90% of my IDE features.

For me personally, it’s a fantastic way to learn. I could definitely see people just using it and not actually learning, but to each their own.

[antupis]

If you need Google to code in Python, have you really learned Python?

[antfarm]

Learning to be a good programmer is as much about learning how to avoid technical dept as it is about learning to use a programming language. It may take a while until an AI assistant will be able to help with that.

[1-6]

I think humans are excellent at finding fault. It’s easier to deconstruct a problem than it is to reconstruct one from scratch.

Having an oracle that knows how to put a framework of events together (even wit errors) is much better than asking a human to do it from scratch.

[shufflerofrocks]

>Having an oracle that knows all answers is useless if you don't know what to ask.

This sentence summarizes the issue with the current AI debacle, along with the whole "just copy/pase code from stackoverflow and earn top bucks" meme that was going around in 2010s.

You're not gonna be a valuable dev if you're just write wrong code faster. Not only does chatgpt/copilot give haphazard code half of the time, it approaches seemingly random syntax and format. Even if LLMs are polished, you're gonna need stand software engineering knowledge to know what's right and wrong.

[greenie_beans]

i started to not like coding once ai became involved

[forgetfreeman]

Coding just keeps getting grosser and weirder decade over decade as new layers of abstraction and complexity get piled on. Just about everyone who does this shit for a living eventually hits a break point where the headassery du jour becomes too much to turn a blind eye to.

[codegladiator]

"genie granting 3 wishes gone wrong" is making a come back

[joshstrange]

LLMs are no excuse for bad code reviews or developers who don’t know what it’s spitting out.

In my code reviews the person who wrote the code needs to explain to me what they changed and why. If they can’t then we are going to have a problem. If you don’t understand the code that an LLM spits out you don’t use it, it’s that simple. If you use it and can’t explain it, well… we are going to have to have some discussions and if it keeps happening you’re going to need to find other employment.

The exact same thing has been happening for pretty much the entire time we’ve had internet. Stack Overflow being the primary example now but there were plenty of other resources before SO. People have always been able to copy/paste code they don’t understand and shove it into a codebase. LLMs make that easier, no doubt, but the core issue has always been there and we, as an industry, have had decades to come up with defenses to this. Code review being the best tool in our toolbox IMHO.

[chx]

> Having an oracle that knows all answers is useless if you don't know what to ask.

But that's not what these LLM systems are. https://hachyderm.io/@inthehands/112006855076082650

> You might be surprised to learn that I actually think LLMs have the potential to be not only fun but genuinely useful. “Show me some bullshit that would be typical in this context” can be a genuinely helpful question to have answered, in code and in natural language — for brainstorming, for seeing common conventions in an unfamiliar context, for having something crappy to react to.

> Alas, that does not remotely resemble how people are pitching this technology.

It is exactly what happened to you: it wrote bullshit. Plausible bullshit but bullshit nonetheless.

[teeray]

It’s also just not as good at the task anymore. It frequently gets lazy and gives you an outline with a bunch of vague pseudocode. Compare to when GPT-4 was slower at producing output, but all of that output was solid, detailed work. Some of the magic that made you say “wow” feels like it’s been enshittified out of it.

[beeboobaa3]

I sometimes try the free chatgpt when I run into a problem and it's just hilarious how terrible it is. Loves to go around in circles with the same made up solution that has no basis in reality, using functions in libraries that would be great if they actually existed.

[no-mana]

I noticed that like since a week ago? Output faster, but not impressive. Now I just skip to stack overflow or docs. The output is also giving error a lot more, as if the libraries on which the example is based off was old. Sometimes it's really trivial task just to save time, and it's just not of any help. Still helpful when you want to start something new, it just doesn't scale that well.

[throwaway14356]

oh, i didn't think of that. stack overflow was great early on but then the answers aged poorly

[pwdisswordfishc]

No, they were always rather poor. It’s you who’s matured enough to notice.

[6510]

Yes, rather poor but people can always post new answers and votes sort the answers. It might not work all that well but there is a mechanism for improvement and to keep things up to date.

Language models can copy the top answers from SO, ingest docs and specs etc. And then the information is never updated? Or are they going to train it from scratch? On what? Outdated github saved games?

[chillfox]

Can’t say I have noticed any drop in quality at all. I do have a fairly detailed set of custom instructions set.

[romeros]

It is difficult to get a man to understand something when his salary depends on his not understanding it. ~ U. Sinclair

A significant problem is the subconscious defense mechanism or bias that compels us to conclude that AI has various shortcomings, asserting the ongoing need for status quo.

The capabilities of GPT-3.x in early 2023 pale in comparison to today's AI, and it will continue to evolve and improve.

[signatoremo]

I’m surprised to see this comment was downvoted heavily. The quote is very popular around here, to the point where there is an Ask HN if it’s the most quoted quote:

https://news.ycombinator.com/item?id=27771186

Yet people don’t like it in this thread. Does it touch a nerve?

[raincole]

> Having an oracle that knows all answers is useless if you don't know what to ask.

You just need to ask it what to ask. /s

[loceng]

You need to pay 80% of the efficiency improvement for a higher-tiered curated set of code output from only senior-experienced developers. /s