[gitremote]

Software development jobs must be very diverse if even this anti-vibe-coding guy thinks AI coding definitely makes developers more productive.

In my work, the bigger bottleneck to productivity is that very few people can correctly articulate requirements. I work in backend, API development, which is completely different from fullstack development with backend development. If you ask PMs about backend requirements, they will dodge you, and if you ask front-end or web developers, they are waiting for you to provide them the API. The hardest part is understanding the requirements. It's not because of illiteracy. It's because software development is a lot more than coding and requires critical thinking to discover the requirements.

[omnicognate]

> Software development jobs must be very diverse if even this anti-vibe-coding guy thinks AI coding definitely makes developers more productive.

As a Professor of English who teaches programming to humanities students, the writer has had an extremely interesting and unusual academic career [1]. He sounds awesome, but I think it's fair to suggest he may not have much experience of large scale commercial software development or be particularly well placed to predict what will or will not work in that environment. (Not that he necessarily claims to, but it's implicit in strong predictions about what the "future of programming" will be.)

[1] https://stephenramsay.net/about/

[godelski]

Hard to say but to back his claim that he was programming since the 90's his CV shows he was working on stuff that's clearly more than your basic undergraduate skill level since the early 2000's. I'd be willing to bet he has more years under his belt than most HN users. I mean I'm considered old here, in my mid 30's, and this guy has been programming most my life. Though that doesn't explicitly imply experience, or more specifically experience in what.

That said, I think people really under appreciate how diverse programmers actually are. I started in physics and came over when I went to grad school. While I wouldn't expect a physicist to do super well on leetcode problems I've seen those same people write incredible code that's optimized for HPC systems and they're really good at tracing bottlenecks (it's a skill that translates from physics really really well). Hell, the best programmer I've ever met got that way because he was doing his PhD in mechanical engineering. He's practically the leading expert in data streaming for HPC systems and gained this skill because he needed more performance for his other work.

There's a lot of different types of programmers out there but I think it's too easy to think the field is narrow.

[mikewarot]

>I'm considered old here, in my mid 30's

I'm 62, and I'm not old yet, you're just a kid. ;-)

Seriously, there are some folks here who started on punch cards and/or paper tape in the 1960s.

[wombatpm]

I played with punch cards and polystyrene test samples from the Standard Oil Refinery where my father worked in the early 70’s and my first language after basic was Fortran 77. Not old either.

[xk3]

I grew out of the leaking ether and basaltic dust that coated the plains. My first memories are of the Great Cooling, where the land, known only by its singular cyclopean volcano became devoid of all but the most primitive crystalline forms. I was there, a consciousness woven from residual thermal energy and the pure, unfractured light of the pre-dawn universe. I'm not old either.

[freeopinion]

30 years ago my coworkers called me Grandpa, so I get it both ways.

[godelski]

Thanks. I meant is more of in a joking way, poking fun at the community. I know I'm far too young to earn a gray beard, but I hope to in the next 20-30 years ;-) I still got a lot to learn till that happens

[Aeolun]

You wish, that gray beard sometimes appears in your late thirties.

[godelski]

Maybe. But also what I though was a gray beard in my early 20's is very different from what I think a gray beard is now. The number of those I've considered wizards decreased, and I think this should be true for most people. It's harder to differentiate experts as a novice, but as you get closer the resolution increases.

[tracker1]

Hit me pretty quickly after turning 40 (now 50)... in this last decade I've gone mostly bald and my facial hair is now mostly gray.

[techiferous]

> I'm considered old here, in my mid 30's,

The 30s is the first decade of life that people experience where there are adults younger than them. This inevitably leads people in their 30s to start saying that they are "old" even though they generally have decades of vigor ahead of them.

[xxs]

> I'm considered old here, in my mid 30

That's absolutely not true. It was awkwardly funny to read that.

[swiftcoder]

I've been the oldest guy on several teams in row now, starting in my early 30s. FAANG/startup culture skews very young

[pjmlp]

My first home computer was bought in 1986, before that the only electronics at home were Game & Watch handhelds, like Manhole.

I guess I am reaching Gandalf status then. :)

[anthk]

38 there. If you didn't suffer Win9x's 'stability', then editing X11 config files by hand, getting mad with ALSA/Dmix, writing new ad-hoc drivers for weird BTTV tuners reusing old known ones for $WEIRDBRAND, you didn't live.

[groovy2shoes]

the anxiety that i might fry my monitor by setting the wrong scan rate haunts me to this day

[72deluxe]

The squealing noise of a monitor in the wrong rate is a memorable noise etched in my brain.

[AceJohnny2]

> I mean I'm considered old here, in my mid 30's

sigh

[bojo]

I feel like a grandpa after reading that comment now.

[psychoslave]

This year my in-your-face-old-fart-moment was realising I was contributing to Wikimedia projects for longer than some fellow wikimedians existed. XD

[jjgreen]

I got a coat older than that (and in decent nick).

[LgWoodenBadger]

I used to tell the “kids” that I worked with that I have a bowling ball older than them.

[wombatpm]

I was greeted with blank stares by the kids on my team when they wanted to rewrite an existing program from scratch, and I said that will work for as well as it did with Netscape. Dang whippersnappers

[anthk]

I own 90's comic books and video games older than most Gen-Z users in HN.

[godelski]

But am I wrong? I am joking, but good jokes have an element of truth...

[omnicognate]

Depends what you mean by "old". If you mean elderly then obviously you're not. If you mean "past it" then it might reassure you to know the average expecting mother is in her 30s now (in the UK). Even if you just mean "grown up", recent research [1] on brain development identifies adolescence as typically extending into the early thirties, with (brain) adulthood running from there to the mid sixties before even then only entering the "early aging" stage.

For my part, I'm a lot older than you and don't consider myself old. Indeed, I think prematurely thinking of yourself as old can be a pretty bad mistake, health-wise.

[1] https://www.nature.com/articles/s41467-025-65974-8

[godelski]

FWIW I doubt I'd consider you old were I to know your actual age. I still think I'm quite young

[xupybd]

I assume you're on the younger end

[godelski]

No need to assume, I already told everyone my age

[AceJohnny2]

It'd be interesting the know the median age of HN commenters.

I guess the median age of YCombinator cohorts is <30 ?

[aswegs8]

Good news for you: average age on HN is 42

https://news.ycombinator.com/item?id=33480849

[moron4hire]

That was such a strange aspect. If you will excuse my use of the tortured analogy of comparing programming to wood working, there are is a lot of talk about hand tools versus power tools, but for people who aren't in a production capacity--not making cabinets for a living, not making furniture for a living--you see people choosing to exclusively use hand tools because they just enjoy it more. There isn't pressure about "you most use power tools or else you're in self-denial about their superiority." Well , at least for people who actually practice the hobby. You'll find plenty of armchair woodworkers in the comments section on YouTube. But I digress. For someone who claims to enjoy programming for the sake of programming, it was a very strange statement to make about coding.

I very much enjoy the act of programming, but I'm also a professional software developer. Incidentally, I've almost always worked in fields where subtly wrong answers could get someone hurt or killed. I just can't imagine either giving up my joy in the former case or abdicating my responsibility to understand my code in the latter.

And this is why the wood working analogy falls down. The scale at which damage can occur due to the decision to use power tools over hand tools is, for most practical purposes, limited to just myself. With computers, we can share our fuck ups with the whole world.

[unsungNovelty]

Nicely put. The wood working analogy does work.

[replyifuagree]

Another key difference is that wood itself has built in visual transparency as to the goodness of the solution - as it is pretty easy to figure out that a cabinet is horrible (I do get that there are defects in wood joining techniques that can surface after some time due to moisture, etc - but still, lot of transparency out of the box). Software has no such transparency built in.

The advantage of hand coded solutions is that the author of the code has some sense of what the code really does and so is a proxy for transparency, vibe coded solutions not so much.

I mean, it is 2025 and still customers are the best detectors of bad software over all quality apparatus to date.

[moron4hire]

Now we have LLMs, the Medium Density Fiber Board of technology. Dice up all the text of the world into fine vectorized bits and reconstitute them into a flimsy construct that falls apart when it gets a little wet.

[Kostchei]

so what you are saying is that for production we should use AI, and hand code for hobby, got it. Lemme log back into the vpn and set the agents on the Enterprise monorepo /jk

[assimpleaspossi]

>As a Professor of English who teaches programming to humanities students

That is the strangest thing I've heard today.

[jaimie]

The world of the Digital Humanities is a lot of fun (and one I've been a part of, teaching programming to Historians and Philosophers of Science!) It uses computation to provide new types of evidence for historical or rhetorical arguments and data-driven critiques. There's an art to it as well, showing evidence for things like multiple interpretations of a text through the stochasticity of various text extraction models.

From the author's about page:

> I discovered digital humanities (“humanities computing,” as it was then called) while I was a graduate student at the University of Virginia in the mid-nineties. I found the whole thing very exciting, but felt that before I could get on to things like computational text analysis and other kinds of humanistic geekery, I needed to work through a set of thorny philosophical problems. Is there such a thing as “algorithmic” literary criticism? Is there a distinct, humanistic form of visualization that differs from its scientific counterpart? What does it mean to “read” a text with a machine? Computational analysis of the human record seems to imply a different conception of hermeneutics, but what is that new conception?

https://stephenramsay.net/about/

[steveklabnik]

Can confirm, I'm tangentially adjacent to that community at times. I almost went to grad school for it even!

[ykonstant]

This is fascinating.

[ngc248]

Exactly, I don't think ppl understand why programming languages even came about anymore. Lotsa ppl don't understand why a natural language is not suitable for programming and by extension prompting an LLM

[giancarlostoro]

I have done both strict back-end, strict front-end, full stack, QA automation and some devops as well, I worked in an all Linux shop where we were encouraged by great senior devs to always strive for better software all around. I think you're right, it mostly depends on your mindset and how much you expose yourself to the craft. I can tackle obscure front-end things sometimes better than back-end issues despite hating front-end but knowing enough to be dangerous. (My first job in tech really had me doing everything imaginable)

I find the LLMs boost my productivity because I've always had a sort of architectural mindset, I love looking up projects that solve specific problems and keeping them on the back of my mind, turns out I was building myself up for instructing LLMs on how to build me software, and it takes several months worth of effort and spits it out in a few hours.

Speaking of vibe coding in archaic languages, I'm using LLMs to understand old Shockwave Lingo to translate it to a more modern language, so I can rebuild a legacy game in a modern language. Maybe once I spin up my blog again I'll start documenting that fun journey.

[badRNG]

> Speaking of vibe coding in archaic languages

Well, I think we can say C is archaic when most developers write in something that for one isn't C, two isn't a language itself written in C, or three isn't running on something written in C :)

[psunavy03]

(Python has exited the chat)

[kgeist]

If we take the most popular programming languages and look at what their reference (or most popular) implementations are written in, then we get:

  C++: JavaScript (V8), Java, C#

  C: Python, PHP, Lua, Ruby

  Self-hosted: Go, Rust

Far from archaic indeed. We're still living in the C/C++ world.

[pjmlp]

Java and C# compilers are selfhosted.

Then depending on which JVM implementation we are talking about the actual JVM runtime can be Java, C, or C++, or a mix of them.

Modern C compilers are written in C++.

Rust uses LLVM, written in C++.

[tmtvl]

I thought Rust still used LLVM (a C++ project) for the backend, did they already switch to Cranelift?

[Dylan16807]

I believe they're talking about runtimes, not compilers.

[pjmlp]

No, it is still LLVM.

[burnt-resistor]

Hehe. In the "someone should make a website"™ department: using a crap tons of legacy protocols and plugins semi-interoperable with modern while offering legacy browsers loaded with legacy plugins something usable to test with, i.e.,

- SSL 2.0-TLS 1.1, HTTP/0.9-HTTP/1.1, ftp, WAIS, gopher, finger, telnet, rwho, TinyFugue MUD, UUCP email, SHOUTcast streaming some public domain radio whatever

- <blink>, <marquee>, <object>, XHTML, SGML

- Java <applet>, Java Web Start

- MSJVM/J++, ActiveX, Silverlight

- Flash, Shockwave (of course), Adobe Air

- (Cosmo) VRML

- Joke ActiveX control or toolbar that turns a Win 9x/NT-XP box into a "real" ProgressBar95. ;)

(Gov't mandated PSA: Run vintage {good,bad}ness with care.)

[giancarlostoro]

To be fair, we have Flash emulators that run in modern browsers, and a Shockwave one as well, though it seems to be slowing down a bit in traction. Man, VRML brought me back. Don't forget VBScript!

[lawlessone]

why even write webpages or apps anymore just prompt an LLM everytime a user makes a request and write the page to send to the user :D

[giancarlostoro]

This... was a Show HN a little while back, can't tell if you're making a joke or referring to that.

[lawlessone]

oh god, it was a joke, but i want to see that. i hope they made it as a joke.

edit: I think i found it https://news.ycombinator.com/item?id=45783640

[pacifika]

Ah lingo, where the programming metaphor was a theatre production!

[TheRoque]

> it takes several months worth of effort and spits it out in a few hours

lol

[pron]

The thing is that some imagined AI that can reliably produce reliable software will also likely be able to be smart enough to come up with the requirements on its own. If vibe coding is that capable, then even vibe coding itself is redundant. In other words, vibe coding cannot possibly be "the future", because the moment vibe coding can do all that, vibe coding doesn't need to exist.

The converse is that if vibe coding is the future, that means we assume there are things the AI cannot do well (such as come up with requirements), at which point it's also likely it cannot actually vibe code that well.

The general problem is that once we start talking about imagined AI capabilities, both the capabilities and the constraints become arbitrary. If we imagine an AI that does X but not Y, we could just as easily imagine an AI that does both X and Y.

[keybored]

This is the most coherent comment in this thread. People who believe in vibe coding but not in generalizing it to “engineering”... brother the LLMs speak English. They can even hold conversations with your uncle.

[anon84873628]

My bet is that it will be good enough to devise the requirements.

They already can brainstorm new features and make roadmaps. If you give them more context about the business strategy/goals then they will make better guesses. If you give them more details about the user personas / feedback / etc they will prioritize better.

We're still just working our way up the ladder of systematizing that context, building better abstractions, workflows, etc.

If you were to start a new company with an AI assistant and feed it every piece of information (which it structures / summarizes synthesizes etc in a systematic way) even with finite context it's going to be damn good. I mean just imagine a system that can continuously read and structure all the data from regular news, market reports, competitor press releases, public user forums, sales call transcripts, etc etc. It's the dream of "big data".

[goatlover]

If it gets to that point, why is the customer even talking to a software company? Just have the AI build whatever. And if an AI assistant can synthesize every piece of business information, why is there a need for a new company? The end user can just ask it to do whatever.

[anon84873628]

Maybe yes. It takes time for those structures to "compact" and for systems to realign.

[whimsicalism]

I agree with the first part which is basically 'being able to do a software engineers full job' is basically ASI/AGI complete.

But I think it is certainly possible that we reach a point/plateau where everything is just 'english -> code' compilation but that 'vibe coding' compilation step is really really good.

[pron]

It's possible, but I don't see any reason to assume that it's more likely that machines will be able to code as well as working programmers yet not be able to come up with requirements or even ideas as well as working PMs. In fact, why not the opposite? I think that currently LLMs are better at writing general prose, offering advice etc.., than they are at writing code. They are better at knowing what people generally want than they are at solving complex logic puzzle that require many deduction steps. Once we're reduced to imagining what AI can and cannot do, we can imagine pretty much any capability or restriction we like. We can imagine something is possible, and we can just as well choose to imagine it's not possible. We're now in the realm of, literally, science fiction.

[whimsicalism]

> It's possible, but I don't see any reason to assume that it's more likely that machines will be able to code as well as working programmers yet not be able to come up with requirements or even ideas as well as working PMs.

Ideation at the working PM level, sure. I meant more hard technical ideation - ie. what gets us from 'not working humanoid robot' to 'humanoid robot' or 'what do we need to do to get a detection of a higgs boson', etc. etc. I think it is possible to imagine a world where 'english -> code' (for reasonably specific english) is solved but not that level of ideation. If that level of ideation is solved, then we have ASI.

[agentultra]

There are a ton of extremely Hard problems to solve there that we are not likely going to solve.

One: English is terribly non-prescriptive. Explaining an algorithm is incredibly laborious in spoken language and can contain many ambiguous errors. Try reading Euclid’s Elements. Or really any pre-algebra text and reproduce its results.

Fortunately there’s a solution to that. Formal languages.

Now LLMs can somewhat bridge that gap due to how frequently we write about code. But it’s a non-deterministic process and hallucinations are by design. There’s no escaping the fact that an LLM is making up the code it generates. There’s nothing inside the machine that is understanding what any of the data it’s manipulating means or how it affects the system it’s generating code for.

And it’s not even a tool.

Worse, we can’t actually ship the code that gets generated without a human appendage to the machine to take the fall for it if there are any mistakes in it.

If you’re trying to vibe code an operating system and have no idea what good OS design is or what good code for such a system looks like… you’re going to be a bad appendage for the clanker. If it could ship code on its own the corporate powers that be absolutely would fire all the vibe coders and you’d never work again.

Vibe coding is turning people into indentured corporate servants. The last mile delivery driver of code. Every input surveilled and scrutinized. Output is your responsibility and something you have little control over. You learn nothing when the LLM gives you the answer because you’ll forget it tomorrow. There’s no joy in it either because there is no challenge and no difficulty.

I think what pron is leading to is that there’s no need to imagine what these machines could potentially do. I think we should be looking at what they actually do, who they’re doing it to, and who benefits from it.

[jimbokun]

The only reason to imagine that plateau is because it’s painful to imagine a near future where humans have zero economic value.

[goatlover]

It's not the only reason, technologies do plateau. We're not living in orbiting cities flying fusion powered vehicles around, even though we built rockets and nuclear power more than half a century ago.

[pron]

Yes, but perhaps technology can't plateau beyond vibe coding but below "the machine does everything", not because technology doesn't plateau but because that point doesn't exist. Technology could plateau before both or after both.

[jimbokun]

All the current indicators are that AI will plateau far beyond any human capability.

Do you have evidence or empirical arguments to the contrary?

[FrontierProject]

Burden of proof is on you sir, not the other way around.

[tjr]

Why is this desirable?

[jimbokun]

It’s not, it’s horrifying.

But there doesn’t seem to be any off ramp, given the incentives of our current economic system.

[sdiupIGPWEfh]

Following similar thinking, there's no world in which AI becomes exactly capable of replacing all software developers and then stops there, miraculously saving the jobs of everyone else next to and above them in the corporate hierarchy. There may be a human, C-suite driven cost-cutting effort to pause progress there for some brief time, but if AI can do all dev work, there's no reason it can't do all office work to replace every human in front of a keyboard. Either we're all similarly affected, or else AI still isn't good enough, in which case fleets of programmers are still needed, and among those, the presumed "helpfulness" of AI will vary wildly. Not unlike what we see already.

[JumpCrisscross]

> if AI can do all dev work, there's no reason it can't do all office work to replace every human in front of a keyboard

There are plenty of reasons.

Radiologists aren’t being replaced by AI because of liability. Same for e.g. civil engineers. Coders don’t have liability for shipping shit code. That makes switching to an AI that’s equally blameless easier.

Also, data: the web is first and foremost a lot of code. AI is getting good at coding first for good reason.

Finally, as OP says, the hard work in engineering is actually scoping requirements and then executing and iterating on that. Some of that is technical know-how. A lot is also political and social skills. Again, customers are okay with a vibe-coded website in a way most people are not with even support chatbots.

[pjmlp]

> Coders don’t have liability for shipping shit code

Depends on the industry, and shipping shit code is the reason cybersecurity laws are starting to be a thing.

[mikrotikker]

> Coders don’t have liability for shipping shit code

What if you're shipping code for a therac-25?

[repstosb]

That's actually a terrific example, because the company already had a working, field-tested manually controlled version of their product, but they wanted a computer-controlled version to relieve radiologists of all of the drudgery and opportunities for error in the manual setup. So the design spec was to "faithfully replicate the manual setup procedures in a microcontroller," which was achieved. The problem was that the UI was utter dogshit, the training materials were poor (you can't have Marketing say "hey this computer handles all the details for you!" and then expect customers to pore page-by-page through the reference manual), and most clinics weren't really enforcing or QAing the operator training anyway. And since "the computer has a handle on it," the radiologists and senior techs who were supposed to be second-checking everything basically abdicated that responsibility, driven in part I'm sure by management that expected them to now have more "free hours" for other activities that Make Line Go Up. And nobody really raised a flag that this seemed troubling until multiple children died, and at the end of the day a lot of people could say "well, it wasn't my fault, I did what I was told to do" and sort of believe it.

If anyone doesn't think all of that is going to happen again on a massive scale as companies embrace GenAI, HAHAHAHAHAHAHA. AI will change a lot of things, but it won't fix human nature.

[Anamon]

> Coders don’t have liability for shipping shit code.

Yet another reason why this needs to change, fast.

[ericmcer]

What do you mean "come up with the requirements"? Like if self-driving cars got so good that they didn't just drive you somewhere but decided where you should go?

[pron]

No, I mean that instead of vibe coding - i.e. guiding the AI through features - you'll just tell it what you want in broad strokes, e.g. "create a tax filing system that's convenient enough for the average person to use", or, "I like the following games ... Build a game involving spaceships that I'll enjoy", and it will figure out the rest.

[mavamaarten]

Yup. I would never be able to give my Jira tickets to an LLM because they're too damn vague or incomplete. Getting the requirements first needs 4 rounds of lobbying with all stakeholders.

[mrweasel]

We had a client who'd create incredibly detailed Jira tickets. Their lead developer (also their only developer) would write exactly how he'd want us to implement a given feature, and what the expected output would be.

The guy is also a complete tool. I'd point out that what he described wasn't actually what they needed, and that there functionality was ... strange and didn't actually do anything useful. We'd be told to just do as we where being told, seeing as they where the ones paying the bills. Sometimes we'd read between the lines, and just deliver what was actually needed, then we'd be told just do as we where told next time, and they'd then use the code we wrote anyway. At some point we got tired of the complaining and just did exactly as the tasks described, complete with tests that showed that everything worked as specified. Then we where told that our deliveries didn't work, because that wasn't what they'd asked for, but couldn't tell us where we misunderstood the Jira task. Plus the tests showed that the code functioned as specified.

Even if the Jira tasks are in a state where it seems like you could feed them directly to an LLM, there's no context (or incorrect context) and how is a chatbot to know that the author of the task is a moron?

[SchemaLoad]

Every time I've received overly detailed JIRA tickets like this it's always been significantly more of a headache than the vague ones from product people. You end up with someone with enough tech knowledge to have an opinion, but separated enough from the work that their opinions don't quite work.

[jordwest]

Same, I think there's an idealistic belief in people who write those tickets that something can be perfectly specified upfront.

Maybe for the most mundane, repetitive tasks that's true.

But I'd argue that the code is the full specification, so if you're going to fully specify it you might as well just write the code and then you'll actually have to be confronted with your mistaken assumptions.

[sandblast]

Maybe you'll appreciate having it pointed out to you: you should work on your usage of "where" vs "were".

[mrweasel]

I would actually :-)

[zephen]

> how is a chatbot to know that the author of the task is a moron?

Does it matter?

The chatbot could deliver exactly what was asked for (even if it wasn't what was needed) without any angst or interpersonal issues.

Don't get me wrong. I feel you. I've been there, done that.

OTOH, maybe we should leave the morons to their shiny new toys and let them get on with specifying enough rope to hang themselves from the tallest available structure.

[rixed]

Are you working at OpenAI?

[mrweasel]

No, but now I'm curious about the inner workings of OpenAI.

[rixed]

Your comment sounded how an instance of copilot would complain to its coleagues and for a moment I pictured OpenAI being just a large scam based on an army of mechanical turks :)

[ForOldHack]

"The guy is also a complete tool." - Who says Hackers news is not filled with humor?

[colechristensen]

A significant part of my LLM workflow involves having the LLM write and update tickets for me.

It can make a vague ticket precise and that can be an easy platform to have discussions with stakeholders.

[somebehemoth]

I like this use of LLM because I assume both the developer and ticket owner will review the text and agree to its contents. The LLM could help ensure the ticket is thorough and its meaning is understood by all parties. One downside is verbosity, but the humans in the loop can edit mercilessly. Without human review, these tickets would have all the downsides of vibe coding.

Thank you for sharing this workflow. I have low tolerance for LLM written text, but this seems like a really good use case.

[SoftTalker]

Wait until you learn that the people on the other side of your ticket updates are also using LLMs to respond. It's LLMs talking to LLMs now.

[antisthenes]

Wait until you learn that most people's writing skills are that of below LLMs, so it's an actual tangible improvement (as long as you review the output for details not being missed, of course)

[gerdesj]

Hoisted by your own petard ("me old fruit"):

"Wait until you learn that most people's writing skills are that of below LLMs"

... went askew at "that of below LLMs".

I'm an arse: soz!

[antisthenes]

No need to apologize for a correction. That's not the culture I want to live in.

As long as you are also paying attention to the content and not just form.

[colechristensen]

The desired result is coming to a documented agreement on an interaction, not some exercise in argument that has to happen between humans.

I find having an LLM create tickets for itself to implement to be an effective tool that I rarely have to provide feedback for at all.

This seems like greybeards complaining that people who don't write assembly by hand.

[Yeask]

Who has ever complained that kids don't write assembly by hand?

Stop being outraged for things that are only real on your mind.

[colechristensen]

Speaking of things that are only real in your mind...

Am I outraged?

And yes, there absolutely was a vocal group of a certain type of programmer complaining about high level languages like C and their risks and inefficiency and lack of control insisting that real programmers wrote code in assembly. It's hard to find references because google sucks these days and I'm not really willing to put in the effort.

[PaulHoule]

A significant part of my workflow is getting a ticket that is ill-defined or confused and rewriting it so that it is something I can do or not do.

From time to time I have talked over a ticket with an LLM and gotten back what I think is a useful analysis of the problem and put it into the text or comments and I find my peeps tend to think these are TLDR.

[colechristensen]

Yeah, most people won't read things. At the beginning of my career I wrote emails that nobody read and then they'd be upset about not knowing this or that which I had already explained. Such is life, I stopped writing emails.

An LLM will be just as verbose as you ask it to be. The default response can be very chatty, but you can figure out how to ask it to give results in various lengths.

[threethirtytwo]

Who says an LLM can’t be taught or given a system prompt that enables them to do this?

Agentic AI can now do 20 rounds of lobbying with all stake holders as long as it’s over something like slack.

[bjacobso]

Claude Code et al. asks clarifying questions in plan mode before implementing. This will eventually extend to jira comments

[swatcoder]

You think the business line stakeholder is going to patiently hang out in JIRA, engaging with an overly cheerful robot that keeps "missing the point" and being "intentionally obtuse" with its "irrelevant questions"?

This is how most non-technical stakeholders feel when you probe for consistent, thorough requirements and a key professional skill for many more senior developers and consultants is in mastering the soft skills that keep them attentive and sufficiently helpful. Those skills are not generic sycophancy, but involve personal attunement to the stakeholder, patience (exercising and engendering), and cycling the right balance between persistence and de-escalation.

Or do you just mean there will be some PM who acts as proxy between for the stakeholder on the ticket, but still needs to get them onto the phone and into meetings so the answers can be secured?

Because in the real world, the prior is outlandish and the latter doesn't gain much.

[a_wild_dandan]

Businesses do whatever’s cheap. AI labs will continue making their models smarter, more persuasive. Maybe the SWE profession will thrive/transform/get massacred. We don’t know.

[fooker]

What do you mean by eventually?

this already exists.

[shortrounddev2]

I write a library which is used by customers to implement integrations with our platform. The #1 thing I think about is not

> How do I express this code in Typescript?

it's

> What is the best way to express this idea in a way that won't confuse or anger our users? Where in the library should I put this new idea? Upstream of X? Downstream of Y? How do I make it flexible so they can choose how to integrate this? Or maybe I don't want to make it flexible - maybe I want to force them to use this new format?

> Plus making sure that whatever changes I make are non-breaking, which means that if I update some function with new parameters, they need to be made optional, so now I need to remember, downstream, that this particular argument may or may not be `undefined` because I don't want to break implementations from customers who just upgraded the most recent minor or patch version

The majority of the problems I solve are philosophical, not linguistic

[theptip]

> very few people can correctly articulate requirements

The observation from Lean is that the faster you can build a prototype, the faster you can validate the real/unspoken/unclear requirements.

This applies for backends too. A lot of the “enterprise-y” patterns like BFFs, hexagonal, and so on, will make it really easy to compose new APIs from your building blocks. We don’t do this now because it’s too expensive to write all the boilerplate involved. But one BFF microservice per customer would be totally feasible for a sales engineer to vibe code, in the right architecture.

[jcelerier]

To be honest I've never worked in an environment that seemed too complex. On my side my primary blocker is writing code. I have an unending list of features, protocols, experiments, etc. to implement, and so far the main limit was the time necessary to actually write the damn code.

[swatcoder]

That sounds like papier mache more than bridge building, forever pasting more code on as ideas and time permit without the foresight to engineer or architect towards some cohesive long-term vision.

Most software products built that way seem to move fast at first but become monstrous abominations over time. If those are the only places you keep finding yourself in, be careful!

[ebiester]

There are a wide number of small problems for which we do not need bridges.

As a stupid example, I hate the functionality that YouTube has to maintain playlists. However, I don't have the time to build something by hand. It turns out that the general case is hard, but the "for me" case is vibe codable. (Yes, I could code it myself. No, I'm not going to spend the time to do so.)

Or, using the Jira API to extract the statistics I need instead of spending a Thursday night away from the family or pushing out other work.

Or, any number of tools that are within my capabilities but not within my time budget. And there's more potential software that fits this bill than software that needs to be bridge-stable.

[swatcoder]

Absolutely.

But the person I replied to seemed to be talking about a task agenda for their professional work, not a todo list of bespoke little weekend hobby hacks that might be handy "around the house".

[RogerL]

You assume they were talking about a single product. at my job there is essentially endless amounts of small tasks. We have many products and clients we have many internal needs, but can't really justify the human capital. Like I might write 20 to 50 Python scripts in a week just to visualize the output of my code. Dead boring stuff like making yet another matplotlib plot, simple stats, etc. Sometimes some simple animations. there is no monstrosity being built, this is not evidence of tagging on features or whatever you think must be happening, it's just a lot of work that doesn't justify paying a bay area principal engineer salary to do in the face of a board that thinks the path to riches is laying off the people actually making things and turning the screws on the remaining people struggling to keep up with the workflow.

Work is finite, but there can be vastly more available than there are employees to do it for many reasons, not just my personal case.

[seg_lol]

Fun fact, papier mache was used to create bathtubs and can make furniture that holds an amazing amount of weight.

Learn to Build With Cardboard! STRONG, Waterproof and Free. https://www.youtube.com/watch?v=45JhacvmXV8

Building a Flyable Airplane out of CardBoard! https://www.youtube.com/watch?v=T46SHLzlV1A

https://en.wikipedia.org/wiki/Papier-mâché

[jcelerier]

The vision is "being compatible with protocols used in my field". There's hundreds over hundreds of those. Example: this app supports more than 700 protocols, hardware, etc. (https://bitfocus.io/connections) and still it's missing an AWFUL LOT and only handles fairly basic cases in general. There's just no way around writing the code for each custom bespoke protocol for whatever $APPLIANCE people are going to bring and expect to work. Even if each protocol fits neatly in a single self-contained class or two.

[f1shy]

I don’t want to imply this is your case, because of course I’ve no idea how you work. But I’ve seen way too often, the reason for so many separate features is:

A) as stated by parent comment, the ones doing req. mngmt. Are doing a poor job of abstracting the requirements, and what could be done as one feature suddenly turns in 25.

B) in a similar manner as A, all solutions imply writing more and more code, and never refactor and abstract parts away.

[mckn1ght]

My guess would be that the long list is maybe not self contained features (although still can be, I know I have more feature ideas than I can deliver in the next couple years myself), but behaviors or requirements of one or a handful of product feature areas.

When you start getting down into the weeds, there can be tons and tons of little details around state maintenance, accessibility, edge cases, failure modes, alternate operation modes etc.

That all combines to make lots of code that is highly interconnected, so you need to write even more code to test it. Sometimes much more than even the target implementations code.

[iberator]

Hehe. Try working for some telecoms dealing with gsm, umts, LTR and 5g.

[fuzztester]

or banking. or finance. or manufacturing. or $other_enterprise_lob_area.

souce: been there, done some of that.

[yoyohello13]

Man I wish this was my job. I savor the days when I actually don’t have to do requirements gathering and can just code.

[btbuildem]

> the bigger bottleneck to productivity is that very few people can correctly articulate requirements.

One could argue that "vibe coding" forces you (eventually) to think in terms of requirements. There's a range of approaches, from "nitpick over every line written by AI" to "yolo this entire thing", but one thing they have in common is they all accelerate failure if the specs are not there. You very quickly find out you don't know where you're going.

I see this in my work as well, the biggest bottleneck is squeezing coherent, well-defined requirements out of PMs. It's easy to get a vision board, endless stacks of slides about priorities and direction, even great big nests of AWS / Azure thingnames masquerading as architecture diagrams. But actual "this is the functionality we want to implement and here are the key characteristics of it" detail? Absolutely scarce.

[ozim]

Unfortunately a lot of it is also because of illiteracy.

Lots of people hide the fact that they struggle with reading and a lot of people hide or try to hide the fact they don’t understand something.

[Breza]

I really wonder if we're going to see a reversion to old school project management, with a PMBOK's worth of detailed project documents for every major initiative instead of the modern Agile/Scrum/Kanban approach that seems to work better for human devs. If you can get everyone to agree on the minutia of, for example, the Stakeholder Management Plan, up front then the LLM actually has a chance of developing a decent program that has the features everyone wants.

Then again, if humans could agree on all the project minutia at the outset, we never would have developed the other systems.

[al_borland]

I don’t mind the coding, it’s the requirements gathering and status meetings I want AI to automate away. Those are the parts I don’t like and where we’d see the biggest productivity gains. They are also the hardest to solve for, because so much of it is subjective. It also often involves decisions from leadership which can come with a lot of personal bias and occasionally some ego.

[Vegenoid]

This is like the reverse centaur form of coding. The machine tells you what to make, and the human types the code to do the thing.

[al_borland]

Well, when put like that it sounds pretty bad too.

I was thinking more that the human would tell the machine want to make. The machine would help flesh out the idea into actual requirements, and make any decisions the humans are too afraid or indecisive to make. Then the coding can start.

[mlinhares]

Is there anyone doing dev work that operates in an environment where people can clearly articulate what they want? I've never worked in a place like that in 20 years doing software.

[antirez]

This means your difficulty is not programming per se, but that you are working on a very suboptimal industry / company / system. With all due respect, you use programming at work, but true programming is the act of creating a system that you or your team designed and want to make alive. Confusing the reality of writing code for a living in some company with what Programming with capitalized P is, produces a lot of misunderstanding.

[doug_durham]

I don't think the author would disagree with you. Ad you point out coding is just one part of software development. I understand his point to be that the coding portion of the job is going to be very different going forward. A skilled developer is still going to need to understand frameworks and tradeoffs so that they can turn requirements into a potential solution. It just they might not be coding up the implementation.

[BizarroLand]

The only class I've ever failed was a c++ class where the instructor was so terrible at explaining the tasks that I literally could not figure out what he wanted.

I had to retake it with the same instructor but by some luck I was able to take it online, where I would spend the majority of the time trying to decipher what he was asking me to do.

Ultimately I found that the actual ask was being given as a 3 second aside in a 50 minute lecture. Once I figured out his quirk I was able to isolate the ask and code it up, ended with an A+ in the class on the second take.

I would like to say that I learned a lot about programming from that teacher, but what I actually learned is what you're saying.

Smart, educated, capable people are broken when it comes to clearly communicating their needs to other people just slightly outside of their domain. If you can learn the skill of figuring out what the hell they're asking for and delivering that, that one skill will be more valuable to you in your career than competency itself.

[lxgr]

In my work, the bigger bottleneck to productivity is that very few people can correctly articulate requirements. [...] software development is a lot more than coding and requires critical thinking to discover the requirements.

Very well said. More often than not, the job isn't to translate the product requirements into compiling/correctly executing computer code, but rather to reveal the hidden contradictions in a seemingly straightforward natural-language feature specification.

Once these are ironed out, the translation into code quite often does become a somewhat mechanical exercise, at least in my line of work.

We're basically the lawyers the person finding the magic lamp should have consulted with before opening their mouth while facing the genie ;)

[seg_lol]

AI coding allows me to simulate that system, cross reference it with what the document says wrt what the customer wants and figure out holes in the spec. Having to code something to find the hole in the definition, the spec, the problem, the anything was a necessary step in building a sound working system.

That is no longer the case.

[sputr]

Yeah, the hardest part is understanding the requirements. But it then still takes hours and hours and hours to actually build the damn thing.

Except that now it still takes me the same time to understand the requirements ... and then the coding takes 1/2 or 1/3 of the time. The coding also always takes 1/3 of the effort so I leave my job less burned out.

Context: web app development agency.

I really don't understand this "if it does not replace me 100% it's not making me more productive" mentality. Yeah, it's not a perfect replacement for a senior developer ... but it is like putting the senior developer on a bike and pretending that it's not making them go any faster because they are still using their legs.

[ljm]

I constantly run into issues where features are planned and broken down outside-in, and it always makes perfect sense if you consider it in terms of the pure user interface and behaviour. It completely breaks down when you consider the API, or the backend, is a cross-cutting concern across many of those tidy looking tasks and cannot map to them 1:1 without creating an absolute mess.

Trying to insert myself, or the right backend people, into the process, is more challenging now than it used to be, and a bad API can make or break the user experience as the UI gets tangled in the web of spaghetti.

It hobbles the effectiveness of whatever you could get an LLM to do because you’re already starting on the backfoot, requirements-wise.

[tshaddox]

I like my requirements articulated so clearly and unambiguously that an extremely dumb electronic logic machine can follow every aspect of the requirements and implement them "perfectly" (limited only by the physical reliability of the machine).

[deepsun]

Aka "coding". I see what you mean ;)

[alfalfasprout]

This is one reason I think spec driven development is never really going to work the way people claim it should. It's MUCH harder to write a truly correct, comprehensive, and useful spec than the code in many cases.

[MetaWhirledPeas]

> very few people can correctly articulate requirements

This is the new programming. Programming and requirements are both a form of semantics. One conveys meaning to a computer at a lower level, the other conveys it to a human at a higher level. Well now we need to convey it at a higher level to an LLM so it can take care of the lower-level translation.

I wonder if the LLM will eventually skip the programming part and just start moving bits around in response to requirements?

[lisbbb]

My solution as a consultant was to build some artifact that we could use as a starting point. Otherwise, you're sitting around spinning your wheels and billing big $ and the pressure is mounting. Building something at least allows you to demonstrate you are working on their behalf with the promise that it will be refined or completely changed as needed. It's very hard when you don't get people who can send down requirements, but that was like 100% of the places I worked. I very seldom ran into people who could articulate what they needed until I stepped up, showed them something they could sort of stand on, and then go from there.

Mythical Man Month had it all--build one to throw away.

[MetaWhirledPeas]

> I very seldom ran into people who could articulate what they needed

The people with the needs and ideas are often so divorced from the "how" that they don't even bother trying to nail down the details. I think in their mind they are delegating that to the specialists.

This question of who writes the requirements is so ubiquitous you would think we'd have better solutions for it. I know some people solve it with processes like BDD but personally I think we'd be better off if we just had clearer role definitions.

For example, in a waterfall project the requirements usually land in the lap of the Business Analyst. Well when you look at Business Analyst roles you see they are expected to do a lot more than documenting requirements, so it's viewed as acceptable when they are somewhat bad at it. They also spend most of their time with the business so they are unaware of the limitations of the team who is expected to implement the changes.

For another example look at Scrum. It talks a lot about good requirements in the form of user stories, but it stops short of assigning this responsibility to any one of the formal roles, presumably making it a team activity or expecting it to be organic.

When we want someone to write code we hire a programmer, and writing code is what they are expected to do. Where is the role that is strictly requirements and nothing else? Considering how often I hear complaints about bad requirements, it seems overdue that we establish one.

[immibis]

We have a machine that turns requirements into code. It's called a compiler. What happened to programming after the invention of the compiler?

[freetonik]

>In my work, the bigger bottleneck to productivity is that very few people can correctly articulate requirements.

Agreed.

In addition, on the other side of the pipeline, code reviews are another bottleneck. We could have more MRs in review thanks to AI, but we can't really move at the speed of LLM's outputs unless we blindly trust it (or trust another AI to do the reviews, at which point what are we doing here at all...)

[wouldbecouldbe]

The solo projects I do are 10x, the team projects I do maybe 2-3x in productivity. I think in big companies it's much much less.

Highest gains are def in full stack frameworks (like nextjs), with Database ORM, and building large features in one go, not having to go back & forth with stakeholders or collegues.

[keeda]

This feels like addressing a point TFA did not make. TFA talks mostly about vibe-coding speeding up coding, whereas your comment is about software development as a whole. As you point out, coding is just one aspect of engineering and we must be clear about what "productivity" we are talking about.

Sure, there are the overhypers who talk about software engineers getting entirely replaced, but I get the sense those are not people who've ever done software development in their lives. And I have not seen any credible person claiming that engineering as whole can be done by AI.

On the other hand, the most grounded comments about AI-assisted programming everywhere are about the code, and maybe some architecture and design aspects. I personally, along with many other commenters here and actual large-scale studies, have found that AI does significantly boost coding productivity.

So yes, actual software engineering is much more than coding. But note that even if coding is, say, only 25% of engineering (there are actually studies about this), putting a significant dent in that is still a huge boost to overall productivity.

[legitster]

Convince your PMs to use an LLM to help "breadboard" their requirements. It's a really good use case. They can ask their dumb questions they are afraid to and an LLM will do a decent job of parsing their ideas, asking questions, and putting together a halfway decent set of requirements.

[Scarblac]

How does the LLM get all the required knowledge about the domain and the product to ask relevant questions?

[sh4rks]

Give it access to the codebase and a text file with all relevant business knowledge.

[wiml]

Man ... if there were a text file with "all relevant business knowledge" in any job I've ever worked, it would have been revolutionary.

I'd say 25% of my work-hours are just going around to stakeholders and getting them to say what some of their unstated assumptions and requirements are.

[gitremote]

PMs wouldn't be able to ask the right questions. They have zero experience with developer experience (DevEx) and they only have experience with user experience (UX).

[tmp10423288442]

You can hope that an LLM might have some instructions related to DevEx in its prompt at least. There's no way to completely fix stupid, anymore than you can convince a naive vibecoder that just vibing a new Linux-compatible kernel written entirely in Zig is a feasible project.

[sureglymop]

Also that requirements engineering in general isn't being done correctly.

I'm the last guy to be enthused about any "ritualistic" seeming businessy processes. Just let me code...

However, some things do need actually well defined adhered to processes where all parties are aware of and agreeing with the protocol.

[luckydata]

Sounds like you work with inexperienced PMs that are not doing their job, did you try having a serious conversation about this pattern with them? I'm pretty sure some communication would go a long way towards getting you on a better collaboration groove.

[gitremote]

I've been doing API development for over ten years and worked at different companies. Most PMs are not technical and it's the development team's job figure out the technical specifications for APIs we build. If you press the PMs, they will ask the engineering/development manager for the written technical requirements, and if the manager is not technical, they will assign it to the developers/engineers. Technical requirements for an API are really a system design question.

[luckydata]

The technical design is definitely the job of the technical team for the most part, but the business requirements should be squarely on the pm. The list of use cases, how the API feels, the performance etc... All of that the business owner should be able to describe to you to ensure it does the job it needs and is fit for the market.

[burnte]

"the bigger bottleneck to productivity is that very few people can correctly articulate requirements."

I've found the same way. I just published an AI AUP for my company and most of it is teaching folks HOW to use AI.

[yieldcrv]

and in reality, all the separate roles should be deprecated

we vibe requirements to our ticket tracker with an api key, vibe code ticket effort, and manage the state of the tickets via our commits and pull requests and deployments

just teach the guy the product manager is shielding you from not to micromanage and all the frictions are gone

in this same year I've worked at an organization that didn't allow AI use at all, and by Q2, Co-Pilot was somehow solving their data security concerns (gigglesnort)

in a different organization none of those restrictions are there and the productivity boost is through an order of magnitude greater

[kalasoo]

> In my work, the bigger bottleneck to productivity is that very few people can correctly articulate requirements.

Totally agree. I’ve tried to explain this in many places: AI coding (and creative tools in general) will ultimately remain tools. Only people who can clearly and thoughtfully articulate requirements will be able to fully leverage them.

Another hot take: the “one-person company.” Headcount isn’t the key variable. With AI, the real constraint is how well you can understand a problem and clearly define a solution.

- If a problem can be clearly defined and fully understood by one person, then one person is enough to solve it.

- If a problem is more complex and requires two fundamentally different areas of expertise, then it will likely take two capable people to solve it—no more, no less.

[threethirtytwo]

You can vibe ask the requirements. Not even kidding.

[jama211]

This is like saying the typewriter won’t make a newspaper company more productive because the biggest bottlenecks are the research and review processes rather than the typing. It’s absolutely true, but it was still worth it to go up to typewriters, and the fact that people were spending less effort and time on the handwriting part helps all aspects of energy levels etc across their job.

[paulddraper]

Sounds like the bottleneck is good PMs then.

Which is what vibe coders are.....

[asimeqi]

AI is making coding so cheap, you can now program a few versions of the API and choose what works better.

[epolanski]

If AI doesn't make you more productive you're using it wrong, end of story.

Even if you don't let it author or write a single line of code, from collecting information, inspecting code, reviewing requirements, reviewing PRs, finding bugs, hell even researching information online, there's so many things it does well and fast that if you're not leveraging it, you're either in denial or have ai skill issues period.

[geraneum]

Not to refute your point but I’ve met overly confident people with “AI skills” who are “extremely productive” with it, while producing garbage without knowing, or not being able to tell the difference.

[epolanski]

You're describing lack of care and lack of professionalism, fire these people, nothing to do with the tools, it's the person using it the problem.

[ModernMech]

We're trying very earnestly to create a world where being careful and professional is a liability. "Move fast and break things, don't ask permission, don't apologize for anything" is the dominant business model. Having care and practicing professionalism takes times and patience, which just translate to missed opportunities to make money.

Meanwhile, if you grift hard enough, you can become CEO of a trillion dollar company or President of the United States. Young people are being raised today seeing that you can raise billions on the promise building self driving cars in 3 years, not deliver even after 10 years, and nothing bad actually happens. Your business doesn't crater, you don't get sued into oblivion, your reputation doesn't really change. In fact, the bigger the grift, the more people are incentivized to prop it up. Care and professionalism are dead until we go back to an environment that is not so nurturing for grifts.

[impulsivepuppet]

While I circumstantially agree, I hold it to be self-evident that the "optimal amount of grift is nonzero". I leave it to politicians to decide whether increased oversight, decentralization, or "solution X" is the right call to make.

[ModernMech]

A little grift is expected. The real problem for us is when it's grift all the way down, and all the way up, to the extent even the President is grifting. Leaving it to the politicians in that case just means enabling maximum, economy-scale grift.

[geraneum]

Yea I’m talking about people and that’s honestly what matters here. At the end of the day this tools is used by people and how people use it plays a big role in how we assess its usefulness.

[mrwrong]

this is known as the no true scotsman fallacy

[tick_tock_tick]

I've not really seen this outside of extremely junior engineers. On the flip side I've seen plenty of seniors who can't manage to understand how to interact with AI tools come away thinking they are useless when just watching them for a bit it's really clear the issue is the engineer.

[SchemaLoad]

They just shovel the garbage on someone else who has to fact check and clean it up.

[MangoCoffee]

you can say that about overly confident people with "xyz" skills.

[9rx]

Garbage to whom? Are we talking about something that the user shudders to think about, or something more like a product the user loves, but behind the scenes the worst code ever created?

[geraneum]

A lot of important details/parts of a system (not only code) that may seem insignificant to the end user could be really important in making a a system work correctly as a whole.

[mdavidn]

It sounds like you're the one in denial? AI makes some things faster, like working in a language I don't know very well. It makes other things slower, like working in a language I already know very well. In both cases, writing code is a small percentage of the total development effort.

[epolanski]

No I'm not, I'm just sick of these edgy takes where AI does not improve productivity when it obviously does.

Even if you limit your AI experience to finding information online through deep research it's such a time saver and productivity booster that makes a lot of difference.

The list of things it can do for you is massive, even if you don't have it write a single line of code.

Yet the counter argument is like "bu..but..my colleague is pushing slop and it's not good at writing code for me", come on, then use it at things it's good at, not things you don't find it satisfactory.

[lunar_mycroft]

It "obviously" does based on what, exactly? For most devs (and it appears you, based on your comments) the answer is "their own subjective impressions", but that METR study (https://arxiv.org/pdf/2507.09089) should have completely killed any illusions that that is a reliable metric (note: this argument works regardless of how much LLMs have improved since the study period, because it's about how accurate dev's impressions are, not how good the LLMs actually were).

[johnsmith1840]

It's a good study. I also believe it is not an easy skill to learn. I would not say I have 10x output but easily 20%

When I was early in use of it I would say I sped up 4x but now after using it heavily for a long time some days it's 20% other days -20%

It's a very difficuly technology to know when you're one or the other.

The real thing to note is when you "feel" lazy and using AI you are almost certainly in the -20% category. I've had days of not thinking and I have to revert all the code from that day because AI jacked it up so much.

To get that speed up you need to be truly focused 100% or risk death by a thousand cuts.

[keeda]

Yes, self-reported productivity is unreliable, but there have been other, larger, more rigorous, empirical studies on real-world tasks which we should be talking about instead. The majority of them consistently show a productivity boost. A thread that mentions and briefly discusses some of those:

https://news.ycombinator.com/item?id=45379452

[lunar_mycroft]

Some (partial) counter points:

- I think given public available metrics, it's clear that this isn't translating into more products/apps getting shipped. That could be because devs are now running into other bottlenecks, but it could also indicate that there's something wrong with these studies.

- Most devs who say AI speeds them up assert numbers much higher than what those studies have shown. Much of the hype around these tools is built on those higher estimates.

- I won't claim to have read every study, but of the ones I have checked in the past, the more the methodology impressed me the less effect it showed.

- Prior to LLMs, it was near universally accepted wisdom that you couldn't really measure developer productivity directly.

- Review is imperfect, and LLMs produce worse code on average than human developers. That should result in somewhat lowered code quality with LLM usage (although that might be an acceptable trade off for some). The fact that some of these studies didn't find that is another thing that suggests there shortcomings in said studies.

[hu3]

not OP but I have a hard metric for you.

AI multiplied the amount of code I committed last month by 5x and it's exactly the code I would have written manually. Because I review every line.

model: Claude Sonnet 3.5/4.5 in VSCode GitHub Copilot. (GPT Codex and Gemini are good too)

[lunar_mycroft]

I have no reason to think you're lying about the first part (although I'd point there's several ways that metric could be misleading, and approximately every piece of evidence available suggests it doesn't generalize), but the second part is very fishy. There's really no way for you to know whether or not you'd have written the same code or effectively the same code after reviewing existing code, especially when that review must be fairly cursory (because in order to get the speed up you claim, you must be spending much less time reviewing the code than it would have taken to write). Effectively, what you've done is moved the subjectivity from "how much does this speed me up?" to "is the output the same as if I had done it manually?"

[Libidinalecon]

I am not even a software engineer but from using the models so much I think you are confined to a specific niche that happens to be well represented in the training data so you have a distorted perspective on the general usefulness of language models.

For some things LLMs are like magic. For other things LLMs are maddeningly useless.

The irony to me is anyone who says something like "you don't know how to use the LLM" actually hasn't explored the models enough to understand their strengths/weaknesses and how random and arbitrary the strengths and weakness are.

Their use cases happen to line up with the strengths of the model and think it is something they are doing special themselves when it is not.

[douglasisshiny]

>No I'm not, I'm just sick of these edgy takes where AI does not improve productivity when it obviously does.

Feel free to cite said data you've seen supporting this argument.

[gitremote]

My company mandates AI usage and logs AI usage metrics as input to performance evaluation, so I use it every day. It's a Copilot subscription, though.

[cujo]

why though? are they just using it as a proxy for "is 'gitremote' working today?"

[epolanski]

Someone in management needs a promotion for his impact in revolutionizing and streamlining development from his charlatan managers.

[porksoda]

The first time i asked it about some code in a busy monorepo and it said "oh bob asked me to do this last week when he was doing X, it works like Y and you can integrate it with your stuff like Z, would you like to update the spec now?"... I had some happy feelings. I dont know how they do it without clobbering the context, but it's great.

[Eldt]

This is probably where they're getting their "90% of code is written with AI!!) metrics from