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Devs are famously bad at estimating how long a software project will take.
No, highly complex creative work is inherently extremely difficult to estimate.
Anyway, not shocked at all by the results. This is a great start that begs for larger and more rigorous studies.
You’re absolutely correct that the angle approach that statement is bullshit. There is also that they want to think making software is not highly complex creative work but somehow is just working an assembly line and the software devs are gatekeepers that don’t deserve respect.
“Devs are famously bad at estimating how long a software project will take.”
No, highly complex creative work is inherently extremely difficult to estimate.
Akshually… I’m on a dev team where about 60% of us are diagnosed with ADHD. So, at least in our case, it’s both.
If we didn’t have ADHD, we wouldn’t be able to do the work regardless.
We’re the only ones that can get hyper focused and also hyper fixated on why a switch statement is failing when it includes a for loop until finding out there’s actually a compiler bug, and if you leave a space after the bracket it somehow works correctly.
That was a fun afternoon.
Gross, which compiler was that?
I managed to make an assembler segfault with seven bytes
As someone that has had to double check peoples code before, especially those that don’t comment appropriately, I’d rather just write it all again myself than try and decipher what the fuck they were even doing.
Megacorp LLM death spiral:
- Megacorp managers at all levels introduce new LLM usage policies.
- Productivity goes down (see study linked in post)
- Managers make the excuse that this is due to a transitional period in LLM policies.
- Policies become mandates. Beatings begin and/or intensify.
- Repeat from 1.
I’ve been through the hellscape where managers used missed metrics as evidence for why we didn’t need increased headcount on an internal IT helpdesk.
That sort of fuckery is common when management gets the idea in their head that they can save money on people somehow without sacrificing output/quality.
I’m pretty certain they were trying to find an excuse to outsource us, as this was long before the LLM bubble we’re in now.
oh, absolutely. I mean you could sub out “LLM” with any bullshit that management can easily spring on their understaff. Agile, standups, return to office, the list goes on. Management can get fucked
I wish I could make more people both know about, and understand, Goodhart’s law
5% “coding”
95% cleanup
ahahaha holy shit. I knew METR smelled a bit like AI doomsday cultists and took money from OpenPhil, but those “open source” projects and engineers? One of them was LessWrong.
Here’s a LW site dev whining about the study, he was in it and i think he thinks it was unfair to AI
I think if people are citing in another 3 months time, they’ll be making a mistake
dude $NEXT_VERSION will be so cool
so anyway, this study has gone mainstream! It was on CNBC! I urge you not to watch that unless you have a yearning need to know what the normies are hearing about this shit. In summary, they are hearing that AI coding isn’t all that actually and may not do what the captains of industry want.
around 2:30 the two talking heads ran out of information and just started incorrecting each other on the fabulous AI future, like the worst work lunchroom debate ever but it’s about AI becoming superhuman
the key takeaway for the non techie businessmen and investors who take CNBC seriously ever: the bubble starts not going so great
Yeah, METR was the group that made the infamous AI IS DOUBLING EVERY 4-7 MONTHS GRAPH where the measurement was 50% success at SWE tasks based on the time it took a human to complete it. Extremely arbitrary success rate, very suspicious imo. They are fanatics trying to pinpoint when the robo god recursive self improvement loop starts.
Software and computers are a joke at this point.
Computers no longer solve real problems and are now just used to solve the problems that overly complex software running on monstrous cheap hardware create.
“Hey I’d like to run a simple electronics schematic program like we had in the DOS days, it ran in 640K and responded instantly!”
“OK sure first you’ll need the latest Windows 11 with 64G of RAM and 2TB of storage, running on at least 24 cores, then you need to install a container for the Docker for the VM for the flatpak for the library for the framework because the programmer liked the blue icon, then make sure you are always connected to the internet for updates or it won’t run, and somehow the program will still just look like a 16 bit VB app from 1995.”
“Well that sounds complicated, where’s the support webpage for installing the program in Windows 7?”
“Do you have the latest AI agents installed in your web browser?”
“It’s asking me to click OK but I didn’t install the 1GB mouse driver that sends my porn browsing habits to Amazon…”
“Just click OK on all the EULAs so you lose the right to the work you’ll create with this software, then install a few more dependencies, languages, entire VMs written in byte code compiled to HTML to run on JAVA, then make sure you have a PON from your ISP otherwise how can you expect to have a few kilobytes of data be processed on your computer? This is all in the cloud, baby!”
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Mark Zuckerberg would like to know your location
Don’t be silly. Mark Zuckerberg already knows our location.
Something something grindset mindset
@dgerard What fascinates me is *why* coders who use LLMs think they’re more productive. Is the complexity of their prompt interaction misleading them as to how effective the outputs it results in are? Or something else?
What fascinates me is why coders who use LLMs think they’re more productive.
As @dgerard@awful.systems wrote, LLM usage has been compared to gambling addiction: https://pivot-to-ai.com/2025/06/05/generative-ai-runs-on-gambling-addiction-just-one-more-prompt-bro/
I wonder to what extent this might explain this phenomenon. Many gambling addicts aren’t fully aware of their losses, either, I guess.
Here’s a random guess. They are thinking less, so time seems to go by quicker. Think about how long 2 hours of calculus homework seems vs 2 hours sitting on the beach.
This is such a wild example to me because sitting at beach is extremely boring and takes forever whereas doing calculus is at least engaging so time flies reasonably quick.
Like when I think what takes the longest in my life I don’t think “those times when I’m actively solving problems”, I think “those times I sit in a waiting room at the doctors with nothing to do” or “commuting, ditto”.
I know what you mean. If I’m absorbed in something I find interesting time flies. Solving integrals is not one those for me.
I just want to point out that every single heavily downvoted, idiotic pro-AI reply on this post is from a .ml user (with one programming.dev thrown in).
I wonder which way the causation flows.
Machine learning is essentially AI with a paper-thin disguise, so that makes sense
It’s kind of the opposite, GenAI is downstream of machine learning which is how artificial neural networks rebranded after the previous AI winter ended.
Also after taking a look there I don’t think lemmy.ml has anything in particular to do with machine learning, it looks more like a straight attempt at a /r/all clone.
wait til you find out what the ml does stand for, it’s a real trip (and it sure as fuck ain’t Mali)
the ml in lemmy.ml stands for marxism-leninism
From the blog post referenced:
We do not provide evidence that:
AI systems do not currently speed up many or most software developers
Seems the article should be titled “16 AI coders think they’re 20% faster — but they’re actually 19% slower” - though I guess making us think it was intended to be a statistically relevant finding was the point.
That all said, this was genuinely interesting and is in-line with my understanding of the human psychology that’s at play. It would be nice to see this at a wider scale, broken down across different methodologies / toolsets and models.
Anyone who has had to unfuck someone else’s work knows it would have been faster to do the work correctly from scratch the first time.
Bit late to the party, but this should prolly be tagged “Paper” on pivot.
I want to put together a little pitch for the data-brained that AI is Not Good Actually®, and this is the most smoking gun I can think of.
ty!
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@dgerard@awful.systems who is your illustrator? These are consistently great.
these are stock images! Which are surprisingly cheap. By Valeriy Kachaev, who puts stuff up as Studiostoks on a pile of stock image sites. His pics are bizarre and keep being the perfect thing.
I’m not sure how much this observation can be generalized, but I’ve also wondered how much the people who overestimate the usefulness of AI image generators underestimate the chances of licensing decent artwork from real creatives with just a few clicks and at low cost. For example, if I’m looking for an illustration for a PowerPoint presentation, I’ll usually find something suitable fairly quickly in Canva’s library. That’s why I don’t understand why so many people believe they absolutely need AI-generated slop for this. Of course, however, Canva is participating in the AI hype now as well. I guess they have to keep their investors happy.
all the stock sites are. use case: an image that’s almost perfect but you wanna tweak it
LEARN PAINT YOU GHOULS
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Are these entry-level developers that are merely half as good as expert human unassisted developers in the room with us right now?
LLM-assisted entry-level developers merely need to be half as good as expert human unassisted developers
- This isn’t even close to existing.
- The theoretical cyborg-developer at that skill level would surely be introducing horrible security bugs or brittle features that don’t stand up to change
- Sadly i think this is exactly what many CEOs are thinking is going to happen because they’ve been sold on openai and anthropic lies that it’s just around the corner
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“I’m not scared a LLM is going to be able to replace me. I’m scared that CEO are going to think that”
AI->cocaine filter: Cocaine isn’t going to replace you. Someone using cocaine is going to replace you.
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as one of the people representing the “hero group” (for lack of a better term) your comment references: eh. I didn’t start out with all this knowledge and experience. it built up over time.
it’s more about the mode of thinking and how to engage with a problem, than it is about specific “highly skilled” stuff. the skill and experience help/contribute, they refine, they assist in filtering
the reason I make this comment is because I think it’s valuable that anyone who can do the job well gets to do the thing, and that it’s never good to gatekeep people out. let’s not unnecessarily contribute to imposter syndrome
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the astute reader may note a certain part of my comment addressed a particular aspect of this
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You’re the one bringing up popularity in response to a substantial argument. I hope you’re okay…
and upon hearing the lesson, the journeyman went to the pub
Entry-level devs ain’t replacing anyone. One senior dev is going to be doing the work of a whole team
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But when a mid-tier or entry level dev can do 60% of what a senior can do
This simply isn’t how software development skill levels work. You can’t give a tool to a new dev and have them do things experienced devs can do that new devs can’t. You can maybe get faster low tier output (though low tier output demands more review work from experienced devs so the utility of that is questionable). I’m sorry but you clearly don’t understand the topic you’re making these bold claims about.
I think more low tier output would be a disaster.
Even pre AI I had to deal with a project where they shoved testing and compliance at juniors for a long time. What a fucking mess it was. I had to go through every commit mentioning Coverity because they had a junior fixing coverity flagged “issues”. I spent at least 2 days debugging a memory corruption crash caused by such “fix”, and then I had to spend who knows how long reviewing every such “fix”.
And don’t get me started on tests. 200+ tests, of them none caught several regressions in handling of parameters that are shown early in the frigging how-to. Not some obscure corner case, the stuff you immediately run into if you just follow the documentation.
With AI all the numbers would be much larger - more commits “fixing coverity issues” (and worse yet fixing “issues” that LLM sees in code), more so called “tests” that don’t actually flag any real regressions, etc.
half as good as expert human
60% of what a senior can do
is there like a character sheet somewhere so i can know where i fall on this developer spectrum
It’s going to be your INT bonus modifier, but you can get a feat that also adds the WIS modifier
For prolonged coding sessions you do need CON saving throws, but you can get advantage from drinking coffee (once per short rest)
but you can get advantage from drinking coffee (once per short rest)
I must have picked up a feat somewhere because I hit that shit way more than once per short rest
Yeah, the glorious future where every half-as-good-as-expert developer is now only 25% as good as an expert (a level of performance also known as being “completely shit at it”), but he’s writing 10x the amount of unusable shitcode.
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This is a very “nine women can make a baby in one month”.
The idea that there can even be two half as good developers is a misunderstanding of how anything works. If it worked like that, the study would be a dud because people could just run two AIs for 160% productivity.
