@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.
The reward mechanism in the brain is triggered when you bet. I think it also triggers a second time when you do win, but I’m not sure. So, yeah, sometimes the LLM spits out something good, and your brain rewards you already when you ask it. Hence, you probably do feel better, because you constantly get hits dopamine.
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.
Most people want to do the least possible work with the least possible effort and AI is the vehicle for that. They say whatever words make AI sound good. There’s no reason to take their words at face value.
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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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.
the ml in lemmy.ml stands for marxism-leninism
wait til you find out what the ml does stand for, it’s a real trip (and it sure as fuck ain’t Mali)
And generate shit code
I have an LLM usage mandate in my performance review now. I can’t trust it to do anything important, so I’ll get it to do incredibly noddy things like deleting a clause (that I literally always have highlighted) or generate documentation that’s more long-winded than just reading the code and then go to the bathroom while it happens.
Gotta justify all that money that they have just spent without any trials, testing or end user input.
Are you fucking serious?
this sort of bloody stupid metric is widespread, i’ve heard about it widely
goodhart’s law’s zombie era
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.
For each time saved, you’re having that one kink that will slow you down by a fuck ton, something that AI just can’t get right, something that takes ai 5 hours to fix but would’ve taken you 10-20 to write from scratch
@dgerard I normally consider myself a 10x developer. With the 10x speedup of AI I now consider myself a 100x developer. I can replace an entire small business worth of developers with just myself and my LLM bot assistance. Just pay me $100 million up front no strings and I’ll prove it to you! /s
Something something grindset mindset
Mark Zuckerberg would like to know your location
Don’t be silly. Mark Zuckerberg already knows our location.
I have the deal of a lifetime for you.
I represent a group of investors in possession of a truly unique NFT that has been recently valued at over $100M. We will invest this NFT in your 100x business - in return you transfer us the difference between the $100M investment and the excess value of the NFT. Standard rich people stuff, don’t worry about it.
Let me know when you’re ready to unlock your 100x potential and I’ll make our investment available via a suitable escrow service.
@Silic0n_Alph4 Sold! LOL.
@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.
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.
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
Here’s a LW site dev whining about the study, he was in it and i think he thinks it was unfair to AI
There a complete lack of introspection. It seems like the obvious conclusion to draw from a study showing people’s subjective estimates of their productivity with LLMs were the exact opposite of right would inspire him to question his subjectively felt intuitions and experience but instead he doubles down and insists the study must be wrong and surely with the latest model and best use of it it would be a big improvement.
I think if people are citing in another 3 months time, they’ll be making a mistake
In 3 months they’ll think they’re 40% faster while being 38% slower. And sometime in 2026 they will be exactly 100% slower - the moment referred to as “technological singularity”.
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.
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.
I wish I could make more people both know about, and understand, Goodhart’s law
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
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.
5% “coding”
95% cleanup
