TechTakes
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@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 @[email protected] 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.
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.
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.
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!"
And generate shit code
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)
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.