Open source has had a QA problem pretty much its entire life... not in the sense that it stinks necessarily, but in that getting it at all is a challenge and was in many projects probably already the blocker to further progress.
One wonders if what is happening here is just that even in the software space, where the fluidity and flexibility is maximized as we work with nearly entirely digital constructs, that once we burn through the dry tinder of "all the stuff we know we needed but didn't have the coding time to get to" and the frontier of "work to do" advance on all fronts to "some sort of human or real-world blocker", it may just turn out that the steady state improvement in productivity after accounting for Amdahl's Law, even when code is "nearly free", is only a maybe 2x or 3x improvement after all. If this is true, goodness help the financial bubble which is assuming that something like 5x or 10x indefinitely is a lower bound, if even in the best possible domain for AI that's all we really get.
It doesn't seem like the SWE labor market has been shedding anywhere near that order of magnitude of jobs (there are about 1.7 million SWEs in the USA alone) or that companies going heavy into AI are boosting revenue significantly.
I think all things considered we're only getting a single digit percentage total productivity increase.
At most places I've worked, the "designing and writing code" part (basically the part that LLMs can do) was maybe 5-15% of the calendar time it took to actually get the software out into the market. The remaining 85-95% of the time was spent on squishy people-things like aligning stakeholders, getting executive buy-in, working with x-functional teams, getting priorities aligned so one team wasn't done in 30 minutes while the other team took 30 days, doing security reviews, doing privacy reviews, doing legal reviews, doing QA and verification, lining up marketing, educating salespeople, waiting for people to get back from vacation, waiting for people to get back from sick leave, waiting for people to respond to their E-mails, waiting for people to click "approved" on various internal review sites, doing final reviews with executives so they know what their company is doing. These other things take up the vast majority of the time it takes to release a feature. LLMs are only speeding up the relatively tiny 'code writing' part.
You point all these new software but some of them are literally only a few months to a few weeks old and complaining that they aren't up to standard yet. Even if LLMs didn't get any better than they are right now, these projects have barely even begun, and there is plenty of time and resources to build them up.
I've written a bunch of cool new software with LLMs in my spare time -- are you sure you even have a way to notice all the new cool software that exists?
This might be a problem in itself. I find myself unable to have the time to even investigate new software because even newer software with even more features comes around a week later. I bookmark so many Show HNs that I'm impressed by and only ever go back to a rare few.
I personally (no LLM) wrote some open source software a few years ago that maybe has a dozen to a hundred users and somebody used an LLM to port it to MacOS and Linux.
But even so, the entire ecosystem has been changing over this entire time. You might be using an entirely different set of LLM tools now and/or those tools themselves have gotten a lot better and easier to use.
My life has been improved immeasurably (our home is filled with attachments and affordances built on-demand by Claude), and no new software was created that anyone else would see. It is entirely possible that these tools fail to create a Photoshop/Blender replacement and yet replace Photoshop/Blender.
My wife started out building in Blender[1] but these days even she uses Claude Code and mostly ideates. The nature of LLMs might not be "they can build you something better than Photoshop in a day" but that "where we're going we don't need roads".
0: https://wiki.roshangeorge.dev/w/Blog/2026-01-11/Modeling_Wit...
1: https://wiki.roshangeorge.dev/w/Blog/2026-01-15/Modeling_Wit...
I wish!
The quality of commercial software has really gone downhill the past decade. Some of it may be AI, but it has likely more to do with the fact that fewer and fewer want to pay for QA.
On the endless framework treadmill, money is better spent going forward and changing things.
A lot of these harnesses and mcps themselves are built with llms.
No matter what you think about it, it's impressive what the folk at Omarchy[1] have been doing with LLMs.
From what I can see, it’s just a bunch of defaults pre-installed on top of Linux. Some of the defaults they use like Proton is far more complex and impressive than their entire distro , and that was built before agents.
Then read Omarchy news.
"ChatGPT, list the files in this directory. use ls"
vs
"ChatGPT, list the files in this directory. no utility exists but here's a hexdump of the hard drive"
the AI might muddle through with option #2, but #1 is way more efficient
It's here already, but not at a global scale.
You can pick any application you pay for, but only use 10% of the features of, and create a bespoke version that only has that 10% in it. It'll take you a day to get an MVP and maybe a week or two for it to be "good enough".
I would say Photocraft is around 75% of GIMP or Affinity level and already better than both in some ways, like speed and memory usage. This is less than a month after first release and if you remember than one you know it was rough.
Of course the last 10 will be the hardest, but 90% of Photoshop for free with native PSD and lower system requirements is a win no matter how you put it.
I think the models are good at this because we can just set them loose and they can permute through their training and because a lot of things are common patterns, this can work, but is also generating massive amounts of slop that people are dumping on maintainers who are getting overwhelmed by it. I really want to know how many failed iterations a successful run cost.
One unanswered question is if this is economical. Like, if this is just gobs of money and is unsustainable, what did we just spend the last few years doing? I think these things have value, but not like this.
[ 1 ] https://pixellect.app/