It's so early game, is the real problem. My experience so far, has been that it's barely a junior dev. I've met so many in my career that think reading stackoverflow, or watching a youtube video mysteriously makes them an expert. AI reminds me of this sort.

Well anyone can use (prior to AI) a simple linter and learning to code isn't that big a deal. It's learning the pitfalls, the traps, that's the issue. And so far Opus just seems to fall into them again and again. I guess the best way to put it, is that it's not an architect. I sees no big picture, and that's not really a surprise with (compared to a human) an incredibly small context window. When I'm on a project, or working with a codebase, I often have years of "context window". And I have a career of "don't do this" context window.

So what I wonder is, will this be resolved? Will that awareness of larger scope be solved? If that happens, we'll be in another ballpark of competency.

Some companies have massive codebases. Are these companies slowly gaining rot in those codebases, a swiss cheese effect, which eventually will result in collapse? Because I've worked where a bad hire had just this effect over time. And what I worry about isn't using Claude to speed one up, it's the DEV that uses Claude and just "meh" and submits because it passes regression + other tests, and then a manager or code reviewer uses Claude and "meh" because it's a pass too.

I get the point having read much the same from Tesla (and fans) regarding self driving cars that still haven't done half the things that Musk said was just around the corner pending regulators a decade ago and repeatedly since then.

And myself I keep making comparisons between AI and the progress in 90s video games where every minor improvement got called "photo realistic" and then forgotten with the next game engine: https://archive.org/details/nextgen-issue-26

So I'm not gonna say "this is it" when the software quality really matters, and I absolutely won't speak to progress (or lack of it) outside of software.

But I will say "you can look around and easily see small businesses using AI to generate posters, quite a lot of small business software and websites are in the same category: the mistakes are real but increasingly don't matter".

I guess it's important who one hears this from.

I just spoke to a fried who is a headhunter and who's been trying to automate his processes for a while (he likes to fiddle and certainly has skills, but he's not an engineer). He kept trying, but it just wasn't good enough.

Now he said with GPT Work and Sol, it worked, but the key point is: all of it suddenly worked.

The problem was one of reliability, of handling edge cases. All previous attempts / model-harness-combinations were too brittle and needed too much observation and fiddling - cheaper to do it yourself.

Now he says "I don't know why I would ever hire a recruiter [the folks doing the cold outreach] again. I can focus on the candidate screening and acquiring projects, everything else is fully automated".

This doesn't come from an engineer or an AI lab, but a technically inclined power user, and I think this is where things get interesting.

It seems to be true this time though; I have observed it myself and heard it from several experienced developers I personally know and respect. It feels like some threshold was crossed with Opus 4.5 and Gpt 5.3, where the models are now able to reliably solve certain classes of problems that were previously unreliable.

Time will tell of course, and it’s early, but inflection points do exist with progress.

Nobody was saying coding agents started working in 2023 or 2024, because the category was defined by Claude Code which was first released in February 2025.

Perhaps the LLM companies need to start hiring true Scotsmen?

Claude 4.5 was it (nov 2025?), without a doubt. It went from frequent hallucinations to highly usable with much less garbage output. If you were making demos of AI tools around this time your demo/pitch/product was saved and you probably looked like a genius.

Yep, the goalposts just keep shifting. In reality: they still don't work well, unless you're content with producing low quality work.

I haven't. Around the start of 2026 is pretty widely mentioned as when they went from "this is broken slop" to "huh this is actually 90% what I would have written", which matches my experience.

I personally hope that AI continues not to result in a noticeable negative impact on employment and that pandemic over-hiring turns out to be the major factor for all of the layoffs.

I'm nervous that the studies which show that so far don't seem to be taking the 2026 improvements in coding and general agents into account.

>programmers and IT were severely overhired during the pandemic

1) I hesitate to believe that losses were disproportionately technical roles as opposed to administrative.

2) Over-hired by what metric? It's well known that hiring never fully recovered after the GFC; was the recruitment post-pandemic just bringing us to parity with where we had been 20 years earlier?

Not to say that I disagree with your following point. The AI overspending and the layoff cost-cutting are not in a direct causal relationship; both are rather symptoms of a common corporate pathology.

I think it's because of the lack of feedback. Humans also can't do much without feedback. E.g. I doubt most people could write 100 lines of code that works first time without even compiling it once.

That early 2025 METR study was particularly interesting because participants self-evaluated themselves as 20% faster, but the measurements showed they were actually 19% slower.

All the reports of productivity since then are self-reported, or using questionable measures such as SLOC and PRs, so it’s reasonable to say that productivity improvements are still unknown.

Unfortunately, METR hasn’t been able to replicate the study because they couldn’t find enough willing participants.

Well… what

Bingo.

  > So that is to say, if they aren’t happy with the price now, how will they feel when it goes up again compared to just keeping a certain headcount?

>This has led to many of them instilling dollar limits or demanding proof of increased productivity (not just output)

They should have done that from the beginning - demanding proof of increased productivity - if that was their goal. otherwise they were not using their brains well enough.

And you doubly don't want to work with them, first because they confused output with productivity at first. and second, because they're parroting the productivity metric.

You only need one guess for whose pockets the productivity benefits go into.

10 . 9 . 8 . 7 . 6 ...

When I was a teenager, a friend had an old gas guzzler from the 70s. I live in a rural area. One time, my car broken, he drove to pick me up to go to College.

This cost him an extra $40, in today's dollars. No, I'm not joking. That thing ate gas like a dry camel drinks water.

This is what Fabel5 feels like. Crazy expensive. 10 minutes work pulled almost $80 is usage credits yesterday. I'd be exceptionally skeptical too, on costs, if I still had the DEV I had last week, but they were also eating that kind of cash on a very-improved, but still used as a linter.

For $200+/hr, or ~$400k/year, I'd want to see a tripling of output at least. In a lot of US markets, you can hire 3 junior devs for that.

Yes, there are cheaper options. Opus, etc. But it's really over-priced, and frankly I think the real gold now is making open models fully functional. Anyone predicating their business upon tie-in with the big boys is just going to fail, hard.

If decision-makers put up a front of recruiters and talent acquisition "specialists", don't they send a very explicit message that going past those is unwelcome and won't be considered?

yeah the lead lecturer on my data engineering masters once told us about a job posting he saw asking for 8 years of Hadoop experience, even though Hadoop had only been publicly available for 5 years at the time.

it's often HR / hiring managers throwing some numbers into a text document based on what they've heard is important for the role, not what you'll actually need for the job.

similarly, something like "has previous experience with kubernetes" doesn't usually translate to "knows absolutely everything there is to know about kubernetes". it means "you've used it at least once, ideally more, but can at least talk about when / how you used it / what problems it solved and could probably get up to speed on it fairly quickly when you join and/or in the time before you join" (kinda writing this last bit about an interesting job posting i saw that i've been talking myself down on and i really ought to be doing the opposite).

My favorite in this regard is this story: https://x.com/tiangolo/status/1281946592459853830?lang=en

Sebastián Ramírez seeing a job requiring 4 years of experience with FastAPI, the library he created 1.5 years before that posting.

A 10x engineer only needs about five months of experience.

So, leave college/uni with your "Desmond" (1) in comparative pornography in Feb 2026, buy a PC/Apple and by now you will be writing Windows Entra 2027 on your own.

Profit!

(1) Tutu - geddit!

Wow, fuck.

Literally some minutes later, i scrolled down below my above comment.

And saw this one.

https://news.ycombinator.com/item?id=49053201

Which doesn't validate mine, but agrees with what I said.

Except that it was posted about one hour before mine.

go figure.

I think Sturgeon's law would tell us that everything will stay about the same.

But in reality, a lot of corporate software exists just because there are plenty of companies who are afraid of owning code. They don't want to maintain any in-house coding skills, and therefore are willing to buy literally any vaguely-relevant CRUD app that the manager heard about at the conference. I don't think replacing that class of software with vibe coded alternatives will be any worse, because the bar is starting on the floor.

There are entire software categories that consist entirely of code that is only one or two evolutionary steps away from some engineer's spreadsheet originally written in 1995. One fine example I work with has changed its backend database 3 times in the past 4 years. Their most recent decision to use mongodb came with the questionable decision to store json as a raw string literals complete with bizarre escaping inside a database literally designed to store json-shaped-objects.

I don't think Opus could store data that poorly, even if the end user prompting it didn't know what they were doing.

One of the upside I can foresee is the return of single payment software. No one is going to be paying subscriptions when they can LLM themselves, but paying someone else to LLM for them would let them shrug off accountability for malfunctions

To me, this is inline w the book BULLSHIT JOBS, and that class of job that was really like a few hours a week but 40 hrs pay. That type of job should be automated and the person removed. The exception is going to the person who complained to management that it’s a 2 hr a week job…. Give me more work.

We got the thumbs up from management last week.

may i join ?

Probably both. We were already hitting limits in terms of finding software that could generate returns; without public funding or enormous regulation the possibility of finding new jobs with a degree is lower than it's been in a while.

Seems like all companies think that their products are good enough and can’t offer more, as they always want to remove people instead of offering better and bigger products.

I'm surprised the layoffs worldwide hasn't produced more entrepreneurs building their own software product.

No one will use it.