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I was worried this time last year that by this time this year, companies would have slashed their engineering teams down to a handful and everything would be driven by mostly autonomous agents with human guidance. But it just hasn't happened. Do I write all my code with an agent now? Yes. Can you just give an agent a desired outcome and let it work, unsupervised? Absolutely not. I can produce more code than I used to, but if I want it to be good, to be stable, to do what the product manager and designers want, it's only about 2 to 3 times more code than before. And that productivity is impacted by the fact that I'm reviewing 2 to 3 times more code than before (and you have to review, even more so now than before, because if you just let opus or gpt 5 do its thing, you'll get some terrible results, and I've found a lot of engineers on my team are just letting it do it's thing without a lot of iteration).
The thing is: I could produce 2-3 times as much code as before _without_ an LLM, if I didn't care about my colleagues' ability to review my output properly.
Lines of code are a liability, not an asset. You want as few of them as you can get away with, without compromising the actual asset: the functionality.
A huge part of the job of Software Engineering is producing the right amount of code at the right time.
>I was worried this time last year that by this time this year, companies would have slashed their engineering teams down to a handful and everything would be driven by mostly autonomous agents with human guidance. But it just hasn't happened.
I find this somewhat puzzling. I thought things were moving quickly, but at this time last year I couldn't even get Claude (using Cursor) to spin me up a service skeleton that would compile, let alone do anything meaningful.
I know it feels like a long time somehow, but it was only between November and February that things started to actually somewhat work without significant hand holding. Even now, it seems like we're still figuring out how to fully leverage the current models and tooling, even in organizations that have largely gotten on board.
Do I write all my code with an agent now? Yes. Can you just give an agent a desired outcome and let it work, unsupervised? Absolutely not.
I strongly suspect that developers moving from writing code to managing agents to write code for them is very similar to developers moving into leadership and management roles and managing ICs to write code for them.
Some devs just 'get it' and thrive, leading a team really well and building a great culture. But a lot of them don't, especially if they don't get the support necessary to understand what changes when you move from IC to manager. If the team (or agent swarm) isn't performing well it often isn't a problem with them. It's a problem with the new manager still trying to stay on top of everything and micromanaging all the things. Alternatively, the new manager is completely hands off and only appears at a check-in point (one-to-one, agent completes a task, etc) where they crap on the work and get cross.
I have no evidence for this, but I'd guess that putting developers through some sort of management training would make them much better at using agentic swarms.
> Can you just give an agent a desired outcome and let it work, unsupervised? Absolutely not.
Ignoring instructions - whether in AGENTS.md or my prompt - is the worst of it, and it routinely happens. It just waives things that I explicitly told it to do as part of the design.
Vibe coders (in the true sense, zero oversight) claim that you just need to prompt it carefully. That's completely untrue when faced with your careful prompt being ignored.
I even have "don't overrule me without asking" in my global AGENTS.md, and it simply doesn't do that.
Companies are putting a ton of effort into getting to that point of having agents do the work unsupervised. Whoever gets there first is going to be the winner.
I personally don't think it's possible and I haven't written a line of code since Sept 2025.
There's an AI psychosis going on right now, especially among the execs or management class, and we all gotta nod our heads in agreement and burn through tokens.
I'm really struggling to get an agent to write code I'm happy with. It's mostly pretty awful.
I've a fairly simple c# coding style. But simple is proving a bit more difficult to convey than I thought.
I get it to produce code. I then have to spend along time convincing myself it's correct. If I don't I end up embarrassing myself when a coworker reviews it, questions it and it's obvious I don't properly understand it.
This is really starting to screw with me mentally. It's like everyone in the world is saying they can fly by flapping their arms (dark factories). When I try I just stay in the same spot burning a lot of energy.
Measuring software performance by lines of code is like measuring aircraft performance by weight.
I have no idea why everyone seems to have forgotten this simple fact over the last four years.
"companies would have slashed their engineering teams down to a handful and everything would be driven by mostly autonomous agents with human guidance. But it just hasn't happened. "
It never was going to happen.
Always the same story: https://en.wikipedia.org/wiki/Gartner_hype_cycle#/media/File...
> I was worried this time last year that by this time this year, companies would have slashed their engineering teams down to a handful and everything would be driven by mostly autonomous agents with human guidance. But it just hasn't happened.
Amara’s law: We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.
This continues to be applied to AI where people think is going to be next 12 to 18 months. Changes are coming but certainly not at the rate Zuckerberg and most people are thinking.
This is a thinner TechCrunch rewrite of this Reuters story: https://finance.yahoo.com/technology/ai/articles/exclusive-z...
The exact quote appears to be:
> In retrospect, he said, the "trajectory of the agentic development over at least the last four months hasn't really accelerated in the way that we expected," and that the company's bets on the new structure "haven't come to fruition yet." Zuckerberg was referring to AI agents, automated systems that can execute tasks on behalf of a user.
Hard to guess exactly what he means by "trajectory of the agentic development" but my best guess is that he means that Meta's own internal efforts to improve the agent (aka longer form tool-using) capabilities of their own in-house models hasn't improved to the point that they can drive an agent harness like Codex or Claude Code in a comparable manner to the best OpenAI and Anthropic models.
At a further guess, that was part of their goal in reassigning large numbers of employees to help label data for their AI efforts.
The gap between "useful chatbot" and "useful agent" is way bigger than people realize. A chatbot can be wrong 10% of the time and still help you. An agent that's wrong 10% of the time is sending bad emails and making wrong API calls with no one checking.
> he expects that the social media giant will begin to experience more significant benefits from its AI investments within the next three to six months.
He is hallucinating just like AI, and unable to come to terms with the facts on the ground. Meta has lost plot about 5 years back - with metaverse, VR, glasses and AI. They should sit back and think with a calm head, about what exactly their core product is. Unfortunately there is none, except a few acquired ones: whatsapp and instagram.
Having agents is like going from walking to having a bicycle.
Business executives look at this and think "at this rate of progress we'll have self-driving cars in a few years!" and start making serious plans for that world.
In reality I think we're going to be riding bikes for a long time. That situation of increased individual contributor productivity makes engineers more valuable, and increases the utility of engineers rather than making them a burden on your budget.
Thus, cutting headcount right as they had huge potential to become vastly more productive was a stupid move. It's an admission that you don't know how to manage people effectively, which is embarrassing when you're paid mountains of money for your management skills.
I think what everyone underestimated was the absolute bonkers amount of compute it will take and how that compute must scale in order to keep up with larger and larger models.
The failure that is llama4 needs to be studied. Meta was kicking ass with llama3.x and then something happened, something really went wrong. what happened between that time and llama4? I think it happened after llama3.1, llama3.2 was nothing to write home about. We need the gossips, maybe a book
There's a disconnect between measured productivity and "anecdotal" productivity. I love this chart because it also demonstrates one of the most effective ways to increase productivity: simply reducing the workforce.
The last two years have been perfect for accumulating tech debt.
2023 you would have probably implemented your Agents with LangChain and RAG
2025 you'd use MCP and OpenAI/Anthropic Agent SDK.
2027 you will use a workspace frameworks (Amazon, Microsoft) sensor libraries and world models.
Agents are a fantastic generational technologies, but in mid-2026 the environment they are operating in is quickly changing.
The only way forward is to stay agile, understand model and vendor risk.
Who cares what Zuckerberg says about AI agents? He is a PHP developer from the early '00s who got lucky with Facebook. He's not an AI scientist or an AI researcher. What authority does he have to speak on the future of AI agents? Morale at his company is at an ATL, and that says more about his leadership skills he'd better off focusing on, otherwise the agents might replace him soon.
My diagnosis is.. You are working with people. Smart ones at that, who have been working for a very long time in their own, niche, specific way. To assume all engineers will become AI-pilled like you and hop on Claude Code whenever asked is the wrong approach. You can make the greatest tools, but if it doesn't fit in the behaviour and the way of working of the engineer, they will simply discard it.
I see this issue with clients and prospects all the time. A client's team of 5 produces 1 foobar widget in 2 weeks. That's 50 human days spent. Then, someone demonstrates the same thing can be produced (at an equal ot higher level of quality, mind you) with AI in 2 hours. Management might celebrate but teams will continue programming by hand as they always have, now asking ChatGPT about their build tool errors instead of using Stack Overflow.
Handing out tools and telling them it's cool is not enough. You'll need to understand, work with, and guide the engineering teams properly step by step. You'll have to change their behaviour. That does not happen overnight. Unfortunately the present approach is to drop the people who don't perform in the new era of AI-assisted software engineering. That is not the right approach in my eyes.
Can't think of a better poster child of complete corporate waste that benefits no one whose assets should be seized and redistributed to the masses.
For the amount that Meta wastes on LLM spending you can pay for things like universal childcare, public community college, and providing free lunch to all public students.
If you care about things like money, look up the dollar returns on feeding children during their development or when you tell families they don't have be an economic burden for simply existing.
A better world is possible.
If AI was a productivity boon: wouldn't a company employ the same or more employees to capture more market share at a competitive edge. Shedding employees because they are more efficient seems like shooting yourself in the foot to try and stand in the same spot in a race.
AI should have caused a job market boon: because less skilled employees would have been more hirable/useful. That this is not the case leads me to suspect that AI is an excuse to reduce employee count, but not the root cause.
I think that over long developers will desperately be needed to handle AI.
In my experience, within weeks now concepts written in stone get shattered and the next paradigm has to be used in order to max out AI in an development environment.
What is the case for AI? To handle basic work? Augment the work? Add work?
Why I think dev will be in a good spot if they adapt is the simple fact, that while laymen are using ChatGPT etc. every day, this is like driving a Tesla vs a formula 1 car.
If you take ChatGPT away from the laymen, they are helpless with IT. Devs aren't.
AI isn't static, and every turn evolves into complexity, only devs may handle when they adapt to frequent paradigm shifts and go into high level mode.
It will be again the interface between men and machine, laymen and AI. The gap won't close anytime as expected (The programming manager - remember 6 month ago?), but widens more and more.
What I see is that in day to day work many services have arms race with AI updates. The managers are more and more overwhelmed by the workload but how to automate systems is still devs' area to shine.
The business case is still hidden and unclear, but only one aspect is clear to me: low level programming is mostly configuration work now and bug fixing for AI very seldomly now.
I feel as thought Meta, compared to other tech giants, have a vested interest in saying that AI failed, as they are the only major tech company that has almost unequivocally lost the AI race.
No one needs Meta AI. They have missed the boat with chatbots / agents / harnesses like Claude Code.
Can you picture anyone you know stopping using the AI services they currently use for an AI service provided by Meta?
They have such huge opportunities in selling access to their data centres to Anthropic etc, and improving their own ad models for better targeted adds (using their proprietary data and their own infra!), it is maddening to watch them try to make SOTA LLM models and harnesses no one will ever use.
Zuckerberg is proof you only need to get really lucky once. He's basically flailed at leading facebook ever since, going all in on monumentally dumb bets and erratically making headcount and project decisions, and still he somehow keeps getting richer.
This article is at least the sixth restatement of a single Reuters article that has been posted here.
I wonder what will be the next big thing for Zuck after metaverse failure and now AI coming to nothing? Perpetual motion machines?
Aka I thought the stuff that these other guys are doing was not so difficult. No one can replace me, of course.
Many such cases.
Have they tried feeding macadamia nuts to the llama?
> said a review of a recent data security incident with the company's controversial mouse-tracking software indicated that no employee data was included in AI training.
That's... not quite right. The employee data is used in AI training and is intended to be used this way. But despite not correctly ACLing the data for a couple weeks, it is believed it was not accessed inappropriately.
The company that helps connect kids with the adults who want to harm them is having a hard time replacing humans? Shocking.
Maybe Zuck is doing the soft walk back so he can justify a few more H1Bs now that he laid off lots of expensive Americans.
So what happened to Meta after those successful llama 3 model releases? They really made competing models back then. If felt like they have right people, strategy and good results. Now it feels they have neither of those…
You'd have thought that Zuck's previous failures to make the things he dreams about (e.g. Metaverse, decent in-house AI) materialize might have made him a bit more cautious about betting the farm on things that don't exist, especially when he's expecting someone else (the AI agent folks) to make it happen!
I suppose you have to admire the conviction: I'll fire my developers today because REAL SOON NOW I'll be able to replace them with AGI!
Why don’t they just got Claude Fable to do it for them? Are they stupid?
I wonder when he'll admit his hopes were baseless
> At the time, he said, executives were "super optimistic" about tools like Claude Code from AI startup Anthropic.
Some guy in sales at Anthropic has a new yacht though.
I can't imagine they'd ever get enough people to opt-in to mouse tracking to generate enough data for their model training. It's either a DOA AI project, employees will be pressured into accepting it (making it part of their review), or their managers will accept the monitoring on their behalf.
If a Meta employee screws up a major project, what happens? What will happen to the executives behind these mass firings and realignment - executives of one of the very top SV companies whose job is dealing with the landscape of disruptive technology development and overreacted to the latest thing? What is the standard for them?
it is amazing that meta continues to burn money and keep afloat. ads DO really make money, especially when they are going to overtake google in this [1].
to all the critics, i would suggest letting him/them cook. the snowden-era privacy concerns was exactly around ai getting trained or using personal data, and they have a treasure trove of it.
their money dump do sometimes also spend money on r&d unrelated to the current mindhive topics. we never know what the scatterbrain approach may give birth to tomorrow.
do be critical and vocal on how they squeeze money out of other areas or how they increase their revenue by ruining our lives instead.
with coding, you have sort of a framework for doing it right, if you have good specs, good testing practices, strict grounding in expected results deterministically, good linting, etc... this is much easier to automate with AI for the coding part within that assuming you did your homework around it... i don't have experience with all the business layers but it seems a bit more nuanced and fuzzy as you get away from that "harness" of sorts as it doesn't have to work in the same way as code for execution and evaluation... and even if code works, it still needs tastemakers in the final ok. maybe the taste maker ability still needs a lot of work/scale to be feasible, idk, like its still earlier than later on that. maybe Elon already cracked this to an extent given his automation in various companies.
Reminder: the "expected" result is replaced all programmers and white collar employees. Even they don't necessarily state it explicitly, that's what is in their minds.
Anything less than that is slower than expected.
By "AI agent development" does he mean using agents and such for in-house coding? Or does he mean their initiative to train their own agentic model based on the data he's having a bunch of employees generate?
AI hype comes quickly, and goes with the wind quickly as well.
built an agent to handle my email triage. it now flags every message as "needs human review" and sends me a daily summary of how overwhelmed it is.
Who is the genius who told him development will get faster?
The man can't catch a break!
Facebook is already renting out their excess GPU capacity. Nvidia is giving out GPU capacity for investment stakes in startups. OpenAI is trying to get the government to take a 5% stake and needs to make the same amount of revenue within 3 years as Google does now or else they're going to default on their payments to Oracle. It may not be the same as the 'dark fiber' from the Dot-com bubble but it sure seems similar. Especially when this hardware is purchased ahead of delivery and ages so quickly it's not even clear it will be reusable after a few years. It's the scale of the investment in this stuff that is the issue. In 3 years, AI spending is off the charts compared to the railway bubble, Dot-com bubble, Roaring 20s, or really any other bubble. I don't think it's going to end well.
Isn't he just trying to tank competitors prices? Try to burst the bubble in a race he is way behind?