Cutting people because of AI makes no sense, you know these people are good without AI, you'd want to keep them! Freeze the constant over-hiring instead, and take care of the people you know aren't lobotomized yet, and train them if needed. I'm seeing so much shedding of knowledge workers though, even though AI clearly isn't ready to replace people, just ready to augment them currently, that it looks like looney-tunes currently.
The major issue, is that once people are more productive with AI, you are able to replace people because less of them are required.
You see this in enterprise consulting, wiht the increase in cloud, serverless, SaaS/iPaaS, low code/no code, content generation and translations, followed by AI agent orchestration, the teams can be reduced down to about 1/3 of what they used to be.
It isn't as if there are enough projects around to keep the other 2/3 busy, so eventually when there are enough of those people on bench they have to find something else.
This sounds like an attempt to rationalize the fact that your business isn't that effective, otherwise adding more people would result in making more money.
> It isn't as if there are enough projects around to keep the other 2/3 busy
I've never worked at any company where there was any limit to the work to be done. Sales people don't give a shit what your product can do, only what they can sell, and they never sleep.
You can always find things to do but how much of that work has a positive ROI, or contributes to your business? You always have some bottlenecks, let's say implementing features was your bottleneck before AI, and you had a team of 15 product engineers with a 1y roadmap. With Claude Code a team of 5 was able to get that done in let's say 3 months. You don't magically come up with 9 months of work for 15 people right away. And your bottleneck will now be sales or something else, but your engineers won't convert to becoming sales people (or at least not all of them), and you might only need 1-2 more sales people, not 15.
>I've never worked at any company where there was any limit to the work to be done. Sales people don't give a shit what your product can do, only what they can sell, and they never sleep.
The issue is how much of that work is "valuable" in the sense = makes money.
I have both been in projects and seen projects which were canceled once it turned out they didn't make money (bad sales? bad product? bad market fit? a bit of everything?). This you can only afford when you have money to spare (= with debts? high profits...?).
With the interest rates so high, how can a company justify hiring dozens/hundreds of people more? It's a risk, and what I am seeing now is that companies are shrinking left and right to focus on the business that makes money and reduce headcount on what they believe doesn't make money at all, or it's a cost too high for their "long term strategy" or whatever. Right now the only metrics that they are caring about is EBIDTA. They don't even care anymore about ARR, they are becoming irrelevant as long as they stay within a range (we want 20% increase, but we're ok with 5%).
The AI will replace everything and everyone is working out pretty well for Anthropic/OpenAI, though.
Predicting which projects will be valuable, directing resources in their direction, and making sure the right people are doing the right work with as few distractions as possible is the definition of high quality management and leadership.
Most managers are mediocre, and many are poor. Some are lucky for one or two projects but can't keep it up consistently.
Companies with a lot of wealth often scattershot random projects - some of which are directly competitive - in the hope that one will stick.
The people who have the insight and intuition to skip this and hit the mark directly are incredibly rare.
A lot of business culture is a set of cargo cult "solutions" that pretend to address this problem.
Only if all roles in a company are bottlenecked in the same way.
Example: natural monopoly in some geographically-locked domain. Just to grab an example. You have 150 people in the field, can't let them go because the company still needs hands and eyes on the ground. You have 15 people in some other, paper-pushing department. Thanks to AI advances, you only need 10 of those now.
> This sounds like an attempt to rationalize the fact that your business isn't that effective, otherwise adding more people would result in making more money.
Yes, or that businesses are expecting a slow down in the economy that hinders their ability to sell (i.e. their customers are going to cutback on spending)
This was the case last year (or maybe it was the year before) where technology companies saw their customers reducing spend and tightening belts.
The current economy feels hard to figure out, in that the market keeps going up but so is inflation and the struggle of the everyday American at least.
Perhaps that is leading technology companies to be more conservative in how much they produce.
But if we're assuming that AI is highly effective, shouldn't that lead to short-term growth in the economy as inflation drops? Shouldn't people then be expected to spend even more?
> This sounds like an attempt to rationalize the fact that your business isn't that effective,
That's actually it. The part that can be sped up with AI don't change how slow everything else still takes. If you need 2 weeks to see the results of a change before AI, you still need that after AI.
Basically, your business is not keeping pace with development.
"I've never worked at any company where there was any limit to the work to be done." Then you live in a bubble. Many organisations are restricted in available profitable work to be done, by many factors. Capital & cashflow, capacity & physical limits, demand, regulation & licensing, supply chains & inputs, management bandwidth, risk tolerance, access to credit, etc. etc.
I’ve never worked anywhere where lack of work or projects was the bottleneck. Time, headcount, and budget were always the constraints.
Even in cost centers like IT or ops, there’s usually an endless backlog of work, technical debt, support requests, and improvements that never get prioritized because resources are limited.
And resources are limited because the cost/benefit ratio for adding more resources just isn't there for most of what's on the backlog. (Or at least that's what management thinks.)
Just because the cost/benefit ratio improves a bit in one area doesn't mean that all of a sudden all projects on the backlog become worthwhile.
> It isn't as if there are enough projects around to keep the other 2/3 busy, so eventually when there are enough of those people on bench they have to find something else.
Eh, are they doing that though?
Anecdotally, firing people “on the bench” isn't whats happening.
Read the tweets. Listen to people still working at these big corps. They are gutting teams and pushing more work onto people because they believe they can be more productive, not because they are.
Lets that sink in.
People are being made redundant on the basis that leadership believes that in the future they will have an over capacity and theyre cutting early to avoid the bench scenario.
It is speculative.
What this article is arguing, is that, that is stupid.
If, in the future, you need to spin up new initiatives, youve screwed yourself by disposing of your excess capacity in the magical hope that your current capacity will magically increase itself by … spending more money on tokens.
Its just nonsense.
AI is just an excuse for poor historical decisions and unfortunate global economic conditions.
The “cuts due to AI” will be real. There will be people sitting idle as the models improve and people learn to use them better.
… but right now?
they're not. Im not. My friends arent. My former work mates arent. The people left at these companies arent. The people being cut werent (except perhaps, at meta)
In consulting firing people “on the bench” happens regularly if the sales pipeline cannot keep everyone busy, there is only so much agencies pay from their own pocket if there are no outsourcing deals landing.
In some of those well known offshoring companies, being on bench automatically means a downcut on the salary as cost measure.
If you're increasing productivity, you should be doing more and growing, yes? If you're cutting payroll costs and trying to have the same level of capacity...your business sucks and you deserve your stock tanking.
Layoffs are a strong signal that a business is not investing in growth and is just trying to wring more profit from the same thing. If investors were rational, they'd walk away.
Maybe replacing the expensive C-suite with an LLM would help make better, growth-oriented decisions.
> Layoffs are a strong signal that a business is not investing in growth and is just trying to wring more profit from the same thing. If investors were rational, they'd walk away.
Not always. A buggy whip maker in 1920 should be laying off people. No amount of investment in buggy whips will bring that market back.
A layoff is saying that the investment will not pay off. So long as the company is cutting the right things they are good. Many layoffs are not done with a proper cut of the work do be done and so are bad, but that doesn't mean they are always bad.
Yes! Not every business is worth investing in, even if it's currently a cash cow. Often it's better to return money to shareholders, so they can decide how to further deploy the resources.
I think the issue is that at any given point the work required to fire a 100-200k engineer is less than making that engineer do work to make you that much.
If you're growing obviously it's stupid to fire but if you have plateau'd the easiest gain is to trim the fat, so to speak. Also once a company is acquired by a private fund, everyone becomes a title and a number in a spreadsheet, that's all.
The rational thing is to analyze the opportunity cost of the investment, which is dependent on the always fluctuating prices.
Some businesses can grow, some cannot grow, some grow at different rates. The risk adjusted (subjective) prices determine whether or not an investor should walk away.
Again, shortsighted. There's no reason a business has to have a single product. If you run out of customers for cars, you make HVAC and front end loaders.
A lot of companies simply have no direction and aren't looking to build new products. They had a success, rotated in some myopic execs, flipped into rent-seeking mode and are trying to wring more cash out of the same progressive enshittified product.
Generally you can only profitably expand into adjacent products. Making and selling cars and HVACs are completely different, meaning that your expansion will be starting from zero knowledge. Furthermore, the sales channel of HVACs, sales strategies, etc. is not likely to have much in common with that for cars, so you are essentially creating a whole new startup company. (In the case of HVACs, it would be a startup in a commodity market, which would make no sense, because commodity markets have no real profits.) Doing one thing well is not just Unix philosophy, it is also a sound business strategy. Of course, usually adjacent things that could be done well suggest themselves, but often there is a limit to these.
Perhaps you've heard of Mitsubishi, Toyota Group or Samsung? Notably, Mitsubishi is involved in making cars, HVAC and heavy equipment.
Or, for that matter, Apple. If they subscribed to that philosophy, the iPhone wouldn't exist. Honestly, they would have kept trying to make the Apple II.
we're not taking into consideration the new bottleneck: product growth. imo it's the growth/expansion of the product that creates new work and opportunities for more work. at the moment, product growth is human-driven--because it's a risk to take a product in any direction, and whoever makes it has to bear the full responsibility. ideas that cause product growth are still generated by humans (and rightly so), perhaps also augmented by ai.
there's also what the market is ready for. we've said that some products failed because they were ahead of their time. it's even more true now where the power of ai, ai productivity, etc could take the product far beyond the markets expectation. what does that lead to? the deliberate slow rate of growth means power/potentials have to be controlled somewhat. so even without hiring, if ai is adopted as a first-class tool within the organization, there will be surplus resources that need to be shed somehow.
On the scale of a company, augmenting is replacing. If a worker plus AI can do the work of two workers without AI (but cheaper), you go for that; and it doesn't matter how good or bad AI is without the human.
The point is if a worker plus AI can do the work of two workers without AI, then why not keep both workers and have them both use AI to have the equivalent of four non-assisted workers?
Because you don’t have enough work that really needs doing, at least in that particular area. You cut engineers because the bottleneck to increased revenue isn’t software features or bugs, it’s marketing/sales; human beings’ limited attention for which there is now more competition than ever; and customers’ available funds.
ETA: this is sometimes (though not always) very different for a mature company than an early stage startup.
Ha! I’d never thought about it like that but…yeah.
I suspect another big part of it is that marketing and sales are relatively easy to measure and to scale.
You can hire one, two, or three new salespeople and expect that revenue will change more or less proportionately. Fixing (or ignoring) a handful issues doesn’t scale so smoothly—-there are jumps where the product suddenly seems much better/worse.
Because the entire structure of the business is designed for approximately the amount of work it currently does and likely has no particular immediate use for twice as much work in most departments.
Your experience of how the world works is usually because of what work you have done. You can't grow twice as many crops, sell twice as many groceries, drive twice as many busses, because of AI - fundamentally there's a consumption problem as well.
Many businesses are not bottlenecked by processes that are computer based.
But the firms in the headlines doing layoffs after layoffs aren't growing crops, selling groceries, or driving busses... They're knowledge work roles in companies selling intangible products and services. It's large corporations doing this much more than SMBs.
They’re also the ones constantly hiring and recruiting because internally nearly everyone benefits to having more people “under them”, and there’s a massive HR/Talent team that doesn’t go into hibernation after a 20% workforce reduction. Organizations want to grow, not because they need to but because it’s in the best interest of nearly all individuals still on the inside.
That's why it's so important that people get some stock compensation, so that when the stock goes up when they finally fire people the incentives are aligned.
And I’m sure those companies also have “backlogs" due to limited labor/labor costs. There are always shelves to face, vehicles with deferred maintenance, and so on.
Obviously, there are limits: I’m not sure what my local grocery store or bus line would do with 100 new workers, but I have no doubt they could put a few people to work right away.
Well, but they aren't doing so right now, because labour has costs.
If your existing labour suddenly gets more productive, there's still a trade-off between cost and benefit to be made. And it would be a great coincidence if the optimal trade-off were exactly at the same headcount as the old trade-off under the old productivity figures.
It's more likely that the optimal trade-off for the business under the new conditions is at some other headcount.
I think you're viewing this from the perspective of someone who has a functioning brain and plentiful concepts and ideas that aren't being built because you're labour-constrained. Companies like Meta simply don't have productive uses for all of that human + AI labour. Meta spends tens of billions a year paying people to throw shit at the wall and see what sticks. If the idea well you're going to is running dry, AI with a smaller number of humans can slop out the stuff you do want to build more efficiently is their implicit argument, especially when you don't care about quality (as is the case with Meta). Layoffs are also being used to tell a story around efficiency to investors while companies wait for the billions they're plowing in AI actually show profit.
That works for throughput just fine. And if you have a bit of an inventory, you can hide the latency.
That's also how CPUs are made and sold: it takes a few months to make a physical CPU, but you can just go into a shop and buy one whenever you feel like it.
Except that comforting C-suite narrative does not reflect reality. 2026 agents both increase productivity by knocking clearly specified but error-prone and tedious tasks out of the park whilst simultaneously vexing and annoying their users with hallucinations and downright lies on tasks with intrinsic ambiguity. This is made worse by the token providers with their constant tweaks to their deployments to cut costs w/o losing accuracy which flat doesn't work out well for the end user.
- AI pricing is variable, probably the cheapest it will ever be right now
- AI produces a lot more shit for humans to review, and you will always need humans. If you don’t focus on keeping things simple you will probably play yourself unless you’re good at separating out blast radiuses.
- I see a lot of super low quality work that doesn’t solve the problem but it’s like look that guy solved the problem in one day! Promote him! Everyone is happy except for the end users who for whatever reason are being totally ignored (whose problem it fails to appropriately solve) and I saw this in accounting software so…hello eventual lawsuits?
AI is definitely not the cheapest it will ever be right now. The frontier is getting more expensive, but the same capability will get cheaper over time.
The typical playbook for a VC funded startup is to race to a monopoly where the company can have higher margins. Prices continuing to go down for the consumer over time would require competition to stay high in the long term, and even then it’s not clear if even current prices are profitable.
The current level of AI has plenty of inherent competition from local models. In the long term, most of the profit will probably be from very smart models that run at something closer to datacenter scale over long inference loops - where local inference can't do much and even third-party inference/small neoclouds will be severely challenged. That is a very natural "moat" and has natural cross-efficiencies with AI model training, which requires a similar scale.
That's not always the case. Augmenting certainly can mean that, but it can also mean doing something that people couldn't do before.
For example, looking through meta data in a SQL environment that you didn't know existed to troubleshoot an issue. And a million other things. The odds of any employee not knowing everything are very good, even when humanity as a whole had already discovered that thing.
Because they aren't getting cut cause of AI. They are getting cut cause of the uncertainty re: future revenue streams AI is bringing. These layoffs are driven by fear and leadership lacking any vision for how the post AI world looks for their company. Their solution is to tighten the belts, which of course opens the window further for the AI companies to actually write software and make them obsolete.
I disagree. Lots of people are so laser focussed at only the close to the code aspects of programming they are unable to leverage the enormous increase in scope it can offer them.
There is absolutely room for head count reduction while companies restructure around this.
The AI story is a cover for the companies becoming less profitable in a bad economy, less able to invest because of the end of ZIRP, not capable of finding new markets, and developers becoming more expensive due to changes in accounting laws on the US.
People keep trying to make sense from the official story told by professional liars.
