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Comment by skinfaxi | Hacker News Reader

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?

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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.

That is a very convenient message for marketing and sales people. The fact that their whole job is crafting messages shouldn’t raise any eyebrows.

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.

I took 'engineer' vs 'marketing' and 'sales' as just examples in the grandfather message. The essence was about bottlenecks to revenue.

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.

In 20 years I have never been on a team that didn't have twice as much work as we had people to do it.

Businesses are not magically efficient

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.

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.

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.

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.

If one woman can produce a baby on 9 months, why can't you get 9 women pregnant and produce a baby in one month?

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.

The demand doesn't necessarily double.

There's only so much to do and coordination costs (already burdensome) become overwhelming.

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.

Diminishing returns on additional labor.

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