The “explicit” tag on some of these should really be “self reported”. It seems like most companies these days mismanage themselves into layoffs and spin it as AI gains to appease shareholders instead.

The table shows this better. All have just a single reported layoff "event" except Amazon which has three. Even a decade ago Amazon had many reports on Glassdoor and elsewhere of horrible middle management and employee churn.

All these layoffs seem to track better with longer-term decline than AI progress. One would otherwise expect the layoffs to reflect the multiple and much hyped "step change" improvements over the past few years. Instead the chart shows a sudden plateau starting a month ago. Probably when this last made the rounds somewhere else (maybe reddit? too lazy to search).

There's also a huge hole in media reporting regarding smaller businesses. That's where you'd expect AI to have the biggest impact. Instead we hear crickets.

> One would otherwise expect the layoffs to reflect the multiple and much hyped "step change" improvements over the past few years. Instead the chart shows a sudden plateau starting a month ago.

Can you clarify the theory here? So if there is a “step change” you expect companies to do layoffs all at once? How does this account for I.e. diffusion lag or companies deciding if it’s better to chase growth vs. capital efficiency?

Yes I would expect a lag, but we've been hearing hype with every model update about huge AI productivity improvements for years now.

Despite this, the layoffs are steady over that time with no such spikes. If the goal was ever to cut costs, payroll is never spared since it's too big to ignore. Chasing growth is unlikely when lending and investment is tight. Why invest in other tech companies when you can invest in AI?

I think your narratives are a bit mixed up. We went from science experiment ChatGpt 2022 to zero day finder that is too dangerous to release 4 years later. So whoever has been talking about progressive model updates has surely been correct?

Plenty of zero days have also been found with brute force and random fuzzing.

I'm not downplaying the LLMs we have now, but none of this got started in 2022 apart from the hype train.

Health care premiums are expensive, but even the best insurance I've ever seen was a fraction of the compensation software employees were making.

For some fields that's a huge amount of your compensation, but for software engineers it's noticeable but not going to be worth doing layoffs over by themselves.

What an absurd question. You think employers, who are laying people off and claiming AI for shareholder value, are more pressed about their large group plans than the fucking salaries that absolutely dwarf those premiums?

Some of y’all desperately need to stop huffing social media farts.

I can read the news and see things are going up sideways across the globe. You guys are extremely good at flooding the zone with shit. I am asking a question. It is easy to say we layoff people due to AI when the real reason is different. Not every company has shareholders.

You are also thinking about companies having thousands of employees and everybody seem to make millions.

How much do you think healthcare premiums are? Employers are not paying your deductible or out of pocket expenses.

They’re asking for $100+/mo for the plans that are actually usable at scale. If I’m paying that much I have very high expectations.

There’s also the fact that they’re known for dogfooding heavily, I imagine that contributes to it a lot.

> They’re asking for $100+/mo for the plans that are actually usable at scale. If I’m paying that much I have very high expectations.

If you think $100 is that much and get very high expectations from it, you're not the target customer. You're a loss leader to Anthropic, and the fact that you don't see that / still have high expectations means your expectations are unrealistic.

$100/m for SaaS is very steep.

For an entire productivity suite including mail, meetings and terabytes of backed up redundant storage with nearly no bandwidth limitations it's like $35/m for even the most expensive option.

Those products have very low COGS in comparison to this.

Claude Code and Codex are not SaaS products in the traditional sense.

Comparing state of the art LLMs with Office365 / Gsuite is like comparing renting a datacenter vs an airbnb. Entirely different things.

Compare it to hosting models locally, that would be more apt. Or renting GPUs from cloud vendors.

It’s a SaaS, and the most expensive SaaS available.

If you’re saying an LLM provides more value than the office productivity suites , mail platforms and meeting platforms which run essentially the planet: then I am afraid, you have drunk the kool-aid.

If you’re evaluating software licenses you have to weigh the price to value, there can be value to these LLMs but its not 3x the productivity of Mail+Spreadsheets+Live Meetings+presentations+wordprocessing+filesharing.

Its just not.

If you really think the value add by LLMs is comparable to email and calendar, I don’t understand why you don’t understand my point that you’re not the customer Anthropic cares about.

Your point is stupid.

The cost of offering a service and the cost of buying a service are correlated but not the customers problem.

If you are the most expensive SaaS on a docket sheet and you’re also the least reliable you had better be delivering some serious value in the times you’re up otherwise customers won’t depend on you and you’ll be the first one out.

Nobody wants to pay premium prices for things they can’t depend on. If you cant understand that then you need to stop offloading critical thinking to your AI tools because your mind needs the exercise.

you could arguably ditch the productivity suite and a few other 'essential' subscriptions to make room for this one, except the price point will get enshittified to hell in the coming months and years.

I think the bigger point is that the price tag is simply not competitive, especially given all of the issues, downsides and dangers.

Whether Anthropic makes money from the $100 subscriptions or not, is their problem.

Those subscription plans are a loss leader. Anthropic would rather have you pay per-token for their API, where they actually make money. By cutting subscription limits, they push people towards using their API. And it's working, there are people spending thousands per month on their API.

> They’re asking for $100+/mo for the plans that are actually usable at scale. If I’m paying that much I have very high expectations.

They’re losing money on you at that price point.

Or more precisely you’re paying for it by giving them training data.

I'm not convinced, Kimi 2.5, GLM 5.1, Minimax M2.7 are all fraction of the price and still make money on inference.

they can adjust prices or you can adjust your expectations.

...and let's be realistic, it'll be both.

Honestly for such a powerful tool, it’s pretty damn janky. Permissions don’t always work, hitting escape doesn’t always register correctly, the formatting breaks on its own to name a few of the issues i’ve had. It’s popular and successful but it’s got lots of thorns

Crazy timing. My copy of this is being delivered today from the local bookshop. Great review.

I was wondering just yesterday if a model of “why waste time say lot word when few word do trick” would be easier on the tokens. I’ll have to give this a try lol

> No one has ever made a purchasing decision based on how good your code is.

If you have buggy software, people don’t use it if there are alternatives. They don’t care about the code but hard to maintain, buggy code will eventually translate to users trying other products.

Good code can also be buggy, bad code can be buggy.

The thing here was that if you have two boxes that take the same input and produce the same output at the same speed, do you care what the insides look like?

What if one is delivered in 4 days and the other in 30 days and costs more? Which one will you pick?

This has been the sentiment for nearly a decade now.

Much longer. We had VR in the '60s.

Anecdotally I have not seen consistency in quality at all.

My chairs resemble each other. Have you tried ikea?

If you are talking about code which isn’t what I said, then we aren’t there yet.

It’s a bad analogy because the benefits of industrial machines were predictable processes done efficiently.

That came later than the beginning. Workhouses came before the loom. You can see this in the progression of quality of things like dinner plates over time.

Making clay pottery can be simple. But to make “fine china” with increasingly sophisticated ornamentation and strength became more complex over time. Now you can go to ikea and buy plates that would be considered expensive luxuries hundreds of years ago.

Yeah... nah. As others have said, your analogy does not hold up to scrutiny.

You’re not addressing any points I made.

I don’t love the original idea because uploading identification is risky. You could just plug AI into a verified account but at least the vector is a single account instead of unbounded.