YHK - yet another hacker news clone

Growth is conscious now? or what do you mean?

Huh? They provide a service that does something that did not work before and now does and was quickly adopted. They do not have a moat.

their gross margins point at this not being an issue.

The subscriptions are a key part of the engine to ensure The Machine can keep improving itself by harvesting all that data and feeding it back in. Many of the enterprise contracts forbid the lab from training on their data, so the subscriptions are a form of gold.

Doesn't their S-1 render this irrelevant? Their financials are clearly much better than we thought

Their financial statements suggest the answer, even when you take into account the cost of training the model, is now 'not at all'. They are profitable, the main questions for their valuation are 1) can they keep their margins, 2) how big can they grow?, and 3) can this growth match what they have committed to?

> all numbers coming out of Anthropic are utterly meaningless until we can answer the question of "just how subsidized are those subscriptions?"

Subscriptions are a growing minority of revenue.

Not at all, the subscriptions have an adjusted gross margin of approximately 85%. Very profitable! The training is a different story though. How long will the subs last if they stop training? Also, why on earth would they put on the breaks and try to be profitable when they have plenty of funds and are in the growth stage?

Opus 5.5 is basically not included in this data.

I've been throwing opus 5.5 at problems I got stuck on with sonnet in the past and it has breezed through them all. It really reinforced how far the models have come.

I’m not sure it’s a binary thing that contradicts.

I want AI and these companies to succeed. And I especially want new companies to succeed. But I want them to be valued far more realistically. Because if they have to be worth trillions, then there’s a real motivation to do what it takes to realize that valuation. And that’s how you birth a Zuckerberg.

I’m not rooting for them to fail. I’m rooting for the correction to happen sooner than later.

I’m wondering whether Opus 5.5 would have caused growth in an absolute sense or just growth relative to competitors.

Anthropic’s market share is pretty high and there is not enough total currently addressed market for growth at the expense of a competitor to make a big long-term difference.

This is likely true, but doesn’t really tell us much about future revenue growth. Now they need to compete on price, I think their revenue growth may start to look much more like typical Jevons paradox examples. I.e as their usage grows exponentially their revenue grows linearly rather than exponentially as it was before.

Yeah there was a vibe shift towards OpenAI being much more competitive for daily use and then Opus 5.5 hit. Will be curious to look back and see if that shows in data. Of course, could change tomorrow.

As a counterpoint I haven't seen opus doing that much better than the latest gpt models? Astra is definitely comparable to fable and sol has been as good as opus for me. So this rings a bit anecdotal and that's probably what people will be seeing affect the growth trajectory too.

I have zero sense of this myself, am just curious, and not confident anyone really knows, but: I get that its a big deal for software developers when each new model comes out, because its perceived (correctly or not) as the next big boost for their productivity, but what about everyone else who is not a coder? Is there big reactions there to newer models? I don't know a single person who is not a engineer that would be able to tell me if "Astra" or "Opus" are Anthropic things or an OpenAI things respectively, much less when and what the big new version is for any of them. Does this play out for others? Or am I just in my own bubble for some reason?

What does average, non-computer Joe or Jane think when the next big model comes out? "My emails are going to be so much better now, I better stay subscribed"? "I can't wait to see how well it answers my questions"?

> I'm sure there are a lot of people rooting for their IPO to fail but they are still clearly in the lead on coding and will continue to do well until someone definitively passes them.

Then why all the rush to IPO then?

The strongest chinese models from DeepSeek, Kimi and z.ai are already good enough to run for hours on most coding tasks cheaply.

> they are still clearly in the lead on coding and will continue to do well until someone definitively passes them.

I think the first implying the second might be a bit of a stretch. At some point, companies are going to start looking at their AI spending and start negotiating deals. OpenAI is right behind them and Anthropic is around 8x more expensive (Sol 6.1 vs Opus 5.5 based on Artificial Intelligence's cost per task; cost per token is a somewhat useless metric when different models use vastly different numbers of tokens for the same thing). Chinese models like Deepseek 4.1 Flash are cheap, can be self-hosted, and while certainly behind Claude Opus 5.5, are still good.

Lots of companies buy "inferior" products like Microsoft Teams. Over the next 5 years, it seems likely that many models will get really good to the point that people often won't be able to tell any difference. Even if something isn't "definitively" better, companies might say "our engineers can't tell the difference and we're cutting our costs by 85%."

It's not absurd to think that a company would use its own harness or an open source harness and/or put a proxy in to route requests variably. For two months, they have engineers using different models unbeknownst to them and they measure things like how often the engineers have to correct or redirect the model. At the end of two months, they might find little difference in performance and switch to a much lower cost model.

It's not like it'd be crazy hard to analyze workers frustration as they did their jobs and figure out if one model was actually better. They could log all the conversations and it's not like AI can't easily determine things like "no, that's completely wrong" as a phrase showing that the agent was really off base.

I think a big part of the next 5-10 years is going to be about cost/efficiency.

Anthropic can remove all access to their LLMs and start replicating entire software companies. Anyone relying on open weight models is at risk of a security breach from even slightly better models. It is ironic when people think Anthropic is the one without moat while they give all their data away.

Opus 5.5 actually decreased my Anthropic spend, because I stopped using Fable once it came out.

I ping-pong between different agents all day long and don't necessarily agree that Anthropic is clearly in the lead on coding at this point.

Anthropic and OpenAI own no compute. Amazon has no models.

So that leaves...

i think its a lot deeper than that, compared to deepseek-4.1-flash, glm-5.3-flash and the recent minimax-m3.1-flash [0], the comparison in price (15x cheaper inference cost) and the productivity gains are very similar if not more profound depending your prompt topic (cyber, biochem, etc)

[0] https://x.com/jumperz/status/2112226308868436154

Are any of the AI companies selling their services at a profit or are we all being subsidized by investor money that is about to need to be paid back?

Growth being the first derivative… so… not particularly desperate?

when politicians and bankers talk about "reducing inflation" they use the same derivative

I have no issue taking arbitrary derivatives... provided you're not taking derivatives of very noisy data.

Having compute to serve the demand.

What is the moat of any tech company if they are using LLMs to build their products which can also be reverse engineered by an LLM? Hardware?

decent software stack that works out of the box.

You can go very far in life with a thing that isn't futzy

It was six months last year, it’s on the order of weeks now. Presumably they have unreleased models that are a step ahead still. The moat is capacity and how much of an ecosystem the can build around the llms; eg anthropic figma tool.

I always bought on who I thought was best at attracting the best talent in the space, and for how long they could remain dominant in that.

Sometimes it's just Hype -> disillusionment, and then no one ever figures out a better way and it's dead technology.

Not saying that applies to AI, but it certainly applies sometimes.

AI has historically had a habit of disappearing for ten years and coming back once memories fade and the new story sounds enough different from the old one.

I don’t think this era is going to end with us all unemployed, but I do plan to be retired before the next cycle.

I think most people who care or are tracking it would say we've hit it, and those who disagree just have their goalposts a lot more clearly defined and are quietly waiting.

> revenue per dollar spent on compute from $0.40 to $2.08

So that’s ignoring labor and perhaps facilities? That’s like saying we’ve hit net positive fusion by only considering the power produced by the laser and ignoring the 80% power losses in the feed-in.

The answer is ~5 million in case you’re curious how much the penny is worth after 30 days of doubling.

~5 quadrillion after 60

The mental gymanaatics here is crazy

1) customer concentration risk 2) when those customers use a diverse set of models - so too will the rest - they’re not idiots who want to pay more than they should

Aka % growth rate decreasing sharply and eventually flattening out. Within 2-3 quarters.

Understood?

Employees were and are pushing for more model and harness diversity too I promise.

But perhaps for different reasons than Microsoft, Meta, and maybe Adobe leadership are now. See, if they are all in on Claude how do they sue Anthropic for assisting in copyright violations and IP theft? The services would be cut immediately.

Well when they don't need them anymore..

This is why Anthropic is heaping on more and more model restrictions running up to IPO. I believe it's a smokescreen for the IP risk they outlined in their IPO filing..

Zitron is not a serious person

Years, no? Meaning the sky is falling rhetoric was wrong for a long time. He will get lucky eventually.

Zitron's literally just some normie that got pushed by the algo a bit harder than other shocked faces with flames and red arrows and no industry insight.

A lot of people have jobs that aren't limited by how much "stuff" they generate.

How so? Or is this just vibes based analysis? I dont really know what you mean by classical engineering, but sure if something can be done on a computer it can infinite monkey theorem its way to a solution. This isnt exactly useful its just an enablement of laziness.

Idk how many people need to hear this, but not everything 'is computa',no matter what Trump says.

Much of the worlds problems are not verifiable with a compiler that can be trained or brute forced against.

Llms are not as useful as ya'll think they are, not everything exists in a web browser, which is why Anthropic et al have saturated their TAM and are now frantically hiring sales people to convince managers in other verticles.

Turns out most people dont need or want AI.

[flagged]

> The real question is how many people haven't figured out how to use AI to make their job easier/more productive.

I think the answer, to a reasonable approximation, is “everyone”. Outside software engineering most people aren’t using it for anything useful, and I keep encountering technical people including programmers who don’t use it either, which never fails to surprise me.

One of my projects is a transportation management system (TMS) and of course I have added a lot of features to it including a very capable chat-based UI that can automate a lot of tedious data entry and other tasks for dispatchers and accounting and so on. It gets used but really not very much. I’m starting to realize that I’ve probably taken updates as far as they can go in terms of the ability of people to absorb change. Most people just carry on doing things the way they always have.

We had one person on the admin team who started using Cowork to automate all kinds of stuff. She loved it. Then she left. It hasn’t caught on with anyone else.

This is not to say that things won’t change but I think it will take a while.

They said distillation was 5-7% of revenue. The slowdown is much larger than that.

Slop is a side effect for anyone using it at scale it seems.

What did they think was going to happen? Lots of people predicted exactly this progression of events.

People tend to do wonderfully at whatever metric they're judged by. I don't think the "tokens consumed" metric was a very good one.

It may have something to do with the summer intern season ending. I know one of the interns hired by my employer used up the allotted AI spend by doing “fun” things, like making Claude write an entire SQL-to-Pandas transpiler in 10,000 lines of Python.

I now think of software code as DNA.

Your machinery was not written elegantly. It was sloppily assembled via evolutionary pressures.

A gene gets duplicated, mutates, and suddenly you have new functionality and new fitness criteria.

Try something bad and you die without reproduction.

Our code isn't clean. There's redundancy and extra packing and slop all over the human body.

Embrace it. Stochastically hill climb.

Code is DNA. Evolve it, don't intelligently design it. Fit the curves of your environment quickly and use tests to cull bad behavior and the slopes of your domain.

Interesting angle to blame the slopmaxers when the AI companies have been pushing maximum usage for a while now.

I assume they’d hoped that the value of the spend would manifest itself and they could raise prices. The opposite happened and companies are instead cutting back.

It sounds to me like they chose a poor marketing and pricing strategy for a product that is very difficult to make cost effective.

When was the last time anyone used the term "tokenmaxxing" right now?

   Exactly, No-one and as predicted it was a fad. [0]

Vibe-coders don't want to risk getting their accounts suspended if you use their models in a certain way.

We are seeing the result of those subsidizations and discounts that Anthropic made this year and how much of this "tokenmaxxing" hype was used to make their revenue numbers look "good".

With the arrival of more cheaper models which are good enough, it doesn't make much sense to use Anthropic's models.

So don't be easily fooled by their revenue projections. Rather question if it is sustainable for them. (Spoiler, it isn't)

[0] https://news.ycombinator.com/item?id=49330214

Everyone trying to vibecode their next million dollar idea only discover the web is dead. Nobody is looking for anything because that would require leaving the safety of the same handful of sites everyone else is on.

Lmao a colleague who works elsewhere said some goon at work created an AI leaderboard. He spun up research agents. Top of board achieved. Granted the guys a very solid developer, but he did it to prove how dumb this is.

AI put a massive spotlight on all the required but unspoken decision making and coordination that must occur with stakeholders outside their own teams during the development process.

Dysfunctional middle management has always traditionally neglected it or actively undermined it, blaming others when things go wrong and taking credit when things go right.

Naive developers are always more than happy to do what they think is "picking up the slack" not realizing it's a trap.

Perhaps most organizations are just now more wise to the fact that using AI to "accelerate the process" is like arming the monkeys with machine guns?

wow really? Nov 2025 I was still fighting blatant hallucinations in helm charts. Now I'm two prompts away from a new build published on the app store and 5 video reels in the queue complete with captions and everything

No one with a brain does, but Anthropic’s valuation is banking on massive sustained growth to pay their bills.

They need a lot more growth just to afford the compute they've already agreed to buy. Not to mention to justify their rumored record-high IPO price.