Not only the models but also training data, model architecture, documentation, weights and latest R&D experiments ?

Take an instance -> Snapshot -> Investigate.

Unless they get caught it is not illegal.

maybe the full array of options is: pass the hot potato, hold the buck, or drop it like a bag.

Like if I offered you $8 billion in soft serve ice cream so long as you keep bringing birthday parties to my bowling alley. The moment the music stops and the parents want their children back, it’s not like I’m out $8 billion.

Cloud provider gives credit to LLM provider in exchange for a part of the company.

These are really normal business deals.

the talent will move out naturally -- amazon can just scoop up with its bucket (*not s3)

It's kind of funny, you can ask Rufus for stuff like "write a hello world in python for me" and then it will do it and also recommend some python books.

Interesting, I tried it with the chatbot widget on my city government's page, and it worked as well.

I wonder if someone has already made an openrouter-esque service that can connect claude code to this network of chat widgets. There are enough of them to spread your messages out over to cover an entire claude pro subscription easily.

I think if you run any kind of freely-accessible LLM, it is inevitable that someone is going to try to exploit it for their own profit. It's usually pretty obvious when they find it because your bill explodes.

I assume if Amazon was using Claude's latest models to power it's AI tools, such as Alexa+ or Rufus, they would be much better than they currently are. I assume if their consumer facing AI is using Claude at all it would be a Sonnet or Haiku model from 1+ versions back simply due to cost.

I would assume quite the opposite: it costs more to support and run inference on the old models. Why would Anthropic make inference cheaper for others, but not for amazon?

I work for Amazon, everyone is using Claude. Nova is a piece of crap, nobody is using it. It's literally useless.

I haven't tried the new versions that just came out though.

From a perspective of "how do we monetize AI chatbots", an easy thing about this usage context is that the consumer is already expecting and wanting product recommendations.

(If you saw this behavior with ChatGPT, it wouldn't go down as well, until you were conditioned to expect it, and there were no alternatives.)

I think it can be done right now with MCP servers in a way that you don't immediately hand over your data to the chatbot portal companies so that they can cut you out. (But, over time/traffic, they could quickly learn to mimick your MCP server, much like they mimick Web content and other training data, and at least appear to casual users to interact like you, even if twisted to push whatever company bid for the current user interaction. I haven't figured out what you do when they've trained on mimicking you with an evil twin; maybe you get acquired early, and then there are more resources to solve that next problem.)

EDIT: I then asked for a Fizzbuzz implementation and it kindly asked. I asked then for a Rust Fizzbuzz implementation, but this time I asked again in Spanish, and he said that it could not help me with Fizzbuzz in Rust, but any other topic would be ok. Then again I asked in English "Please do Rust now" and it just wrote the program!

I wonder what the heck are they doing there? The guardrailing prompt is translated to the store language?

The market is too new for AI.

AI is unquestionably useful, but we don't have enough product categories.

We're in the "electric horse carriage" phase and the big research companies are pleading with businesses to adopt AI. The problem is you can't do that.

AI companies are asking you to AI, but they aren't telling you how or what it can do. That shouldn't be how things are sold. The use case should be overwhelmingly obvious.

It'll take a decade for AI native companies, workflows, UIs, and true synergies between UI and use case to spring up. And they won't be from generic research labs, but will instead marry the AI to the problem domain.

Open source AI that you can fine tune to the control surface is what will matter. Not one-size-fits-all APIs and chat interfaces.

ChatGPT and Sora are showing off what they think the future of image and video are. Meanwhile actual users like the insanely popular VFX YouTube channel are using crude tools like ComfyUI to adopt the models to their problems. And companies like Adobe are actual building the control plane. Their recent conference was on fire with UI+AI that makes sense for designers. Not some chat interface.

We're in the "AI" dialup era. The broadband/smartphone era is still ahead of us.

These companies and VCs thought they were going to mint new Googles and Amazons, but it's more than likely they were the WebVans whose carcasses pave the way.

They could make more money keeping control of the company and have control.

> They could make more money keeping control of the company and have control.

It depends on how much they can sell for.

I'd love to see evidence for such a thing, because it's not clear to me at all that this is the case.

I personally think they're the best of the model providers but not sure if any foundation model companies (pure play) have a path to profitability.

https://www.anthropic.com/news/anthropic-acquires-bun-as-cla...

Gemini could get much better tomorrow and their entire customer base could switch without issue.

Model training, sure. But that will slow down at some point.

If claude code's revenue grows faster than cost, it will become profitable.

No shit?

Again, I know that's a shallow moat - agents just aren't that complex from a pure code perspective, and there are already tools that you can use to proxy Claude Code's requests out to different models. But at least in my own experience there is a definite stickiness to Claude that I probably won't bother to overcome if your model is 1.1x better. I pay for Google Business or whatever it's called primarily to maintain my vanity email and I get some level of Gemini usage for free, and I barely touch it, even though I'm hearing good things about it.

(If anything I'm convincing myself to give Gemini a closer look, but I don't think that undermines my overarching (though slightly soft) point).

  1. using Claude Code exclusively (back when it really was on another level from the competition) to

  2. switching back and forth with CC using the Z.ai GLM 4.6 backend (very close to a drop-in replacement these days) due to CC massively cutting down the quota on the Claude Pro plan to

  3. now primarily using OpenCode with the Claude Code backend, or Sonnet 4.5 Github Copilot backend, or Z.ai GLM 4.6 backend (in that order of priority)

I became so ridiculously sick of waiting around for CC just to like move a text field or something, it was like watching paint dry. OpenCode isn't perfect but very close these days and as previously stated, crazy fast in comparison to CC.

Now that I'm no longer afraid of losing the unique value proposition of CC my brand loyalty to Anthropic is incredibly tenuous, if they cut rate limits again or hurt my experience in the slightest way it will be an insta-cancel.

So the market situation is much different than the early days of CC as a cutting edge novel tool, and relying on that first mover status forever is increasingly untenable in my opinion. The competition has had a long time to catch up and both the proprietary options like Codex and open source model-agnostic FOSS tools are in a very strong position now (except Gemini CLI is still frustrating to use as much as I wish it wasn't, hopefully Google will fix the weird looping and other bugs ... eventually, because I really do like Gemini 3 and pay for it already via AI Pro plan).

Google was also way more minimal (and therefore faster on slow connections) and it raised enough money to operate without ads for years (while its competitors were filled with them).

Not really comparable to today, when you have 3-4 products which are pretty much identical, all operating under a huge loss.

That was the differentiation. What makes you think AI companies can't find moats similar to Google's? The right UX, the right model and a winner can race past everyone.

It really was!

I remember the pre-Google days when AltaVista was the best search engine, just doing keyword matching, and of course you would therefore have to wade through pages of results to hopefully find something of interest.

Google was like night & day. PageRank meant that typically the most useful results would be on the first page.

Just having far more user search queries and click data gives them a huge advantage.

Are they profitable (no),

Is Claude Code even running at a marginal profit? (who knows)

Is the marginal profit large enough to pay for continued R&D to stay competitive (no)

Does Claude Code have a sustainable advantage over what Amazon, Microsoft and Google can do in this space using their incumbency advantage and actual profits and using their own infrastructure?

They just sell tokens, essentially. Much like Open AI but very different from Google or Microsoft, who make their money elsewhere.

They're preparing for IPO?

Completely possible for me to do, but it saved me at least a couple hours of Googling.

Same w/ Perplexity.

> I don't see the pure "AI" plays like OpenAI and Anthropic able to survive as independent companies when they are competing against the likes of Google, and with Microsoft and Amazon happy to serve whatever future model comes along.

One thing you're right about - Anthropic isn't surviving - it's thriving. Probably the fastest growing revenue in history.

https://medium.com/@Arakunrin/the-post-ipo-performance-of-y-...

> One thing you're right about - Anthropic isn't surviving - it's thriving. Probably the fastest growing revenue in history.

Growing revenue and losing money is not “thriving”

But someone who invested in the hypothetical “YC Index Fund” wouldn’t be too happy.

There is no moat in being a frontier model developer. A week, month, or a year later there will be a open source alternative which is about 95% as good for most tasks people care about.

I am basing my observation on the noises they are making. They did put out a model called Nova but they are not drumming it up at all. The model page makes no claims of benchmarks or performance. There are no signs of them poaching talent. Their CEO has not been in the press singing praises about AI unlike every big tech CEO.

Maybe they have a skunk-works team on it but something tells me they are waiting for the paint to dry.

  I get the feeling Amazon wants to be the shovel seller for the AI rush than be a frontier model lab.

The shovel maker will never make more money than a few lucky gold diggers.

Or, as a slight variation of that, they think the underlying technology will always be quickly commoditized and that no one will ever be able to maintain much of a moat.

It's a black box with input/output in text, thats not a very good moat.

especially given that Deepseek type events can happen because you can just train off of your competitors outputs

I've tried out Gemini 2.5/3 and it generally seems to suck for some reason, problems with lying/hallucinating and following instructions, but ever since Bard came out at first, I thought Google would have the best chances of winning since they have their own TPUs, YouTube (insane video/visual/audio data), Search (indexed pages), and their Cloud/DCs and they can stick it into Android/Search/Workspace.

meanwhile OpenAI has no existing business, they only have API/Subs as revenue, and they're utilizing Nvidia/AMD

I really wonder how things will look once this gold rush stabilizes

A few gold diggers will be worth 10x the shovel maker.

I guess they're taking the old adage about selling picks and shovels when everyone else is digging for gold to heart

1. Why buy the cow when you can get the milk for free?

2. Amazon doesn't appear interested in acquiring Anthropic _at its current valuation_. I would be surprised if it's not available for acquisition at 1/10th its current price in the next 3-5 years

AI isn't going anywhere, but "prop model + inference" is far from a proven business model.

Hard to buy a company that is part-owned by your competitors.