(not pointing the finger only at you, at least you identified that gross margins is the correct thing to look at rather than net profit!)
It's the lack of visibility that causes the judgement; Were the numbers good, it's quite unlikely that Anthropic would be so reluctant to share them.
Were it just Anthropic doing this, it's not much evidence. But it's EVERYONE that obfuscates their numbers, even the publicly traded companies.
Why would Amazon and Microsoft obfuscate the revenues and costs of their AI products? Even their cloud numbers are less clear than desired. And beyond those two, why would the datacenter companies obfuscate their numbers, when everyone desperately needs them to raise debt and investment to build more DCs?
Pretty much the only company showing clear numbers is Nvidia & GPU orders. But immediately beyond that, it's all obfuscated. How many GPUs are sitting in datacenters? They ain't telling.
But what they can (and do) do is structure (in the not financial jargon sense) the reports such that the given datapoint does not exist individually.
E.g. If you want to hide AI revenues or costs, the SEC won't let you just _not report them_, but you can just group the AI revenues with the SaaS/Cloud numbers under a new division, and report only the combined figure for that division.
This works especially well if the grouped components already fluctuate a bit, so one cannot simply substract known SaaS/Cloud numbers from the new total.
1. Continuing to grow their share of the market.
2. Margins staying high.
3. Inference costs coming down.
4. A need for Anthropic's models specifically.
I buy 3. But 1, 2, and 4 rely on models continuing to improve at the same rate, such that you need the latest version to stay competitive. At the cut below frontier models, there's already robust competition between open source models, cheaper providers like Deepseek, more local AI alternatives, etc.
I think the case for the unit economics being fine starts to fall apart if you can't charge a large premium for your best in class model.
If a system can perform or positively augment the work done by a human, especially knowledge workers, then it’s got value, it’s just quite hard to put a finger on what the extent of that value is even now, let alone next month.