Anthropic to receive high 'junk' rating from credit agencies following IPO
techcrunch.com
techcrunch.com
While I'm willing to believe that Anthropic common stock might somehow be a reasonable investment because it might go "to the moon", it seems obvious that this is a high-risk bet. This is shaping up to be a winner-take-all industry. Does anyone really think there is a 90% chance that Anthropic will be that winner?
If you thought there really was only a 10% chance that they'd fail to be in business in a decade, why wouldn't you just buy their common stock and hope for a 100x return? How do the rating agencies justify this degree of confidence in Anthropic's ability to repay these debts? Or do I somehow misunderstand what these ratings mean?
I’d love to live in a world where creating something of real value to average humans outweighs what advertising has been appraised at - which id describe primarily as offering value to businesses looking to acquire customers. Yes, there is some value offered to those customers by an efficient advertising system, but the lions share of value lives with the businesses here.
I’d look to the brief postwar period where inequality was a bit lower as a great example of an era where massive value was captured by those who invented and produced new goods and services improving the lives of everyday people.
Digital ads, like it or not, are one of the only ways to reach your total/potential market.
If I search for "how do I fix a shower that won't drain?" then you will get a mix of results that will include articles, Youtube videos, etc. But also links to plumbers in your area seem entirely relevant to that query, no? I find it strange how many of the most militant anti-advertising purists ignore this completely.
As for creating things of value, there's a problem: housing has become the best performing asset in many developed economies and it is fundamentally parasitic and destructive. As an example, the Reserve Bank of New Zealand analytically created the best-performing portoflio and it was... 100% housing [1].
Demand for housing in many places is inelastic. It enjoys huge tax benefits. And you can leverage it better than most asset classes. Plus it's become a political goal of many governments to have ever-increasing house prices.
So if you want to build a factory that makes widgets that you want to sell, that involves a lot of risks. Why would you when you get a better, easier and safer return from just buying more housing?
If you want a healthier, more equitable economy you absolutely have to decommodify housing. There's simply no other way.
[1]: https://www.rbnz.govt.nz/-/media/fd9fa649c29340d7b9f466ba41b...
They take issue with Google grabbing and compiling every piece of data it can get on you into a profile, keeping that forever, and selling that targeting to advertisers.
[1]: https://benjaminrosshoffman.com/the-debtors-revolt/
[2]: https://www.lesswrong.com/posts/tihhx7iy8C6yyHaC2/the-corner...
Think about it. Google's latest Gemini AI is just behind Anthropic's best offering -- or, in fact, it may be slightly superior. Google also has dozens of other mature, cash-cow businesses, massive infrastructure, their own hardware accelerators, an army of smart technical staff... and leadership that, for all its faults, isn't a literal cult.
Anthropic has a top-tier LLM among other top-tier LLMs. Claude is great, but not unique. Anthropic has effectively no other assets, many genuine liabilities, a downright bizarre wet-lab venture, and leadership that's... well...
So, the way I see it, either Google is massively undervalued, or Anthropic's IPO is massively overvalued. Am I somehow off base here?
1. AI. $26T total addressable market ("TAM");
2. Broadband: $1.6T TAM, split roughly 50-50 between fixed and mobile broadband; and
3. Space: $370B TAM.
In 2025, this resulted in revenue of $18.67B and a loss of $2.6B. Those aren't trillion dollar company numbers.
Now TAM is a bit of a fake number but how it's used and the relative values can reveal useful information.
The first is that space launches do not remotely justify the valuation. It's just not a massive market.
The second is that the company is burning moeny like there's no tomorrow on AI.
Lastly, getting back to your point, I believe that mobile broadband is an interesting opportunity but how big is an open question. You'll still need to comply with regulators in every country you offer service, just like all the mobile telcos do, and I don't know if it's cheaper to build and maintain ground-based towers vs Starlink satellites that have a projected lifespan of 5-6 years. Also, how many do you need? Coverage over Siberia is of limited value. Dense population centers are your primary source of customers.
I believe SpaceX would be a significantly better company if it had stuck to space launches and Starlink. It would be worth a lot less but AI might kill it through all the debt. Of course, Elon needed to do that to rescue his own disastrous Twitter than xAI "investments".
The TAM eventually boils down to whatever floats or flies over the oceans, military customers, and places where the wireless network operator is too feckless to provide coverage to your cottage at the end of 2 miles of driveway.
The old moats are falling. The old rent seekers are losing their sway.
You love to see it.
This is the Zerg rush era.
It's easier to build everything now.
AI is a catalyst and the activation energy is much lower.
High energy (shitty) systems will not prevail.
Of course, things like jetpacks and flying cars also have had that feeling. As well as Stephenson's metaverse.
I'm somewhat inclined to give it to them at this point, I mean it's artificial, general in the sense that it can complete tasks it wasn't programmed for, and intelligent enough I guess. I mean if there was a planet with creatures at the level of LLMs we'd probably call it intelligent life—used in that way we're not really implying the creatures are particularly smart. It's as much simulated disembodied intelligence as you could reasonably hope for. I wouldn't at all expect that simulated intelligence: the computer algorithm would have any relation to actual intelligence except at the minimum superficial level needed to complete tasks. With AGI out of the way we would at least have to be more specific on what the sci-fi dream actually entails. The computer from Star Trek is certainly intelligent but you would never say it has a brain or anything close to it.
AGI would mean something with sentience or consciousness. Data is AGI. Even Exocomps were AGI. LLMs don't come close, aren't getting any closer, and there's no reason to think they ever will.
And I don't really think it's entirely unreasonable because there does actually seem to be a real gap in terminology. Even Star Trek didn't really imagine a computer system that's general but exists without consciousness, the whole message of the Exocomp story is exactly that—it's a huge breakthrough that they invented a general system and it turns out to be conscious. And the show makes a point that while the computers they have are incredibly advanced it's ultimately the product of human programming. We seem to just have assumed that any general system would be conscious and the term AGI was born of that assumption.
"Still"? I mean if someone believed that LLMs would result in AGI, why would he change his opinion? Did something happen? I mean the progress generally exceeded expectations so far so your P(AGI) should increase, not decrease. This rant doesn't apply if you did not believe that LLM can result in AGI from the beginning of course.
I like the way Kevin Roose put it: if you were to bring Astra or Opus 5.5 back to 2017 and show it to the leading AI researchers at the time and ask them if it were a form of AGI what would they say? The goal posts shift too fast to keep up with. Some people still worried about it counting Rs in strawberry as the models are making progress in frontier math and physics.
If Opus could autonomously create Fable, and Fable made Mythos, and so on, it would be AGI. The fact that people need to be involved, means it isn't.
If you gave Mythos infinite energy and compute, it still would not autonomously create the next coherent model.
It's a good bar, or at least I don't see your counterargument. It's the bar we have for humanity (solving increasingly complex novel problems in perpetuity), and the original bar for AGI.
https://www.scientificamerican.com/article/what-does-artific...
> I think most people are vastly underestimating just how far this technology can go
It's easy to say this when you don't define "this technology", isn't it? Talk about shifting goalposts.
They'd say it obviously wasn't. If you went back before the marketers started moving goalposts most people would laugh in your face for even calling an LLM AI because they know what AI is. They've seen what AI is in 2001 A Space Odyssey, I Robot, The Terminator, Short Circuit, etc. and they'd very rightly see LLMs as being a fancier ELIZA (https://en.wikipedia.org/wiki/ELIZA) and not even remotely close to Data from star trek.
“Twenty years ago, I think people would have happily agreed that systems with the ability of GPT-4 or (Google's) Gemini had achieved general intelligence comparable to that of humans,” Hinton said. “Being able to answer more or less any question in a sensible way would have passed the test. But now that AI can do that, people want to change the test.” - Geoffrey Hinton[1]
[1] https://www.clickorlando.com/business/2024/04/04/tech-compan...
AGI a couple decades ago would be the T-800 from the terminator, Data from star trek, and Johnny 5 from short circuit. What we have now isn't even remotely close. Most people wouldn't even call what he have now AI by the standards of the time.
If "the market" believes this, I'd love for "the market" to explain to me how they think this works in practice.
Like if Anthropic hits AGI on Monday, what stops Google or OpenAI from hitting AGI on Tuesday?
There is no substantial difference in capabilities between any of these models, they are all doing the tiniest little leapfrogs over each other from release to release.
Even if the market thinks this leads to AGI, there is no reason to believe any secret magic exists that makes one of them reach AGI without the rest hitting AGI nearly immediately after.
Consider the primary use case for Anthropic: coding. Well, if you're using Claude Code or some variant, you can easily use OpenRouter to simply use whatever free tokens you can get. You may not even care what LLM you're using under the hood for a given task.
That's simply not a trillion dollar moat.
Can Anthropic jack up the prices? No. There are alternatives. There are open weight models that you can run on cloud platforms and increasingly you can run them locally. Local LLMs are going to be incredibly accessible in 3-5 years. Even now you can run Flash models on something you can buy from Apple. The inference is a lot slower compared to cloud usage but that'll change.
I see the Anthropic IPO as an effort to cash out before it all comes crashing down.
I use Paseo and there is a noticeable difference when GPT-6.1 Sol is driving the orchestrator vs Opus/Sonnet 5.5 driving the orchestrator. Anthropic models ignore the shared system prompt to use the Paseo tools for sub-agents and prefer to use its own native sub-agents. It ignores the skills mentioned in the system prompt, but will use them if I explicitly tell it to in a user prompt or I extra emphasize the instruction in an XML fenced block in the system prompt or CLAUDE.md like <BOOTSTRAP_MUST_EXECUTE_AT_START>
Sometimes, I feel like I have to explicitly prompt Anthropic models to behave the way I want it to (even with system prompts in place with the EXACT instruction). Sometimes it even feels like it's disregarding CLAUDE.md. To me, this makes me feel like it is the less compliant of the two because I constantly have to steer it manually. Anthropic models also feels like they prefer to go lone-wolf. I want my orchestrator to use the other subs (configured with different platforms and models) to evaluate a design; Opus really wants to lone-wolf and solo everything.
That said, I prefer Anthropic models generally only when the task is more open ended and exploratory. The Anthropic models' "mind of their own" benefits here; GPT models tend to be too agreeable; and too eager to agree with any change in direction. But for actual coding once a direction/plan is in place, I would much rather delegate it to GPT (more likely to draw on the harness for context, skills, instructions, and tools -> more consistency).
Anthropic's 1m context window default and shorter cache TTL are also not great in agentic flows where an agent could become idle and then re-activated. Burns tokens very quickly. I have it tuned down to 300k across all models (recommend doing this for multi-agent coding).
For sure it's annoying building up so much knowledge about a single product that changes every 6m anyway, but what can you do.
> For sure it's annoying building up so much knowledge about a single product that changes every 6m anyway, but what can you do.
Use GPT :PI use Paseo which can use both CC and Codex (and Pi, OpenCode, etc) and spread ownership of roles around. I find I get more autonomy from a team this way.
More detailed write up here: https://chrlschn.dev/blog/2026/10/larping-with-agents-and-wh...
Re: changes: Paseo's plugin system is very, very good. Some limitations since not all of the internals are accessible via plugin system, but allows building very custom UIs. So this may be a point of delta with T3. But I have some coworkers that have gone absolutely HAM with the plugins and built entirely custom workspaces (wild).
For me, what I have found most useful about Paseo is the multi-platform, multi-agent setup because this has given my agent teams much, much more autonomy that I feel like I can trust (after weeks of watching them work). The agent profile system looks too simple at first blush, but actually, that simplicity and semi-structured dynamic nature of the sub-agents is what makes it powerful.
Might try T3 for a week and see; thanks for sharing!
EDIT: T3 has no docs site yet, but sifting through docs, this was interesting: https://github.com/pingdotgg/t3code/blob/main/docs/user/remo...
> Each T3 Connect account can link up to 3 machines. Phones and browsers do not count. A paid T3 Chat plan raises the limit to 10 machines with Pro, or 100 with Premier.
Paseo has no paid features; only if you want to use the hosted hub gateway (entry point for Slack, Discord, GH). T3 Connect looks to be the equivalent of the Paseo Relay: https://paseo.sh/docs/connectivity#paseo-relay which has no limits (Herdr's ipml is better, though; Paseo currently cannot manage individual connections which would make it SICK for team collab. See: https://github.com/getpaseo/paseo/discussions/6896)4-Carbon is, per benchmarks, said to be superior to Opus 5.5 at coding.
At general tasks -- search, medical, interfacing with maps and mail, planning, etc. -- the Google models are already superior.
Additionally, Google is very good at building and managing data centers (including their own networking hardware) and they even have alternatives to NVidia through their longstanding TPU hardware. It can't compete with NVidia's best offerings for sure but it gives them a path to independence.
I believe SpaceX will be merged with Tesla at some point when things turn south. OpenAI? I don't know what their future is. These mega-IPOs just seem like desperate attempts to cash out before it all comes crashing down.
The real problem is that there is no moat. Chinese labs have seen to that. And I believe that it's the policy of the Chinese government that nobody, especially a US tech company, ends up "owning" or "winning" the AI race.
And on the hardware front, China is building their own alternatives as they've been forced to develop EUV/DUV lithography from scratch [1].
I just don't see how OpenAI, Anthropic and SpaceX survive. Then again, Tesla shouldn't survive either but here we are. As they say, the market can remain irrational longer than you can remain solvent.
[1]: https://www.reuters.com/world/china/how-china-built-its-manh...
Its either AGI, or a robbery beyond behavioral data and the whole internet that can make the AI labs win. I dont even know what such a robbery would look like, would perhaps be just making the most advanced hacking tool and then holding the rest of the world and banks hostage.
The cult definitely has some Jonestown overtones: the singularity is coming so things so mundane as a bond rating are of no concern. One way or the other.
Google is slightly undervalued, Misanthropic is massively overvalued.
Let's talk timelines.
2015: Google deployed it's first TPU (tensor processing unit)... For context, openAI in 2026 is only now producing their first TPU chip. Even being generous saying it was only INT8 the same as Nvidia 20-series (2018) that's still 3 years ahead.
2017: The landmark research paper detailing "transformers" in LLM's, titled: Attention is all you need, was published... by 8 engineers working at Google's Deep Mind.
In my mind there's a few possibilities.
1. Google really were blindsided and through lack of leadership / vision were surpassed.
2. Google has already war gamed this out. They know the limits of stochastic tech with "AI" being mostly marketing hype (same as crypto / NFT's), which is why they've limited their liability by investing 10x less than most others in the space.
3. Or they knew AI is going to have some success, but stuck to principles. Google the search engine started out by running distributed (max redundancy) on absolutely dogshit hardware. Yet through clever software optimizations + minimal CAPEX / OPEX, they were able to provide the best service and out compete everyone (Alta vista, yahoo, etc.). Same thing this time around. I have a feeling they (and anyone else not caught up in religious / marketing hype e.g. Deep Seek) is looking at the OPEX and trying to figure out how to optimize.
I'm watching on Bilibili every day how much Chinese people want to rescue Claude.
So, everyone, don't worry. If you really can't pay it back, as long as you agree, China is willing to take over everything.