It's a memestock.<p>Think about it. Google's latest Gemini AI is <i>just behind</i> Anthropic's best offering -- or, in fact, it may be <i>slightly superior.</i> 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.<p>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...<p>So, the way I see it, either Google is massively undervalued, or Anthropic's IPO is massively overvalued. Am I somehow off base here?
Opus 5.5 has been noticeably better than other models at coding, is Gemini’s (public) AI that close? And is it cheaper?
I genuinely prefer OpenAI models for coding and building in general. My observation: GPT models are generally better at following the system prompt, tool use, and skill use.<p>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><p>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.<p>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).<p>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).
The way I use Opus is basically adhering to its training/emergent behavior. Anything else is always worse in some way. Using default harness, mostly letting it do what it wants the way it wants to (as much as possible anyway) and making it work for my own flow.<p>For sure it's annoying building up so much knowledge about a single product that changes every 6m anyway, but what can you do.
Gemini 4-Argon is very good at coding. I prefer Opus 5.5 -- in large part because I've grown accustomed to Claude Code -- but Argon is undeniably strong.<p>4-Carbon is, per benchmarks, said to be superior to Opus 5.5 at coding.<p>At general tasks -- search, medical, interfacing with maps and mail, planning, etc. -- the Google models are already superior.
All that seeming advantage, and yet Google are perpetual laggards in the AI race. In enterprise, where the money is, they're third behind Anthropic and OpenAI, despite what should have been a colossal incumbency advantage.
They're also inexorably poisoning their own brand and squeezing their primary revenue source with AI Overviews. Truly a masterstroke of value destruction. Search revenue growth has slowed three quarters running, even as query volume hit a five-year high.
As for their hardware and infrastructure advantages, those are indeed making them money, because they're selling and renting the chips to Anthropic.
I dunno. I've been a fan of Google for years. Maybe they'll successfully pivot to being a hardware company. They're too slow and hamstrung by internal politics to make compelling LLM products.
I also see Google winning this in the end. They have absolutely crazy behavioral data and can exploit much more effectively. Meta is also up there, but Google has production hardware as well as clouds, etc.<p>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.
Google stock dipped because search traffic is shifting to LLMs. Even if Gemini got a large percentage of that, margins are much worse.
Reading tea leaves, the market believes that whomever is first to AGI will reap all the benefits, leaving nothing to the runners-up. In this view, even a tiny edge in model quality is decisive.
I cant believe that the market still thinks LLMs are ever going to result in AGI.
AGI has been prominent in pop culture since at least 1968 with 2001: A Space Odyssey. There is a place in our heads for it. And really I think that's just the modern version of anthropomorphic spirits: angels, devils, gods, etc. It gives AGI a feeling of inevitablility.<p>Of course, things like jetpacks and flying cars also have had that feeling. As well as Stephenson's metaverse.
* results may vary depending on your specific definition of AGI.<p>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.
The goalposts have never shifted if you didn't shift your definition for the oligarchs and kept it stable.<p>If Opus could autonomously create Fable, and Fable made Mythos, and so on, it would be AGI. The fact that people <i>need</i> to be involved, means it isn't.
I think the current state-of-the-art models are already AGI, by the kind of definitions of AGI that people had a couple decades ago. I could be wrong but I kind of feel like people have started using the term "AGI" to mean "artificial superhuman intelligence".
The market is not an expert and does not trust experts.
> I cant believe that the market still thinks LLMs are ever going to result in AGI.<p>"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.
Well they're for sure going to result in something a desperate marketing team is going to call AGI and through persistence through all the laughter will result in a new term being coined like ActualAGI so people can refer
to it as separate from "AGI Class Models."<p>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.
Well whatever the next thing after LLMs would be Anthropic would be in the perfect position and have the perfect expertise to train it.
It's so fascinating that people think that AGI will be winner-take-all. If anything the Chinese labs have shown us is that being first is almost a handicap as everyone can quickly learn from your released models and distil into open weights quite easily. If the competitive environment continues to exist how it is today, there doesn't seem like a trillion dollar market for anyone.
> Reading tea leaves, the market believes that whomever is first to AGI will reap all the benefits, leaving nothing to the runners-up.<p><i>If</i> "the market" believes this, I'd love for "the market" to explain to me how they think this works in practice.<p>Like if Anthropic hits AGI on Monday, what stops Google or OpenAI from hitting AGI on Tuesday?<p>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.<p>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.
Sergey has gone a bit culty. But yeah. There are no moats that can keep out everyone who has built and operated data centers before the AI bubble. For these players, overspending, up to a point, is a defensive move.<p>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.
The thing is - Google is fucking terrible. Gemini has nice benchmark but it's unusable, try it. There's a reason why their market share in AI is so small.
as a general rule IPOs are always overvalued...and then theres the hype which is backed by a shrinking set of the raw numbers
I believe Google is the most likely to survive the bubble bursting. They have significant cash flow from other sources and have likely insulated themselves by using SPVs for a lot of their debt. It's true that they've invested a lot of their own cash but they've also rented a lot of GPUs from SpaceX and elsewhere and I think that's probably a good idea.<p>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.<p>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.<p>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.<p>And on the hardware front, China is building their own alternatives as they've been forced to develop EUV/DUV lithography from scratch [1].<p>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.<p>[1]: <a href="https://www.reuters.com/world/china/how-china-built-its-manhattan-project-rival-west-ai-chips-2025-12-17/" rel="nofollow">https://www.reuters.com/world/china/how-china-built-its-manh...</a>
Anthropic NFTs anyone?
It's not any worse than SPCX, so who knows?
Mind share is the true moat. It doesn't matter if your product is not special if when someone thinks "frontier" and "agentic development" they still think of Claude. They don't think Antigravity or Gemini while Google has also decided to safety max themselves into failing to gain more mind share.
The moat doesn’t exist, at least for models used for coding. I switch to what is cheapest for the task at hand and while Claude was my go to at the start of the year now it’s just in the rotation. There is no friction in switching.
I disagree. I believe these LLMs have already been commoditized.<p>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.<p>That's simply not a trillion dollar moat.<p>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.<p>I see the Anthropic IPO as an effort to cash out before it all comes crashing down.
You don't honestly think the software industry alone is large enough to support all the checks Anthropic has been writing, do you? Especially after software devs start to realize how much crufty rot these the agents generate while they aren't looking.