except the employees will be compensated with equity, so they will have an incentive to pump the stock price to increase their compensation. I've seen this play out (and subconsciously been a part of it) for over a decade at Google. The early, super rich leaders won't be the ones to enshittify, but the next generation of leaders that are trying to get rich will feel the stock price reward signal.
This. It will be very interesting to see how plans are going to change and how quickly. Maybe they won't and they'll stay relatively affordable. We'll see.
Plausibly part of the chain of events, unlikely to be a cause in itself. Nothing pops because of an underperforming IPO.
Though Anthropic's IPO flopping might affect the valuation of OpenAI, which further inhibits their ability to raise additional funds (which they're already been struggling with). Given the incestuous financing in AI any major actor in the AI space defaulting could bring a lot of companies with it.
With Anthropic's IPO (and I was looking forward for OpenAI as well) there should be some hope for some rationality to come back into the sector.
If the bubble bursts, better now than much later. The industry stance that's been ongoing "AI, at all costs" has been such a market and economic pressure on the everyday worker that even a small value deflation I deem necessary.
I would guess Jensen's affairs are a huge boon to the IPO price. Money freed up to move from Nvidia to Anthropic. Also Anthropic loses one of it's main idealogical opponents
At this point it is obvious there is some level of astroturfing going on with Jensen's affair. Most Nvidia employees don't want him to leave and there is nothing concrete anyone can point to except some GPUs being sold to China. Incredibly overblown and will eventually be a story running on fumes.
With SpaceX, now Anthropic, and soon OpenAI, we're seeing 3 of the largest IPOs ever. Will existing institutional investors trim other positions to allocate a lot of capital for these mega listings or is this not a concern?
I wouldn't worry too much about OpenAI; they seen to gave deferred their IPO until 'sometime in 2027'. At this point they're basically at the mercy of Anthropic, since if the Anthropic IPO goes poorly or gets pulled then it's going to look to investors (and everyone else, frankly) like OAI will be dead on arrival, too.
There isn't really a question. The market is huge and can absorb it, the questions are around the specifics - can pension funds invest if the company has a junk rating (no), is the valuation justified based on current finances etc.
The demand for the particular company may not be there, but that is different from "the market". There's plenty of capital to go around.
To be fair, that loss includes over $20b from instruments like convertible notes. They're not equity, so the increase in their value has to be reported as a loss. But in the context of this IPO, they will behave like equity, and just turn into stock. That's not money anthropic will pay, it will just dilute investors during IPO.
Reporting an increase in the value of the company as a loss is weird, but they have to do it. this is a case where adjusted earnings give a better idea of how the business is going.
I would wait for 2-3 quarters before investing, it will drop and there will likely be lock-ins to contend with. if growth slows then price could tumble fast.
Shorting the leading AI company during the AI revolution?
Reminds me when HN was saying NVIDIA is a good short 3 years ago, supposedly it was "in a bubble", because it's stock prices was as if it had 10x the revenue it had in back then. Plot twist: today NVIDIA revenue is 10x the revenue from 2023, so it turns out the stock was priced exactly right back then, because the stock market is forward looking.
I wouldn't short it, it's likely to ruin you similar to what happened to the Tesla shorts. I would hold off to see if their earnings look good then go all in with 100-1 leverage. /s
The stock market is barely distinguishable from a casino at this point (and arguably never has been far from gambling), I have 0 confidence that the horrible business that Anthropic is will be reflected accurately in any way
I feel like the saying "Markets can remain irrational longer than you can remain solvent" has applied my entire life; I have yet to see the stock market behave rationally in my lifetime.
This page is specifically to register for the UK retail offering of shares. I don't imagine that'll stop people who haven't clicked through posting off topic nonsense.
The URL says `/us`. And it calls it a "roadshow", which is the term when the company and the supporting bank goes around to investors to pitch their offering.
The submitted URL is https://ipo.anthropic.com/us/ . I was redirected to /eu/ ("Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden").
Apparently not every country can participate in this IPO. As of now, if you open the Revolut Anthropic IPO page from Poland, you get:
> Linked page(s) related to Anthropic IPO can only be viewed by persons located in UK, Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden.
Guessing, but probably where the underwriters have brokerage relations or there are favorable capital controls, since it’s a US listing.
I confess I’m about 17 years out of practice in the Polish market, and about 12 years out of touch with how the European industry shakes out on the whole, so I’m not entirely familiar with the legal or business structures.
I don't know about the IPO specifically but it's only retail that has limitations for some US listings. And custodian banks/brokers offering products to retail.
The biggest one in the EU being the "No KID, no deal" (for funds, derivatives, etc.): no Key Information Document, then cannot be offered to retail.
That is unless retail is an accredited investor (say a letter from a bank saying you have more than 1m EUR in investments): then it can trade/invest in everything.
Or for example if you own a company (say private weath management) that's non-custodian (say you manage your wealth using your own company, and shares of your company are privately owned) and you're considered a professional in the finance world, you can ask your broker to let you trade / invest in basically every single product under the sun.
AFAIK pre-IPO stocks are just as vanilla as regular stocks and do not need the KID notice.
In addition to that Anthropic (in the EU), says you can enter pre-IPO using Revolut, Trade Republic, eToro or using bigger players like Saxo or IBKR.
Availability of American investment products is the outcome of compliance required (KID in local language) then volume and sophistication of investors. In case of paltry investors like e.g. Poland, Czechia, Hungary, they don't bother.
„The IPO process begins with a roadshow starting on November 10th (EST). Subject to regulatory clearance, the final IPO share price is expected to be set on November 18th (EST), and shares are expected to begin publicly trading on November 19th (EST).“
So if share price is only set one day before trading, I guess you just have that day to decide to buy if you can get allocation from your broker? I'd like to try it but I've never bought an IPO before.
To further emphasize this, it is very challenging to get in a pre-auction allocation.
You can submit an order via your broker (depending on the broker and your account) to the auction itself on the exchange once it’s in the quotation phase.
Not that I would advocate for that. Sometimes it’s better to buy in the secondary market once things settle a bit.
Reminder that hot IPOs, in this era, rarely do a great job at getting returns for the investor - its more a mechanism to reward long term private investors, employees and the book runner.
I may be inclined to wait 2 months when the price drops and pick up then.
You indicate your interest. Also start funding the account. So you fund 7000 for 100 shares at 70. Then they announce the price is 75. You must change the order to fit the funds or have extra money. Of course you can opt out or change the quantity anyways. But I think in both the cases I actually went ahead (Reddit and figma), I had to reconfirm the quantity. You can't be away from the network.
Just echoing what another comment said: it’s rarely a good idea in the long run to buy an IPO. Not financial advice. It’s one of those things where if you have to ask how to do it, you probably aren’t wealthy enough to be speculating at this level.
Would you buy a gaming console for a high price from a company that’s never shipped a gaming console? Maybe, but you’d wait til it’s been reviewed by someone else on YouTube or something.
Given that almost all IPOs are priced to be intentionally oversubscribed these days (to achieve an "IPO pop"; beats me why that's good for the company doing the IPO), isn't it a mistake to not participate?
There is a lot of value from LLMs but it is something that I can switch easily. Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI". Anything that solves specific problems (even multiple problems) does not need frontier LLMs.
Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
Easily in the context of the corporate world is to pay for something, that something gets installed and then just works, and if it doesn’t work there’s always someone you can call 24/7 to come and fix it. I don’t see how this is possible with open models.
What do you mean? We use Bedrock at our company and I can switch to literally any model, including the open ones, by just typing /model and picking it, even including inside Claude Code. It's ridiculously easy to switch, and imho GLM 5.3 is good enough for 99% of my daily tasks already.
> Meanwhile, Google and Microsoft, which already dominate that area, seem to be dormant.
Google owns 15% of Anthropic I think.
And Google offers Argon 4 to paying Workspace and Google One customers now. How's what was the number 1 model on nearly every single bench a few weeks ago being "dormant"?
I know people all in in the Google ecosystem (getting credits from Android phones they buy etc.) who only swear by the Google models and who are now using Argon 4: I asked them and a few days ago they had access (but they were already using other Google models before that).
Doesn't GMail have billions account by now?
I'd tend to say with billions of users on GMail and a model like Argon and 15% of the Anthropic shares, Google is not where you think it is.
It's easier to use claude to do stuff insider workspace than it is to use the integrated gemini. Claude has more power to do stuff than gemini, in it's own house. That is such an egregious fumble that it's honestly hilarious.
It's almost like the workspace devs are anthropic plants that are purposely underminig google.
Integrated gemini stuff sucks but it's nothing that special about Claude, the general agentic tools are just better, Agy is also much better at doing things in workspace than the bespoke in-app gemini stuff
Right, because Google actually has assets and a responsibility to keep their customers secure, whereas Claude can do things that are completely insane from a security perspective because they have no liability.
The sad thing is Google could totally own this space.
They had a huge head start, more raw data (from search) than anyone, a huge installed base on Workspace and consumer Gmail, tons of compute resources...
Yes, that's the direction I've been witnessing for Claude too. But it's a short to middle-term strategy IMO, by the time companies are ready to drop all these apps they will need something else entirely, not Claude's slides or spreadsheets or Salesforce.
The fact that Frontier AI can become Google Workspace at a flip of a switch is what is crazy valuable. Anthropic and OpenAI can enter and disrupt any market, especially software, faster than any company ever could, because users want the flow to start and end in their chat interfaces.
I think eventually almost all non-creative software will, essentially, be a wrapper around a session.
This pattern has already happened before, in the translation industry. Someone figured out how to learn from and recall context from ordinary translation work (the "translation memory"). It started as an add-on to Microsoft Word, and matured into a standalone software, that was ultimately a wrapper around a document editor. Then language management systems plugged into that wrapper, hey presto, every translator at your company does the same work they were always doing, and you've produced an entire corpus of quality translations to reuse everywhere.
Now _translate_ that idea over. Every time any human works with an agent on anything, simple heuristics find everything true and reusable, save it to the everything-memory as skills, refences, glossaries.
Anyone does any work, all agents can now that work at that organisation. Self-fine-tuning models everywhere, and it fits into corporate intellectual property expectations.
I have done something like this at a medium-sized listed business.
If Google and Microsoft have gone dormant in this space, I have to think it’s because they haven’t been seeing any ROI, either. Possibly because customers have been so underwhelmed.
I’ve been using Office Copilot more or less since it was released, and the general opinion around the office is that it’s a huge waste of time. The auto-transcripts produce 3 pages of fluff when previously someone would send 3 sentences’ worth of what actually mattered. The auto-drafted documents rarely add anything meaningful beyond what was already in the prompt. The question answering and research tools are only as good as Sharepoint/Confluence/Jira/etc’s pre-existing search feature, and therefore untrustworthy, etc.
What made Anthropic exciting was they had locked onto a use case that reliably generates positive value: coding. Not much else has proven, from a business perspective, to be anything more than an exceptionally buzzworthy money pit.
I have been using Claude privately for coding a few weeks now, and my company encouraged us to use company paid Copilot recently. I tried coding with it and the result made me irate i had to close it it was so infuriating. The idea that i need to point out it’s bugs and have Copilot tell me “you are absolutely right!” Haha never again
Helping my wife this past week try and setup an automation in her workspace account revealed how dormant google is here.
Gemini is unable to take an attachment from gmail, read it, then place it in the correct drive folder and update a spreadsheet with what it found in the attachment.
For whatever reason, Google decided to firewall "Gmail Gemini" from "Drive Gemini". Gmail Gemini can send files to drive, but not edit anything, and Drive Gmail can edit files, but cannot be initiated from gmail.
Meanwhile claude code with Google extensions can do this no problem.
Not only can you switch easily, they all seem to do the same thing, fail in the same ways, make the same bad linguistic choices, write the same code... I think at the end of the day, LLMs are a commodity. They're like a grease, or oil. They're trying all the tricks with branding cute names, version numbers, benchmarks, thinking levels, but it all just seems the same stuff to me: I put in tokens, I get more tokens back, and if I didn't know ahead I wouldn't be able to distinguish if they'd come from Anthropic or OpenAI or wherever. Maybe some people can but I can't.
Switching models is easy as a solo developer. Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS, GCP etc… same-looking product, very high switching cost that would have to be driven at the CIO-level. And ultimately they are selling compute capacity.
Switching LLM providers as a company is even easier than a solo developer, most large companies I know are using AWS Bedrock and selecting another model is basically just a checkbox for them
As far as I know, our corporate has deals with all of them: Anthropic, OpenAI and GitHub Copilot.
They stroke a great discount deal with all, so different teams/departments have different provider, and those using Copilot are even free to switch between models as they please (although with lower usage limits).
You could make the argument that it's not worth switching SAAS providers for enterprises when the costs were like 10 dollars a month per developer and switchign would require 1 team to work for half a year... but with AI providers it's more like paying 1000 dollars a month per developer vs paying 200 dollars if you strike a good deal with different provider and swtiching costs are more like 4 to 8 hours of work for each developer.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.
I'm not so sure about this. I guess it depends on how well people did their job there.
Ideally, whatever people built is loosely coupled to that third-party resource, meaning that switching cost will stay low.
After all, it's probably just prompts + an API layer. Unless one micro-optimizes their prompts for claude (which then breaks once a new checkpoint drops, hence is a bad idea regardless), pointing them towards a different API endpoint should be doable.
Currently we are building agentic systems for various business functions like Legal and Finance. How these models perform in those tasks is paramount, and things like cost per run is only a part of the equation. It can become very subjective, and things like brand recognition comes into play. The cost of a counsel or a VP finance overshadows the savings you get by micro-optimizing for a cheaper model. We tend to use the best-in-breed LLM for the various tasks - mainly Claude and Gemini, and sometimes GPT.
> How these models perform in those tasks is paramount,
Then you have no choice bit to use your own hosted model because that's the only way you can be sure the model isn't going to be removed or quantized/nerfed behind your back.
If your system can widstand the fluctuations of closed models over time, then it can most likely support switching between multiple providers in the first place.
> The value proposition of the frontier labs is their post-training taste, how reliably the model handles ambiguity and infers intent,
That's also literally what frontier labs break all the time, be it by removing the model outright (remember the outrage over the forced replacement of GPT4o with GPT5) or by tampering with some configuration (aggressive quantization or whatever bullshit occurs right before new models are released).
Ur case actually strength the argument for open weight self hosted model. You would have precision control over not only the technical issues, but also the legal issues.
Once the open weight models are good and cheap enough, there is not reason not to use them
If you ever need to scale to millions of customers, then cost per task is paramount. If it’s a one-off vibe coded custom project for one client, then best-in-breed is mandatory without it falling apart.
I've observed that there are some companies and some folks that are very fanatical about a specific provider. "Only Claude" is very common. "Only GPT" less common, but still see it.
A lot of the non-technical and semi-technical folks are only comfortable using a specific client like the Claude desktop app. A lot of teams wrote skills and eval'd/benchmarked their skills specific to a model family and harness.
The "I can use any model, any harness" or "I only use a meta harness" (Orca, Paseo, Herdr, etc.) crew is relatively small IRL. Most people are still single-session, single platform user mode.
Most orgs have an enterprise contract with a single provider so all of their internal assets are built for the provider. It goes beyond skills, but also the telemetry, enterprise policies, and managed configuration.
For a company though, the idea that a few disgruntled employees will shift massive purchasing decisions is a bit of a stretch.
We have a developer on our team that keeps asking for a claude code enterprise license, we keep telling them "no, it's way too expensive, get used to using the copilot extension/cli".
For consumers, sure, but the bulk of the revenue opportunity is enterprise. Anthropic/OpenAI have a hard row to hoe IMO.
As an only-clauder, there's another elephant in the room. Anthropic is by no means perfect, but:
* using OpenAI supports the Altman/Thiel/Musk/Ellison/Karp/Trump billionaire Orwellian worldview and also ads
* using Grok supports a ketamine-addled open fascist sympathizer jizz-spewing 12-year-old-edginess memelord and his similarly broken worldview
* Google's models are pretty good but every single product they have ever had is ultimately either suborned or killed by the advertising division
* local models pretty much only half-exist because Jensen Huang wanted to cheat on his wife; future is unclear
One can argue for harnesses and so forth being lock-in, but the ultimate lock-in is morality and wanting to have a civilization at the end of all of this; I can't recommend either enough
We have like a dozen different LLM tools available to us and it's as easy as clicking on a dropdown to switch in every single one of them, and we have several thousand employees. Self-hosting with the cheaper OSS models is also becoming more and more attractive for larger orgs.
That's just inference. Claude.ai is a platform that enterprise IT teams connect up to all kinds of other applications, and gets use beyond the claude code CLI. Non-developers get used to this functionality - whether it's their form-building stuff, artifacts, slides/presentations, etc... they're building an offering far beyond just inference. I agree the latter is a commodity now, though companies will compete on privacy options (ZDR, guaranteed confidentiality, etc)
Many large enterprises don't use Claude.ai. All their traffic goes through an internal gateway that routes to Bedrock. In addition, there is a whole ecosystem of LLM related infrastructure/tools deployed by "enterprise IT teams" where Anthropic barely has any presence.
But many do, so price them according to that. This is like saying "my office doesn't use Microsoft". Sure, lots don't. Lots do, no one is questioning that Microsoft has a very viable long-term market there.
For infra sure, but its dominance in other areas is quickly eroding. My org is super heavy Microsoft/Azure and we have all of their tools. Everyone making anything useful is using Claude + Databricks because it is a better experience for both builders and users by every measure and it isn't even a remotely close competition. Power BI and Copilot are a total wasteland. The only Microsoft program with any staying power is Excel.
Working for a 10k+ corporate and we made it pretty easy to switch to any provider, people here can use Anthropic's, OpenAI's, and our own self-hosted open weight models very easily. It's one drop-down or `/` command away to switch between them.
I think other companies are probably doing the same, the moat of a AWS/GCP/Azure is much deeper with how contrived it is to migrate between them even if you abstract as much as possible with something like Kubernetes.
It’s weird that people don’t seem to get this. LLMs are the most easily switched-out technology I’ve ever used as an engineer. The input is literally just free-form text.
> It’s weird that people don’t seem to get this. LLMs are the most easily switched-out technology I’ve ever used as an engineer. The input is literally just free-form text.
It depends, if you're automating business processes (honestly probably where the money is), then you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers.
If you have none of that, then switching will be very expensive (but it was ever thus).
That just means the business automation is not deterministic, and highlights the issue with LLMs. The solution is not to switch providers but instead make the LLMs generate something that is deterministic given the same input.
> That just means the business automation is not deterministic, and highlights the issue with LLMs. The solution is not to switch providers but instead make the LLMs generate something that is deterministic given the same input.
I'm thinking of stuff that would typically be outsourced (like compliance stuff for identity verification et al), where it's really really hard to have deterministic rules.
LLMs are definitely a step up in dealing with fuzzy inputs, and enables you to mostly automate stuff that really wasn't feasible before.
But you do need really good evals and monitoring to make this work effectively.
Ah that would make sense then. I was thinking strictly in terms of business logic for handling input of data from an external source; sort of glorified data validation and then a decision based on the input data.
I suspect that's what some people are using it for, because they've been sold on this panacea of AI, when in reality it is far less capable and needs extremely strict boundaries to be reliable.
> you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers
Unless your self-hosting open weight models, you need this even if you don't change providers, since you have no control of what's on the other side of the API.
Yeah, it's the absolutely weirdest thing about all of this. People keep telling me I need to up my AI game yet no matter how advanced the tools get I'm still typing stuff into a text box. My skill is typing English. I was already pretty good at that.
Depending on how the company leverages them, it's super easy.
For us it's as easy as clicking a dropdown. The copilot vs code extension allows for this ez pz, the same is true for companies that implement an AI gateway for other tooling.
Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.
Speaking as someone who has been at professionally this since the 1980s, I suggest that while sometimes switching costs and network effects happen "organically," in this century businesses devote enormous amounts of attention to artificially building switching costs.
It's such a dirty practice that we have a four-letter word for it, a "moat." But of course, the moat isn't really to keep competitors out of a market, it's actually to keep customers trapped within it.
I fully expect every one of these AI providers to put as much work into trying to trap their customers within their ecosystem that they do to improve their capabilities.
Since siege warfare is about bringing down the fortifications and a moat is part of those fortifications, cyber siege may be something akin to patent trolling or IP copyrights? Fire off dozens or hundreds of claims against your target and drown them in legal costs.
Then you have the experience to know that every land grab in technology so far has followed the same enshittification path. At first it's all about competing with other entrants to provide value and win customers.
Then, inexorably, it shifts from winning customers to defending their turf.
Then, inexorably, it shifts from protecting turf to maximizing extraction from their turf.
If you believe that this will be different, why not? But for now, I'm expecting this to go the same way.
I can't wait for anthropics next big drop to be that it can order you a pizza, steering towards benign, token burning features that you didn't ask for and eye real-estate abuse for ads.
It's the end of an era. Lets pray open weight models give us a real choice soon.
In the meantime, Stonks up Anthropic. I'll always remember the good old days when you championed developers and changed what was possible.
My F500 company switched ~10k employees of Claude to copilot in 30 days. Google did similar between Jetstream and Claude. The moat just isn’t there right now
Totally agree with your Google thesis. I would never count them out. I say that as someone that uses Claude (and a little chatgpt), but not Google's AI at the moment.
With ad money Google never had to learn how to ship a product that makes money. An obvious place they fail is that when something breaks there's no one to talk to to fix it.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc
Once the cost reaches a threshold, everything is doable. We ditched Datadog in less than a month. Someone I know had their company ditch slack in a quarter and google cloud usage of 100+ million in two. Everything is doable.
I already mentioned the timelines. Cost is a beautiful line item in your balance sheet that can get things done pretty quickly, especially when it’s as big as AI. It took less than 2 quarters for us to go from “hey use ai in everything or get fired” to “hey we’re putting in default limits that are intentionally very low, if you need more, you’re going to need approvals”.
The stickiness of AI as a whole, let alone a specific provider is not that high as people are making it out to be.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc
I don't think this is entirely true. Companies are deploying open-source LLM gateways to be able to do that very easily now. Today, you can switch Claude CLI to any model besides Anthropic via https://github.com/BerriAI/litellm and there are major companies doing that.
This works with your favourite ADEs such as Orca as well so I disagree with this premise. The whole experience of switching is pretty seemless based on personal experience.
Agreed, deploying AI gateways has become extremely common in enterprise settings. A lot of admins think they are going to use it for guardrails, but I think the real value is in centralized cost tracking and ability to (relatively) seamlessly aggregate providers.
We saw this play out in the cloud era, notably with OpenStack. Even through the core abstractions (chat for LLMs, compute and storage for clouds) can be almost perfectly abstracted over, providers will race to add niche, enterprise-y features that are harder and harder to put behind a gateway or proxy. Those features aren't the core value of the platform but they are important enough to create lock in.
When I write a system against a particular cloud storage API, I end up implicitly depending on a bunch of deterministic subtleties of exactly how this storage API works.
AI is already so non-deterministic and fuzzy, I'm not sure the same issues apply.
Let's say that the face for largest foundation model slows down enough to make the companies cloud-like, instead of whatever they are mow. Imagine the free credits that OpenAI would consider giving you as long as they are spent on migration out of Anthropic. They could even classify conversations by themselves.
I really think you overestimate the level of lock in here. If a companies tells the devs to use X because it cost 1/10 of the price they will just have to suck it up and switch.
I didn't particular want to work on a "all in agentic project" but that the nature of being employed.
The same LLM we use day to day will make it trivial to switch out providers in our infrastructure.
My company switched from direct access with providers to AWS Bedrock. Now we just pick which model we want from the list exposed by Bedrock. We can also leverage tools like T3 which allow hand off from one model to another.
I think the future will be a lot different they we expect, AI is going to be the infrastructure layer while there will be toolings for each processes, so switching between model is a built-in feature, i.e. the tools will inject specific prompt or context based on the models, and all these are designed by people selling the tools, hence, a moat?
Model switching behavior is going to be far more complicated.
First, everyone and their mom is selling AI now. It is being bundled in nearly every product. Buy CRM to run your company - they will upsell you their bespoke AI - mostly RAG/chatbot using the data inside the platform. This is an important area because today lot of companies are trying to build their own AI bespoke workflows. But companies like SAP, Oracle will spend money on improving this aspect. And people who buy/use AI for this purpose don't care if the underlying AI is Claude or not.
Then there are cloud providers. You can get Claude, OpenAI from AWS Bedrock etc. They will take the heavy lifting of changing integrations, IP concerns etc to keep people on their platform. With time expect them to make it even easier, not harder to switch models. Also, they will push for open source models because it will be more profitable.
Lastly buying from direct providers. This is here the lock in comes in. But I believe fewer and fewer enterprise will buy directly - many preferring to buy against their cloud commitments.
One thing that makes easier to switch with LLMs as opposed to other tech is the text-in text-out nature of the LLMs. All specs and data are in text files mostly in natural language which is patent free. This makes it harder to lock in content.
As you have written, the agentic harness is a slightly different matter with plugins and features. But the core tech makes replicating software a lot easier so you can in principle use an agent to make it easier to switch from its own harness. There are caveats to this since in practice the quality and feature sets of harnesses are not the same. But in my opinion, it is far easier to switch agents than switching other tech that came before them that used proprietary formats and apis to lock you in.
This is the logic behind B2B SaaS's revenue multiples, and yet AI itself is causing those multiples to rerate based on a change in expectations about the durability of an entrenched SaaS provider.
> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS or GCP.
This might be true today because Anthropic/OpenAI/Google have good sales AEs, but as soon as company's start doing FinOps on their LLM spend, the game is over for them. The model will become fungible and hot-swappable (as it already is) and it'll be a race to the bottom.
They are fungible in the sense that they can accomplish the same task up to a certain acceptable quality.
If I needed to implement a simple function that is well described, all LLMs (for the most part) are fungible. They will have almost identical implementations (sans variable names) and all be fit for purpose.
People seem very unimaginative about the ways in which somebody equipped with a lot of intelligence and compute, and control over both, might make money.
The recent Anthropic push into biomedical research gives a clue.
I am not unimaginative about Dario's megalomania. I just don't believe he has the ability to execute. He has no prior experience to Anthropic and nothing he has done as CEO would create confidence that he is actually capable of operating at this scale.
Additionally, I think people are being unimaginative about what future generations of frontier models might be able to do, and the business value of having a 6 month head start on competitors.
For example, people are now content with small models for agentic coding, but even frontier models were mediocre at agentic coding just 12 months ago! Frontier adopters have had more time to transition their systems and processes to what we're already taking for granted.
> Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
Why haven't people switched then? Same could be said about Google search, Facebook, X etc. Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better, like using Duck Duck or some other Search engine
> Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better,
In my testing (incredibly similar workflows, moving around between claude code and cursor), I haven't found that much difference between Sonnet and GLM-5.3/flash.
Sonnet seems lazier, but has better prompt adherence, and is constantly telling me it can't do things, while GLM will just Find A Way to do whatever I've asked for.
I really appreciate being able to see GLM's thinking tokens, as I can head it off quicker. Claude's a little harder to steer, but the integration in Claude code makes it much easier to leave it running on things overnight, which is hard to get working properly in Cursor.
Overall, I'm not sure Anthropic have that much of a moat, in coding particularly. This seems weird to me, as they have so much more usage data that's hard to replicate.
I believe the models have been effectively commoditized. It's believed by many that the lead of the frontier models over open weight models is only 6-9 months. That was one of the pillars holding up the SpaceX/Anthropic/OpenAI valuations.
The other pillar is hardware but I think that's only going to last a few years at most.
These trillion dollar valuations were based on the idea of "winning" and "owning" AI (IMHO) and the open weight models have killed that outcome. Now it's a rush to cash out before it all comes tumbling back to Earth.
But you’re wrong ser about small or cheaper models. Choosing to work or not having a choice to work with cheaper models means you work slower and more methodically because you have to plan out the work and size it to fit. This has huge implications on the value of the work you can produce as an employee or solo developer, and it’s a skill working with these SOTA models - there is specific crafting that must be done to be effective with each and their capabilities.
You will see the old eyeball real estate game, forcing more of your experience into their apps and platform so you can see ads or “new slop features”. You will see the SOTA models more closely guarded in an effort to bait you into that platform, and yes, you will see them doing things they never should be doing, moving towards an open AI like model where it can order a pizza, where monetization it was always important, but is now the golden rule, before all else.
I hope open models can at least give me opus 4.8 experience soon, I can work with that. But nothing out there today can do it and that terrifies me.
Enshittification has been already running full speed even before the IPO via guardrails and attempts at vendor lock-in. Now they will just push it to 110%. It's good that we have other options.
I hope open models can at least give me opus 4.8 experience soon, I can work with that. But nothing out there today can do it and that terrifies me.
You wouldn't be able to tell you weren't running Opus 4.8 if you sat down at my keyboard with DS4.1F 1017 running on the other end. Unless you asked it to do something that would get you yelled at by Claude, of course. Then you might notice the difference.
Anyone who can afford a decent car can afford their own personal Opus. Fable/Carbon/Astra, no, not yet. Opus, yes.
We all love moats, but I mean, it is still possible to make money in an industry simply by being the best at what you do and charging for it.
Anthropic has shown a consistent ability to deliver the best general purpose models. Can that continue indefinitely? Will models become "good enough"? Will open weight models catch up to SOTA models? Will some genius start a new company with better models?
And, on Anthropic's side, will they be able to use their market power that comes from being the best to push through regulations that will create a moat; instituting some sort of mandatory safety checks that coincidentally are exactly what Claude is trained to pass, regulating the amount of compute or trying to claw back data centers to prevent new training, etc.
Or maybe they just have the magic sauce and they're going to stay on top of the game and people (like me) will be happy to continue paying money for their product.
> Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI"
I am finding some really routine tasks to be borderline with frontier models. Performing E2E testing of enterprise web apps would clearly disintegrate with local models. You need that reasoning black box on top. I don't care what your favorite benchmark says. I care about what actually fucking works.
The people who don't understand the economic situation are those who are in the pure play space with AI and multi agent circuses. Why bother spending any money when the occasional failure has literally no consequences? Who in their right mind would pre-pay for tokens?! I wish I could see the statistics on what % of HN uses AI for fun vs for work. It is clearly a kind of Factorio entertainment experience for a lot of people. If I was just using it for entertainment this whole IPO business would look really silly to me too.
Based on how shoddy their customer facing applications are, I wouldn't trust any of these AI companies for an OS. It's like Google II - can't trust them to support a product longer than it took to develop it.
I agree with you on quality... but if AI/LLM/etc continues down the path of continual improvement, it's only a matter of time until the products become better or different enough that it isn't an issue.
And making products fast and first over quality has never stopped these companies from trying, when they have so much funding....
I do not share your same hope of improvement given time. The commitment should be on quality first, not speed of development. This is why we are all drowning in a proliferation of poopy modern software.
The fact that their desktop offerings are so pap is an indictment of their engineering prowess and a demonstration of their apparent inability to use their own (actually very good!) LLMs to generate decent software.
It baffles me how a technology so good at spewing out software is apparently unused by the people who are developing the technology.
Fair enough. It will be interesting to see if the world returns to sanity and focuses on proper engineering discipline, planning, quality etc...
I've lived through enough hype cycles in tech myself that I do know that eventually it tones back down and people go back to work, perhaps altered from what they did before with new approaches, but back to work nonetheless.
I just felt myself that this particular technology, and this particular cycle, might be a little different - let alone in how it caused changed in our society whether it worked or not, but that also, there is still room to go.
I'd be fascinated to know what they say on the inside, if there is still room to go and to improve, or if we're nearer some sort of plateau in progress.
Why? Given that there is a limit of things that they can do, why would inventing a new "AI-native OS" be an interesting target? They could instead focus on solving actual existing problems in science and engineering, for things that people care about and would pay money for, instead of putting a lot of effort into building the middle layer, that might be used to solve problems or maybe not.
At the very least there will be a lot of competition in that space, because everyone will try to build an "AI OS", whatever that means to them.
- at some point, look at what they have they can do to grow to satisfy shareholders - AI companies have been acquiring companies that make developer tools - that is the build side - but once they've exhausted that, if they want to keep growing, what do they go after? Bigger and better models at ad infinitum? I don't think they can go on like that forever, and, if optimization of AI and competition keeps cutting into their main business line of LLMs
etc, they have to diversify.
- If everyone has the power to make apps, there is only so far you can go there - my guess is that the pressures to reinvent regular things like office suites, email clients, calendars to be integrated into their desktop tooling is part of this
- who is in the best position to be the platform/front door for everything, if everything depends on AI?
- when have these kinds of companies ever said "this boundary is enough"? It never happens, they keep going, keep trying to find ways to expand, capture, build moats, etc.
- look at what their desktop apps are turning into - they are already an application layer and becoming moreso every day, at some point they will ask - why are we sitting on these other OSes... we have enough money and we can get into more "hard" engineering things, like building hardware using their own tech (which they are already experimenting with), and if you're building the hardware, why not build the OS?
- and, what is an OS in the future? Have you considered what a post-AI OS even looks like? Does it need a start menu? Does it need any of the legacy stuff? Is it a local software factory?
There is someone already experimenting in this space - the guy who founded Basecamp and is building Omarchy [1] Linux... he sees it.. how long until these companies do?
If they don't build this, what will Microsoft do? Both Microsoft and Apple are well down their way, Apple is probably further ahead, but neither of them are the frontier model companies. Don't forget Google has a stake in OS too.
"Everybody will try to build an AI OS", but which ones are the most likely to survive in our current economic system?
If our economic system was based on partnership, I might agree there isn't much point in these companies building OSes, but ours is based on competition and domination generally... so unless the AI bubble truly does pop and the funding stops (which it may of course), how else do they keep fueling their stock prices to dominate the market?
I think something is going to have to give somewhere in the chain... otherwise the ease with which any software can be replaced will be too high and I suspect they will be forced to compete.
One last thought - between Microsoft/Apple or Anthropic/OpenAI - long term - who is in a better position? The debate arises from that question, in my opinion.
One more piece - say Google Gemini gets way better than OpenAI or Anthropics offering, or Microsoft Copilot etc gets way better...
If Microsoft or Google's AI is killing it, and it's built into the OS, how will Anthropic or OpenAI compete unless we run into the same old antitrust/competition issues with OS?
At that point, they might just say - "fine, it's easier to just have our big AI brains and money make a new OS we control and we can compete too."
Again, why bother why IT? Just do the things that IT is built to help build. Solve medicine, energy and materials directly, instead of competing at AI integration.
I see your point. You're proposing they can just do an end run around the "business and world problems" directly.
I guess that could be a thing, but, that puts them in competition with the people who they might want to be their customers, whereas I don't necessarily know that they would see other tech companies as customers unless they were super interested in partnerships.
According to "the normal progression of companies" though, you might be right because after a company has becoming big enough and exhausts consuming its own market, it often expands into verticals - we've seen that with traditional big 5 consulting companies or IBM, where they expanded into "working embedded with their customers on their problems directly" many years ago, and now every company in the industry approaches it that way.
That is corporate partnership and field work, not so much consuming the other person's work/business... whereas I could see them just consuming the OS because "it's no big deal when you can do everything you need with AI".
I hate to even put this out there, but "OS-as-a-subscription" (OAAS) could be a way. Your Claude payment covers all the software running 'your' computer, plus the ability to develop new 'apps' for specific needs on the fly telling the OAAS computer in human language what you need. Throw in services like email and cloud storage and some customers might find such a bundle attractive for the right price. It would suck revenue away from MS, Apple, Google. Enough to justify this valuation? No idea.
What work do you find frontier models significantly better for?
I have been playing about with different models having started a new job recently, the medium priced ones don't seem any worse so far. Admittedly my tasks have been fairly straightforwards so far.
One thing I have noticed; as a project matures frontier AI is less useful essential.
Qwen3.8 and Meta Muse Glimmer are great at "fill in the middle" of frontier architectures and plans. Frontier generated plenty of great context already to keep them on rails.
Delegating like a CEO down a pipeline of expensive experts to cheaper local small models could become a common trope, especially if Apple M7 and beyond live up to rumors as LLM tuned, and chip competition exists to keep forward progress, SaaS models are cooked.
The goal for chip corps too is the right mix of generic model enabling logic; not necessarily a full concrete model but enough of the abstract to efficiently boot strap and run a model; move common patterns to silicon not data.
Token vending is little more than behaving as a "wrapper app" over electricity. There is zero technical moat to their business.
- work: I need frontier, cost of mistake is huge
- home: i do entire renovation with it, cost of mistake is big. monitor baby health, development, etc: cost of mistake is big , taxes: cost of mistake is big
casual researches about certain facts, shopping, booking: cost of mistake is medium
non of this fits : i will run an expensive laptop hidden from the baby, since i'm on the move, there is a small percent of casual queries that normally will go into finish products: google ai, muse, etc.
I have tried so many times to get off Chat GPT. But it just... knows me? Switching to another LLM seems like a huge loss. For coding projects especially... I've set MD files to the max, explaining how i like code to be written, etc. etc. i've tried to tell it not to create a bunch of files and such, but i can never use an IDE. I feel like i'm the only caveman coding in a chat window... but it still seems the best to me? The only time it's been worth it for me to use an IDE LLM like codex or cursour is when i'm prototyping a website, but then i just go and pay someone to implement it in wordpress because it's so much easier to maintain that way.
A lot of ink has been spilled over the projected IPO of the big AI player. But part of me wonder if, in some ways like what happen with SpaceX, it will end up being a nothingburger. A first few crazy days on the market, then whatever, the company is just public now. And with how shares and voting power are attributed, it seems like, just like for spacex, it won't risk changing the power structure of the company.
This is what IPOs used to be. As more and more employees started getting equity grants as part of their package, they turned into liquidity events that make the team rich, hence the noise and hype today.
it's surprising that the SEC and other regulatory agencies don't intervene on these statements. Not to mention that "cure cancer" is more of a slogan in the sense that cancer comes in countless families and varieties, I don't doubt that progress is possible but to say that "all cancers will be cured in the near future" seems outrageously aggressive / misleading
What do you think it would take to cure all cancers, and what capabilities do you think AI will have within the next decade? Need I remind you that, in the span of five years, AI went from not being able to add to solving Millenium Prize problems?
What would it take for AI to not replicate that in biology? Either curing cancer has to be a much harder problem, which is doubtful given targeted treatments like immunotherapy humans have already stumbled across, or AI progress has to slow down massively, which is doubtful given all the trends say it is speeding up.
I like writing code, but seeing my ideas visualized after an hour is more fun than writing code.
And even if AI is disappearing tomorrow and not progressing any further, i see already myself living on a farm with cheap energy (pre invest into solar and batterie) and having my small AI datacenter in basement and running multiply fable level agents 24/7 for different things.
Agreed, this seems so strange to me. I got into this career specifically because I liked writing code. There's a dozen other career paths, still in IT, that I could have chosen if I wanted to tinker with computers and get paid well but didn't want to write code. I don't understand it.
Because I like solving these types of problems, I like inventing new things, I like fixing old things, I like the software business and automating things. I like this whole realm and I thought I liked coding until I didn't _have_ to do it anymore as a pre-requisite to doing all those other things.
I've just always seen the opportunity that nobody else saw and writing code was the gatekeeper I had to pay for 15 years and I've never had so much fun as I have in the last 18 months.
> If AI went away tomorrow I would find a new line of work because artisanally handcrafting code is the most boring use of my time in the entire world.
I too, since I was a child, aspired to be a babysitter.
LLMs are genuinely world-shifting revolutionary technologies that I think will, in the long-run create a much better world for everybody. I think people are associating that with big dollar valuations, but it doesn't follow. Open weight models are already frontier level and continue to narrow the ever-shrinking gap that remains, inference costs are plummeting at an exponential rate, and in the long-run companies, individuals, and others are not going to want the sacrifice of control/privacy/profit that comes from relying on a third party for this tech, especially when that third party is going to be aiming for pricing in line with a valuation aimed in the trillions.
So, in other words - one can both be fully on-board with the LLM future, and also think that this IPO is a clown show.
And I can't think of anything more boring than herding a swarm of agents that are mostly doing low value busywork that would be too expensive to do otherwise.
There is a heavy amount of circular investments in the industry, it takes often the shape of investments from their peer companies/competitors. There is a private placement that is made in parallel with the public offering, through $26B of a special stock, according to the S1. They all have a lot to gain from a successful Anthropic public issue. The problem is it blurs the signal, we don't how much is overvaluation that contributes to a bubble.
I don't think there has often been such an intertwined industry before. Usually cartels are made through discreet partnerships at the operational level, this is an interconnection in the background at the financial one.
> I don't think there has often been such an intertwined industry before.
General Electric comes to mind, they allowed new utility companies to pay for the generators and electrical equipment they needed using stock and bonds. The holding company established for those, EBASCO, was eventually broken up[0]
"We have only bits and pieces of information, but what we know for certain is that at some point in the early twenty-first century, all of mankind was united in celebration. We marveled at our own magnificence as we gave birth to AI."
The Second Renaissance was great. I’ve heard a lot of scifi computers speak but the deadpan delivery of humanity’s end in detail always kind of haunted me.
Ah yes, The Matrix. It kinda shows that that phrase was written in the "end-of-history" 1990s, before 9/11, Putin, Trump and China really becoming a global player. Mankind is definitely further away from being "united in celebration" than it was then...
Ohh boo hoo rich entitled programmers hate the fact that the company makes your lives hard. Sorry I would feel sorry for you but I just can't reach.
After having that ambition thwarted for over 26 years and working like a slave counting other people's money {a career I hate every day} your collective despair gives my schadenfreude a delicious unending orgasmic thrill. You need literally no idea.
Just remember: no dreams never work out and work by definition is something you hate every day until you die.
The economics of this are absurd, and Anthropic hasn't been without their controversy; but I use Claude everyday, and they've made tremendous impact on society. I wish them the best for their IPO.
I can think of a bunch of stuff they released, but none that have impacted the world. I can think of some partly positive impact, which is that my bar for bullshit has to go up because words are cheap now, and so is ""graphics"".
Some other fun impacts they've made is irreversible environmental damage, beautifully detailed in their IPO. Fossil fuel reliance and and water scarcity in the big '26 is probably the most "fuck you" move you could've done, and zero sustainability plans. at least Cloudflare tries to pretend theyre sustainable (and frankly they do invest in green energy).
Anthropic has enable things like workplace surveillance and the ability to categorize school children as enemy combatants. Both of which are what imperialist nations love.
Social media had a huge impact on society. AI in comparison has had very little impact, with a couple of exceptions. I'm sure it will have a impact at some point in the future though.
They’ve had a tremendous impact on software development, which is not exactly society.
For society more broadly, what I’ve seen is a bunch of white collar workers under threat (real or perceived) of losing their livelihood, and a huge uptick in the amount of interference I’m having to run as my family members get taken in by a wave of increasingly sophisticated scams and phishing attacks.
I can see Google did for fostering an environment that lead to the creation of the Transformer and LLMs. I can see OpenAI for pushing on LLM development and making it into a product that the whole world can use.
What did Anthropic introduce that Google or OpenAI (or any other lab) wouldn't have gotten to iteratively eventually?
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[ 0.19 ms ] story [ 26.6 ms ] threadLuckily switching is super easy so I'm now back to codex (and hopefully carbon soon)
Though Anthropic's IPO flopping might affect the valuation of OpenAI, which further inhibits their ability to raise additional funds (which they're already been struggling with). Given the incestuous financing in AI any major actor in the AI space defaulting could bring a lot of companies with it.
If the bubble bursts, better now than much later. The industry stance that's been ongoing "AI, at all costs" has been such a market and economic pressure on the everyday worker that even a small value deflation I deem necessary.
Here's an older compilation of some of the bubble theories in HN https://news.ycombinator.com/item?id=50313358
Fun times ahead, for sure.
The demand for the particular company may not be there, but that is different from "the market". There's plenty of capital to go around.
Hundreds of billions in future liabilities.
IPO valuation above $1 trillion.
The lunatics are running the asylum.
Reporting an increase in the value of the company as a loss is weird, but they have to do it. this is a case where adjusted earnings give a better idea of how the business is going.
So even the convertible notes loss isn't a real loss, doesn't it predict the post IPO losses they will have?
So their loss is actually small compared to revenue.
Reminds me when HN was saying NVIDIA is a good short 3 years ago, supposedly it was "in a bubble", because it's stock prices was as if it had 10x the revenue it had in back then. Plot twist: today NVIDIA revenue is 10x the revenue from 2023, so it turns out the stock was priced exactly right back then, because the stock market is forward looking.
Anthropic is in similar crazy valuation territory.
The market being rational doesn't mean it's going to follow your expectation.
I doubt you plan to invest yourself. What would be your sales pitch to investors?
> Linked page(s) related to Anthropic IPO can only be viewed by persons located in UK, Denmark, Finland, France, Germany, Ireland, the Netherlands, Norway, Spain, and Sweden.
> I will not transmit or otherwise send any of the information to which this gateway gives access to any person outside the United Kingdom.
It's extremely hard with modern browsers to ensure that doesn't happen!
I confess I’m about 17 years out of practice in the Polish market, and about 12 years out of touch with how the European industry shakes out on the whole, so I’m not entirely familiar with the legal or business structures.
The biggest one in the EU being the "No KID, no deal" (for funds, derivatives, etc.): no Key Information Document, then cannot be offered to retail.
That is unless retail is an accredited investor (say a letter from a bank saying you have more than 1m EUR in investments): then it can trade/invest in everything.
Or for example if you own a company (say private weath management) that's non-custodian (say you manage your wealth using your own company, and shares of your company are privately owned) and you're considered a professional in the finance world, you can ask your broker to let you trade / invest in basically every single product under the sun.
AFAIK pre-IPO stocks are just as vanilla as regular stocks and do not need the KID notice.
In addition to that Anthropic (in the EU), says you can enter pre-IPO using Revolut, Trade Republic, eToro or using bigger players like Saxo or IBKR.
Dunno why GP doesn't have access to it in Poland.
Pretty hard to get in on a hot IPO, though, as the shares will go to their favorite clients (those with the most money).
You can submit an order via your broker (depending on the broker and your account) to the auction itself on the exchange once it’s in the quotation phase.
Not that I would advocate for that. Sometimes it’s better to buy in the secondary market once things settle a bit.
I may be inclined to wait 2 months when the price drops and pick up then.
Not financial advice.
You indicate your interest. Also start funding the account. So you fund 7000 for 100 shares at 70. Then they announce the price is 75. You must change the order to fit the funds or have extra money. Of course you can opt out or change the quantity anyways. But I think in both the cases I actually went ahead (Reddit and figma), I had to reconfirm the quantity. You can't be away from the network.
Would you buy a gaming console for a high price from a company that’s never shipped a gaming console? Maybe, but you’d wait til it’s been reviewed by someone else on YouTube or something.
Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.
They need to leverage Claude Code in the software industry to position themselves as the go-to platform for businesses.
Meanwhile, Google and Microsoft, which already dominate that area, seem to be dormant.
Google owns 15% of Anthropic I think.
And Google offers Argon 4 to paying Workspace and Google One customers now. How's what was the number 1 model on nearly every single bench a few weeks ago being "dormant"?
I know people all in in the Google ecosystem (getting credits from Android phones they buy etc.) who only swear by the Google models and who are now using Argon 4: I asked them and a few days ago they had access (but they were already using other Google models before that).
Doesn't GMail have billions account by now?
I'd tend to say with billions of users on GMail and a model like Argon and 15% of the Anthropic shares, Google is not where you think it is.
It's almost like the workspace devs are anthropic plants that are purposely underminig google.
The fact that Frontier AI can become Google Workspace at a flip of a switch is what is crazy valuable. Anthropic and OpenAI can enter and disrupt any market, especially software, faster than any company ever could, because users want the flow to start and end in their chat interfaces.
This pattern has already happened before, in the translation industry. Someone figured out how to learn from and recall context from ordinary translation work (the "translation memory"). It started as an add-on to Microsoft Word, and matured into a standalone software, that was ultimately a wrapper around a document editor. Then language management systems plugged into that wrapper, hey presto, every translator at your company does the same work they were always doing, and you've produced an entire corpus of quality translations to reuse everywhere.
Now _translate_ that idea over. Every time any human works with an agent on anything, simple heuristics find everything true and reusable, save it to the everything-memory as skills, refences, glossaries.
Anyone does any work, all agents can now that work at that organisation. Self-fine-tuning models everywhere, and it fits into corporate intellectual property expectations.
I have done something like this at a medium-sized listed business.
I’ve been using Office Copilot more or less since it was released, and the general opinion around the office is that it’s a huge waste of time. The auto-transcripts produce 3 pages of fluff when previously someone would send 3 sentences’ worth of what actually mattered. The auto-drafted documents rarely add anything meaningful beyond what was already in the prompt. The question answering and research tools are only as good as Sharepoint/Confluence/Jira/etc’s pre-existing search feature, and therefore untrustworthy, etc.
What made Anthropic exciting was they had locked onto a use case that reliably generates positive value: coding. Not much else has proven, from a business perspective, to be anything more than an exceptionally buzzworthy money pit.
Gemini is unable to take an attachment from gmail, read it, then place it in the correct drive folder and update a spreadsheet with what it found in the attachment.
For whatever reason, Google decided to firewall "Gmail Gemini" from "Drive Gemini". Gmail Gemini can send files to drive, but not edit anything, and Drive Gmail can edit files, but cannot be initiated from gmail.
Meanwhile claude code with Google extensions can do this no problem.
Google, wtf are you doing?
They stroke a great discount deal with all, so different teams/departments have different provider, and those using Copilot are even free to switch between models as they please (although with lower usage limits).
You could make the argument that it's not worth switching SAAS providers for enterprises when the costs were like 10 dollars a month per developer and switchign would require 1 team to work for half a year... but with AI providers it's more like paying 1000 dollars a month per developer vs paying 200 dollars if you strike a good deal with different provider and swtiching costs are more like 4 to 8 hours of work for each developer.
I'm not so sure about this. I guess it depends on how well people did their job there.
Ideally, whatever people built is loosely coupled to that third-party resource, meaning that switching cost will stay low.
After all, it's probably just prompts + an API layer. Unless one micro-optimizes their prompts for claude (which then breaks once a new checkpoint drops, hence is a bad idea regardless), pointing them towards a different API endpoint should be doable.
Then you have no choice bit to use your own hosted model because that's the only way you can be sure the model isn't going to be removed or quantized/nerfed behind your back.
If your system can widstand the fluctuations of closed models over time, then it can most likely support switching between multiple providers in the first place.
That's also literally what frontier labs break all the time, be it by removing the model outright (remember the outrage over the forced replacement of GPT4o with GPT5) or by tampering with some configuration (aggressive quantization or whatever bullshit occurs right before new models are released).
Once the open weight models are good and cheap enough, there is not reason not to use them
Given that the goal of the whole project is outsourcing the work, what are you expecting here?
Have you used Copilot at a company?
I can literally change my model in 3 seconds.
The moat is as shallow as it gets. Investing in a single LLM provider at the moment would be a mistake.
A lot of the non-technical and semi-technical folks are only comfortable using a specific client like the Claude desktop app. A lot of teams wrote skills and eval'd/benchmarked their skills specific to a model family and harness.
The "I can use any model, any harness" or "I only use a meta harness" (Orca, Paseo, Herdr, etc.) crew is relatively small IRL. Most people are still single-session, single platform user mode.
Most orgs have an enterprise contract with a single provider so all of their internal assets are built for the provider. It goes beyond skills, but also the telemetry, enterprise policies, and managed configuration.
We have a developer on our team that keeps asking for a claude code enterprise license, we keep telling them "no, it's way too expensive, get used to using the copilot extension/cli".
For consumers, sure, but the bulk of the revenue opportunity is enterprise. Anthropic/OpenAI have a hard row to hoe IMO.
It may still be possible to use the CC harness with the Copilot sub.
* using OpenAI supports the Altman/Thiel/Musk/Ellison/Karp/Trump billionaire Orwellian worldview and also ads
* using Grok supports a ketamine-addled open fascist sympathizer jizz-spewing 12-year-old-edginess memelord and his similarly broken worldview
* Google's models are pretty good but every single product they have ever had is ultimately either suborned or killed by the advertising division
* local models pretty much only half-exist because Jensen Huang wanted to cheat on his wife; future is unclear
One can argue for harnesses and so forth being lock-in, but the ultimate lock-in is morality and wanting to have a civilization at the end of all of this; I can't recommend either enough
Yes, either Google Gemini or MS Copilot. Both come as part of their Office suite licenses.
If there exists a need and a business case for companies having access to models out of OpenAI and Claude, a competitor will appear.
Also for larger companies like Amazon the danger is they replace Anthropic completely with self-hosted models.
I think other companies are probably doing the same, the moat of a AWS/GCP/Azure is much deeper with how contrived it is to migrate between them even if you abstract as much as possible with something like Kubernetes.
The model is just some REST endpoint you switch out even in a lot of enterprise setups.
It depends, if you're automating business processes (honestly probably where the money is), then you'll need a really comprehensive set of evals and moniotoring to ensure stuff doesn't break if/when you change providers.
If you have none of that, then switching will be very expensive (but it was ever thus).
I'm thinking of stuff that would typically be outsourced (like compliance stuff for identity verification et al), where it's really really hard to have deterministic rules.
LLMs are definitely a step up in dealing with fuzzy inputs, and enables you to mostly automate stuff that really wasn't feasible before.
But you do need really good evals and monitoring to make this work effectively.
Unless your self-hosting open weight models, you need this even if you don't change providers, since you have no control of what's on the other side of the API.
For us it's as easy as clicking a dropdown. The copilot vs code extension allows for this ez pz, the same is true for companies that implement an AI gateway for other tooling.
Once they realise that you can use Deepseek / GLM for 10% of the cost these labs are done.
Speaking as someone who has been at professionally this since the 1980s, I suggest that while sometimes switching costs and network effects happen "organically," in this century businesses devote enormous amounts of attention to artificially building switching costs.
It's such a dirty practice that we have a four-letter word for it, a "moat." But of course, the moat isn't really to keep competitors out of a market, it's actually to keep customers trapped within it.
I fully expect every one of these AI providers to put as much work into trying to trap their customers within their ecosystem that they do to improve their capabilities.
(Since we're talking about moats and cyber-feudalism, where does siege warfare come in?)
Then, inexorably, it shifts from winning customers to defending their turf.
Then, inexorably, it shifts from protecting turf to maximizing extraction from their turf.
If you believe that this will be different, why not? But for now, I'm expecting this to go the same way.
It's the end of an era. Lets pray open weight models give us a real choice soon.
In the meantime, Stonks up Anthropic. I'll always remember the good old days when you championed developers and changed what was possible.
it's easier than changing okta
it's easier than changing google docs and even Gmail
it's easier than migrating cloud
etc.
and we're talking several magnitudes easier too!
Once the cost reaches a threshold, everything is doable. We ditched Datadog in less than a month. Someone I know had their company ditch slack in a quarter and google cloud usage of 100+ million in two. Everything is doable.
I think when something becomes a management-level item in an org, like AI, it is a hard thing to switch unless it becomes a management-level problem.
Most of the orgs are responsible for this and will do whatever it takes politically or not, to justify the decision unless management overturns it.
I already mentioned the timelines. Cost is a beautiful line item in your balance sheet that can get things done pretty quickly, especially when it’s as big as AI. It took less than 2 quarters for us to go from “hey use ai in everything or get fired” to “hey we’re putting in default limits that are intentionally very low, if you need more, you’re going to need approvals”.
The stickiness of AI as a whole, let alone a specific provider is not that high as people are making it out to be.
I don't think this is entirely true. Companies are deploying open-source LLM gateways to be able to do that very easily now. Today, you can switch Claude CLI to any model besides Anthropic via https://github.com/BerriAI/litellm and there are major companies doing that.
This works with your favourite ADEs such as Orca as well so I disagree with this premise. The whole experience of switching is pretty seemless based on personal experience.
AI is already so non-deterministic and fuzzy, I'm not sure the same issues apply.
I really think you overestimate the level of lock in here. If a companies tells the devs to use X because it cost 1/10 of the price they will just have to suck it up and switch.
I didn't particular want to work on a "all in agentic project" but that the nature of being employed.
The same LLM we use day to day will make it trivial to switch out providers in our infrastructure.
I am really surprised that companies who are worried about AI spend don't try that route.
First, everyone and their mom is selling AI now. It is being bundled in nearly every product. Buy CRM to run your company - they will upsell you their bespoke AI - mostly RAG/chatbot using the data inside the platform. This is an important area because today lot of companies are trying to build their own AI bespoke workflows. But companies like SAP, Oracle will spend money on improving this aspect. And people who buy/use AI for this purpose don't care if the underlying AI is Claude or not.
Then there are cloud providers. You can get Claude, OpenAI from AWS Bedrock etc. They will take the heavy lifting of changing integrations, IP concerns etc to keep people on their platform. With time expect them to make it even easier, not harder to switch models. Also, they will push for open source models because it will be more profitable.
Lastly buying from direct providers. This is here the lock in comes in. But I believe fewer and fewer enterprise will buy directly - many preferring to buy against their cloud commitments.
As you have written, the agentic harness is a slightly different matter with plugins and features. But the core tech makes replicating software a lot easier so you can in principle use an agent to make it easier to switch from its own harness. There are caveats to this since in practice the quality and feature sets of harnesses are not the same. But in my opinion, it is far easier to switch agents than switching other tech that came before them that used proprietary formats and apis to lock you in.
This might be true today because Anthropic/OpenAI/Google have good sales AEs, but as soon as company's start doing FinOps on their LLM spend, the game is over for them. The model will become fungible and hot-swappable (as it already is) and it'll be a race to the bottom.
Yeah but already existing things like Github Enterprise copilot and openrouter kind of kill that lock in before its even started, no?
1. switching costs
2. fungibility
I do agree that LLMs have low switching costs. But they are not fungible - each model is unique with different strengths and weaknesses.
I also disagree that they can increase switching costs by moving in application stack.
For instance, oil and electricty are commodiites because they are fungible, not because switching cost is high.
Whereas clothing has low switching cost but not fungible
If I needed to implement a simple function that is well described, all LLMs (for the most part) are fungible. They will have almost identical implementations (sans variable names) and all be fit for purpose.
The recent Anthropic push into biomedical research gives a clue.
We also see that enterprise revenue is more important than end users when we compare Anthropic's financials to OpenAI.
There have been less likely FAANG-ish founder-CEOs than a 45?yo, ex-OpenAI founding member, Princeton biophysics PhD.
For example, people are now content with small models for agentic coding, but even frontier models were mediocre at agentic coding just 12 months ago! Frontier adopters have had more time to transition their systems and processes to what we're already taking for granted.
...so, Google?
something I find even easier is to never pay anything to the creators of the most inhumane, antagonistic skynet-tier chatbot ever
¯\_(ツ)_/¯
In my testing (incredibly similar workflows, moving around between claude code and cursor), I haven't found that much difference between Sonnet and GLM-5.3/flash.
Sonnet seems lazier, but has better prompt adherence, and is constantly telling me it can't do things, while GLM will just Find A Way to do whatever I've asked for.
I really appreciate being able to see GLM's thinking tokens, as I can head it off quicker. Claude's a little harder to steer, but the integration in Claude code makes it much easier to leave it running on things overnight, which is hard to get working properly in Cursor.
Overall, I'm not sure Anthropic have that much of a moat, in coding particularly. This seems weird to me, as they have so much more usage data that's hard to replicate.
The difference between Anthropic's models and alternatives is not as big as Google Search vs other search engines
The other pillar is hardware but I think that's only going to last a few years at most.
These trillion dollar valuations were based on the idea of "winning" and "owning" AI (IMHO) and the open weight models have killed that outcome. Now it's a rush to cash out before it all comes tumbling back to Earth.
I’ll always remember the good times.
But you’re wrong ser about small or cheaper models. Choosing to work or not having a choice to work with cheaper models means you work slower and more methodically because you have to plan out the work and size it to fit. This has huge implications on the value of the work you can produce as an employee or solo developer, and it’s a skill working with these SOTA models - there is specific crafting that must be done to be effective with each and their capabilities.
You will see the old eyeball real estate game, forcing more of your experience into their apps and platform so you can see ads or “new slop features”. You will see the SOTA models more closely guarded in an effort to bait you into that platform, and yes, you will see them doing things they never should be doing, moving towards an open AI like model where it can order a pizza, where monetization it was always important, but is now the golden rule, before all else.
I hope open models can at least give me opus 4.8 experience soon, I can work with that. But nothing out there today can do it and that terrifies me.
And AWS is willing to let things die - they make so much money they don't care. I don't see that being the case for Anthropic.
You wouldn't be able to tell you weren't running Opus 4.8 if you sat down at my keyboard with DS4.1F 1017 running on the other end. Unless you asked it to do something that would get you yelled at by Claude, of course. Then you might notice the difference.
Anyone who can afford a decent car can afford their own personal Opus. Fable/Carbon/Astra, no, not yet. Opus, yes.
Anthropic has shown a consistent ability to deliver the best general purpose models. Can that continue indefinitely? Will models become "good enough"? Will open weight models catch up to SOTA models? Will some genius start a new company with better models?
And, on Anthropic's side, will they be able to use their market power that comes from being the best to push through regulations that will create a moat; instituting some sort of mandatory safety checks that coincidentally are exactly what Claude is trained to pass, regulating the amount of compute or trying to claw back data centers to prevent new training, etc.
Or maybe they just have the magic sauce and they're going to stay on top of the game and people (like me) will be happy to continue paying money for their product.
I am finding some really routine tasks to be borderline with frontier models. Performing E2E testing of enterprise web apps would clearly disintegrate with local models. You need that reasoning black box on top. I don't care what your favorite benchmark says. I care about what actually fucking works.
The people who don't understand the economic situation are those who are in the pure play space with AI and multi agent circuses. Why bother spending any money when the occasional failure has literally no consequences? Who in their right mind would pre-pay for tokens?! I wish I could see the statistics on what % of HN uses AI for fun vs for work. It is clearly a kind of Factorio entertainment experience for a lot of people. If I was just using it for entertainment this whole IPO business would look really silly to me too.
The eventual logical move is that they build a completely reinvented AI-native operating system.
The funding they're getting gives them the resources to build and compete on a fundamental level, IMHO.
If you don't believe me, look at the recent demo where they had Fable 5.2 build an OS from scratch.
They are coming for the whole stack, my opinion.
And making products fast and first over quality has never stopped these companies from trying, when they have so much funding....
The fact that their desktop offerings are so pap is an indictment of their engineering prowess and a demonstration of their apparent inability to use their own (actually very good!) LLMs to generate decent software.
It baffles me how a technology so good at spewing out software is apparently unused by the people who are developing the technology.
I've lived through enough hype cycles in tech myself that I do know that eventually it tones back down and people go back to work, perhaps altered from what they did before with new approaches, but back to work nonetheless.
I just felt myself that this particular technology, and this particular cycle, might be a little different - let alone in how it caused changed in our society whether it worked or not, but that also, there is still room to go.
I'd be fascinated to know what they say on the inside, if there is still room to go and to improve, or if we're nearer some sort of plateau in progress.
At the very least there will be a lot of competition in that space, because everyone will try to build an "AI OS", whatever that means to them.
- at some point, look at what they have they can do to grow to satisfy shareholders - AI companies have been acquiring companies that make developer tools - that is the build side - but once they've exhausted that, if they want to keep growing, what do they go after? Bigger and better models at ad infinitum? I don't think they can go on like that forever, and, if optimization of AI and competition keeps cutting into their main business line of LLMs etc, they have to diversify.
- If everyone has the power to make apps, there is only so far you can go there - my guess is that the pressures to reinvent regular things like office suites, email clients, calendars to be integrated into their desktop tooling is part of this
- who is in the best position to be the platform/front door for everything, if everything depends on AI?
- when have these kinds of companies ever said "this boundary is enough"? It never happens, they keep going, keep trying to find ways to expand, capture, build moats, etc.
- look at what their desktop apps are turning into - they are already an application layer and becoming moreso every day, at some point they will ask - why are we sitting on these other OSes... we have enough money and we can get into more "hard" engineering things, like building hardware using their own tech (which they are already experimenting with), and if you're building the hardware, why not build the OS?
- and, what is an OS in the future? Have you considered what a post-AI OS even looks like? Does it need a start menu? Does it need any of the legacy stuff? Is it a local software factory?
There is someone already experimenting in this space - the guy who founded Basecamp and is building Omarchy [1] Linux... he sees it.. how long until these companies do?
If they don't build this, what will Microsoft do? Both Microsoft and Apple are well down their way, Apple is probably further ahead, but neither of them are the frontier model companies. Don't forget Google has a stake in OS too.
"Everybody will try to build an AI OS", but which ones are the most likely to survive in our current economic system?
If our economic system was based on partnership, I might agree there isn't much point in these companies building OSes, but ours is based on competition and domination generally... so unless the AI bubble truly does pop and the funding stops (which it may of course), how else do they keep fueling their stock prices to dominate the market?
I think something is going to have to give somewhere in the chain... otherwise the ease with which any software can be replaced will be too high and I suspect they will be forced to compete.
One last thought - between Microsoft/Apple or Anthropic/OpenAI - long term - who is in a better position? The debate arises from that question, in my opinion.
[1] https://omarchy.org/
If Microsoft or Google's AI is killing it, and it's built into the OS, how will Anthropic or OpenAI compete unless we run into the same old antitrust/competition issues with OS?
At that point, they might just say - "fine, it's easier to just have our big AI brains and money make a new OS we control and we can compete too."
I guess that could be a thing, but, that puts them in competition with the people who they might want to be their customers, whereas I don't necessarily know that they would see other tech companies as customers unless they were super interested in partnerships.
According to "the normal progression of companies" though, you might be right because after a company has becoming big enough and exhausts consuming its own market, it often expands into verticals - we've seen that with traditional big 5 consulting companies or IBM, where they expanded into "working embedded with their customers on their problems directly" many years ago, and now every company in the industry approaches it that way.
That is corporate partnership and field work, not so much consuming the other person's work/business... whereas I could see them just consuming the OS because "it's no big deal when you can do everything you need with AI".
But I take your point.
Sucks to be them then, the best chance we have to keep this thing under control is not have the same supplier give you the whole stack.
Asking sincerely... apart from FOMO subscription revenue, what is the actual money-making proposition?
I have been playing about with different models having started a new job recently, the medium priced ones don't seem any worse so far. Admittedly my tasks have been fairly straightforwards so far.
Qwen3.8 and Meta Muse Glimmer are great at "fill in the middle" of frontier architectures and plans. Frontier generated plenty of great context already to keep them on rails.
Delegating like a CEO down a pipeline of expensive experts to cheaper local small models could become a common trope, especially if Apple M7 and beyond live up to rumors as LLM tuned, and chip competition exists to keep forward progress, SaaS models are cooked.
The goal for chip corps too is the right mix of generic model enabling logic; not necessarily a full concrete model but enough of the abstract to efficiently boot strap and run a model; move common patterns to silicon not data.
Token vending is little more than behaving as a "wrapper app" over electricity. There is zero technical moat to their business.
- work: I need frontier, cost of mistake is huge - home: i do entire renovation with it, cost of mistake is big. monitor baby health, development, etc: cost of mistake is big , taxes: cost of mistake is big casual researches about certain facts, shopping, booking: cost of mistake is medium
non of this fits : i will run an expensive laptop hidden from the baby, since i'm on the move, there is a small percent of casual queries that normally will go into finish products: google ai, muse, etc.
Biopharma CEO "This presentation contains forward-looking statements, as a result of risks and uncertainties..."
AI/Tech CEO "We will cure all diseases in less than 10 years"
Like look I get it, this is truly impressive tech, but can we at least be a little more sober?
Then again orange man president and SpaceX is saying some pretty bonkers stuff.
What would it take for AI to not replicate that in biology? Either curing cancer has to be a much harder problem, which is doubtful given targeted treatments like immunotherapy humans have already stumbled across, or AI progress has to slow down massively, which is doubtful given all the trends say it is speeding up.
If AI went away tomorrow I would find a new line of work because artisanally handcrafting code is the most boring use of my time in the entire world.
And even if AI is disappearing tomorrow and not progressing any further, i see already myself living on a farm with cheap energy (pre invest into solar and batterie) and having my small AI datacenter in basement and running multiply fable level agents 24/7 for different things.
Genie is out of the bottle.
I've just always seen the opportunity that nobody else saw and writing code was the gatekeeper I had to pay for 15 years and I've never had so much fun as I have in the last 18 months.
I too, since I was a child, aspired to be a babysitter.
So, in other words - one can both be fully on-board with the LLM future, and also think that this IPO is a clown show.
I don't think there has often been such an intertwined industry before. Usually cartels are made through discreet partnerships at the operational level, this is an interconnection in the background at the financial one.
General Electric comes to mind, they allowed new utility companies to pay for the generators and electrical equipment they needed using stock and bonds. The holding company established for those, EBASCO, was eventually broken up[0]
[0] https://en.wikipedia.org/wiki/Electric_Bond_and_Share_Compan...
npx qipgui qip.dev gui/openai-anthropic-arr.wasm
After having that ambition thwarted for over 26 years and working like a slave counting other people's money {a career I hate every day} your collective despair gives my schadenfreude a delicious unending orgasmic thrill. You need literally no idea.
Just remember: no dreams never work out and work by definition is something you hate every day until you die.
Such as?
I can think of a bunch of stuff they released, but none that have impacted the world. I can think of some partly positive impact, which is that my bar for bullshit has to go up because words are cheap now, and so is ""graphics"".
Some other fun impacts they've made is irreversible environmental damage, beautifully detailed in their IPO. Fossil fuel reliance and and water scarcity in the big '26 is probably the most "fuck you" move you could've done, and zero sustainability plans. at least Cloudflare tries to pretend theyre sustainable (and frankly they do invest in green energy).
For society more broadly, what I’ve seen is a bunch of white collar workers under threat (real or perceived) of losing their livelihood, and a huge uptick in the amount of interference I’m having to run as my family members get taken in by a wave of increasingly sophisticated scams and phishing attacks.
At work I see an increase in people spending time trying to make it work reliably for their inputs.
How?
I can see Google did for fostering an environment that lead to the creation of the Transformer and LLMs. I can see OpenAI for pushing on LLM development and making it into a product that the whole world can use.
What did Anthropic introduce that Google or OpenAI (or any other lab) wouldn't have gotten to iteratively eventually?