Edit: I should clarify that I don’t think this justifies their valuation. It puts them in competition with much more entrenched players with established customer bases, and who aren’t in massive debt to provide their compute. I’d also like to distinguish between a model provider as someone who provides weights vs a model provider who connects their GPUs and models to your codebase and internal systems - I think the latter is where the sustainable business is.
Incidentally this is why I still feel Google is well-positioned in the long-term AI race. If they can remove their head from their ahh and make a coherent product offering across Workspace, GCP and Gemini, they could become as entrenched as MS.
I would assume AWS is probably the most interested in acquiring Anthropic out of the three major cloud providers.
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.
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.
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'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.
Given that the goal of the whole project is outsourcing the work, what are you expecting here?
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?)
Once they realise that you can use Deepseek / GLM for 10% of the cost these labs are done.
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.
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.
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.
Also for larger companies like Amazon the danger is they replace Anthropic completely with self-hosted models.
I am really surprised that companies who are worried about AI spend don't try that route.
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.
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.
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!
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.
The model is just some REST endpoint you switch out even in a lot of enterprise setups.