This is exactly it. Selling the output of a LLM is going to an incredibly cut-throat and low-margin business.

The more interesting, novel, and useful work you wrap the LLM in the more defensible your pricing will be.

That said I think this can describe a lot of agentic code tools - the entire point is that you're not just talking to the raw LLM itself, you're being intermediated by a bunch of useful things that are non-trivial.

I see this with Anthropic most - they seem to have multiple arms in multiple lines of business that go up the abstraction ladder - Claude Code is just one of them. They seem to also be in the customer service automation business as well.

[edit] I think a general trend we're going to see is that "pure" LLM providers are going to try to go up the abstraction ladder as just generating tokens proves unprofitable, colliding immediately with their own customers. There's going to be a LOT of Sherlocking, and the LLM providers are going to have a home field advantage (paying less for inference, existing capability to fine-tune and retrain, and looooooots of VC funding).

This may be old fashioned thinking and the automated loom might come get me but I think traditional software products with enthusiastic customers, some kind of ecosystem will benefit with AI being used.

However they will benefit in a way like they benefit from faster server processors: they still have competition and need to fight to stay relevant.

The customers take a lot of the value (which is good).

While there is a lot of fear around AI and it's founded I do love how no one can really dominate it. And it has Google (new new IBM) on it's toes.

Sherlocking won't happen. It requires them to already have the superior customer relationship.

They do need to develop sustainable end-user products, or be purchased by larger players, or liquidate.

That's a really smart observation.

It's hard to add sophisticated abstractions though, because they are all selling text by the pounds (kilos?). So it feels the same as vendor lock for a cucumber seller, doesn't it? The seller can sell you an experience that would lock you in, but aside from it there is no moat since anyone can sell cucumbers.

To try and give examples: an autonomous agent that can integrate with github, read issues, then make pull requests against those issues is a step (or maybe two) above an LLM API (cucumber seller).

It doesn't take much more of a stretch to imagine teams of agents, coordinated by a "programme manager" agent, with "QA agents" working to defined quality metrics, "architect" agents that take initial requirements and break them down into system designs and github issues, and of course the super important "product owner" agent who talks to actual humans and writes initial requirements. Such a "software team system" would be another abstraction level above individual agents like Codex.

I don't know what the future holds, but I know that this pattern is the 'horseless carriage' of developer automation.

When people talk about how sophisticated hierarchical agent swarms will be built up that perfectly reflect existing human social structures I'm reminded distinctly of all the attempts to build DDD frameworks for modeling software, and then the actual result is that software went in the opposite direction - towards flattening.

As native LLM task completion horizons increase another order of magnitude, so much of this falls out of the window.

This exactly. I built CheepCode to do the first part already, so it can accept tasks through Linear etc and submit PRs in GitHub. It already tests its work headlessly (including with Playwright if it’s web code), and I am almost done with the QA agent :-)

You nailed it. I imagine this is why OpenAI is looking to develop hardware. Right now, I have tabs open for ChatGPT, DeepSeek, and Gemini. I have zero loyalty to any of them. But if I owned a piece of hardware, I immediately am locked into that ecosystem.

My bet is on Bezos. The sheer physical infrastructure is the moat.

My second bet is on Google (for general-purpose LLMs in general) - not because of any technical advantage, but because they have a captive audience of large organizations using GSuite that would be happy to just get Gemini on top to satisfy need for AI tools, instead of having to jump through the hoops of finding another provider. Sales, sales, sales.

Do you mean AWS? They're competing with half a dozen or more hyperscalers now. Cloud infrastructure components are so heavily commoditized now, many of them have open source solutions with compatible API's. (Think Minio)