Comment by merelydev

15 hours ago

Open source should not be a threat just like Linux isn't really a threat to Mac and Windows. It all depends on who will get the network effects first (if there even is network effects in LLMs). People pay for windows because of its strong network effects eg Microsoft Office and countless software that run on windows. Even though Linux is free most businesses today don't use it on the desktop.

Opensource also means do it yourself and most businesses don't have time or expertise to do that, but this very issue creates a market for 3rd party providers that use open models to compete against Anthropic. So hardware and compute availability becomes somewhat of a moat.

The business feels like like web hosting before cloud computing. Web hosting in itself does not really have a moat, but than again AWS appeared with their abstractions created lock-in and network effects and disrupted the hosting industry.

Definitionally, from the product they claim to sell, you could just ask Claude to help you migrate to an open source model (if you have the hardware or if you are ok with a subscription) with very little difficulty in the scope of a single conversation. The product they're selling is capable of helping you stop using it. And there's very little friction to use other products too, unlike linux vs mac vs windows, where program compatibility is not as trivial (although with WINE, Rosetta, and WSL, it is actually decently easy nowadays). In this case, you're just calling out to an API with a harness. And even their harness is capable of using open source models.

I feel like it's different from all other cases because it's the first product which can literally obsolete itself, lol. It can show you the door and walk you through it if you ask it to.

The network effect is way weaker for LLM's. Switching from AWS to GCP or Azure is at least a multi-month project for an engineering org, if not completely operationally impossible. Switching LLM providers is at worst asking your engineers to install a new coding agent client, and at best switching a URL and API token in your config file.

If Linux (and BSD) didn't exist, imagine how much money Oracle, Microsoft and Apple wouldn't made on servers

Regarding moats: it's been said by everyone else, but it doesn't seem like Anthropic has a moat. Everyone can easily switch from Claude to Codex, OpenCode, Pi, or any of the other zillions of harnesses. They can even have Claude do the migration for them if they want and it will oblige – that's what I did when I canceled my Claude subscription.

The idea that hardware and compute is their moat is interesting, but open/local models become more capable each week. As I write this, I have 3 instances of some no-name model working on 3 separate worktrees on my M1 Mac Studio. It was viable for me ages ago, and I'm not an AI enthusiast (I just happened to have bought a Mac several years ago that can run these models). I haven't paid Anthropic or OpenAI a cent since the early part of 2026.

  • But if you’re statisfied with just that throughput and model capability that a M1 can provide, than I don’t think you are a well monetizable client anyway? I agree with the no moat as I use a wide variety of models but to only use my M5 128 would definitely not statisfy my needs, so on top of that I pay.

    • I'm satisfied with it for the most part, which isn't to say that local models can't be slow or don't do dumb shit that show their comparative lack of intelligence sometimes. But when I need speed or intelligence, I just press ctrl+p in my harness and spend a buck on OpenRouter.

      It's my belief that we will (or probably have) hit a point where the majority of us receive diminishing returns from the sota models for the work we do. I don't need Astra or Mythos just to write some crud apps or refactor react to svelte, for example.

  • I'm also local-only in my current development process, and have a couple local agents running right now. The problem with local right now is the price has gone through the roof. Even 3-6 months ago I would have said it's viable for a lot of people, but even getting the RAM for a local inference machine is a big investment for a lot of people trying to dip their toes into the space these days.