Andy Warhol famously said:
What’s great about this country is that the richest consumers buy essentially the same things as the poorest. You can be watching TV and see Coca-Cola, and you know that the President drinks Coke, Liz Taylor drinks Coke, and just think, you can drink Coke, too.
There was a time when everyone used Github Copilot. It used to cost $10 per month, or free for students. I used it, Andrej Karpathy used it, high schoolers learning to code used it too.
This world is already partly gone; the cheapest usable tier of Claude Code is $100/mo. In this post, I outline a bunch of short arguments for why the old state of affairs was temporary, and why the best AI tools will become far more expensive.
The top tier subscription prices are increasing exponentially
I made a plot of a bunch of tiered offerings in AI coding tools, showing an exponential trend. There are two issues with this plot: (1) the data is biased towards products I looked up; (2) if you look at the data, this is obviously multiple disjoint trends in the higher and lower pricing regime, and fitting a straight line seems like a bad idea. But I think it is nevertheless clear that there is some sort of exponential trend.
Furthermore, OpenAI reportedly discussed charging $20k/month on PhD-level research agents with investors. This was in March, and I haven’t found anything since; so take this claim with a grain of salt.
There is slack to expand into by just spending more on inference
LLMs are a very unusual disruptive technology, in the sense that they started out cheap. It has been noticed many times that there are many tasks AI agents cannot do; but when they can, they do it much cheaper than people! This was not usually the case with new technologies. Computers used to be huge and pricey. Or, consider self-driving cars: Waymo is more expensive than Uber.
In fact, at least measured by the number of lines of code they are producing, LLM coding agents are producing way more value than they cost.
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