[aftbit]

The marginal cost of AI is not 0. That's one of the big differences between this and older SaaS software. Inference costs a lot of money. Even if you're looking at just capital depreciation, it's quite expensive. I suppose it's more accurate to say marginal cost is stepwise - adding 1 new user is 0 cost if and only if your existing inference hardware covers that user's usage. As soon as you need a new server, adding _that_ new user costs ~$20k/year (assuming 100k server and 5 year depreciation).

This is true for traditional SaaS too, but the number of concurrent users that could be served by one machine and the cost of the hardware were both at least an order of magnitude better.

[treis]

It's not literally 0 but for most casual users it is. Programmers are heavier users and the ones that have 10 agents going wild are even more so. In that case the cost is above 0 but economies of scale means the effect is the same.

[aftbit]

The marginal cost for _users_ (on a token plan) is $0 but not for the AI company supplying that token plan.

[jqpabc123]

The marginal cost of AI is not 0.

In other words, AI is not your daddy's software. Comparing AI with old school software markets simply does not compute.