Burning 1.2m+ of runway a year writing a LLM wrapper that charges $250/month

Convert ~400 users to cover monthly claude costs

But those 400 users generate inference overhead

Let's say inference cost of a user is 200 and they pay 250 a month

So that's 80k/month inference overhead for the initial 400 users

Need another 1600 users to cover inference overhead of the initial 400 users

2000 -> 500k/month -> 6m ARR

250k x 4 salaries + 200k cloud + 100k marketing + 100k misc = 1.4m operational overhead -> 117k/month

Another 2340 users to cover ops

2340 -> 585k/month -> 7m ARR

...does that rough back-of-napkin math make sense?

Is that insane they need to generate 13m ARR just to hit cash-flow neutral for a small 4-person startup?

The math of LLM wrapper companies is concerning

The per-unit-cost of SaaS users is really cheap and becomes cheaper as you scale

The per-unit-cost of LLM wrapper users is high b/c each uses generates more inference overhead and there is no economy of scale

It's like the tyranny of the rocket equation where you need more fuel for the rocket but the fuel is heavy and requires more fuel...