AI Startup Founder

Found an AI-native startup and run it month by month: build the product, set your pricing and model tier, spend on growth, and hire — and learn burn, runway, and SaaS unit economics by living them.

Learn how an AI-native software startup really works — burn and runway, subscription unit economics, why every free user costs inference money, and growth vs. default-alive — by founding one and living the consequences.

Burn rate & runway
SaaS unit economics (MRR, churn, CAC/LTV)
Inference cost as COGS
Growth vs. profitability
Fundraising & dilution

Month 1 of 24~18 min

1.5M ₴

—

This month's board meeting

New features34%Reliability33%Model quality33%

Higher price = more revenue per user, but lower conversion and higher churnBuys visitors, with diminishing returnsYou have 2 now · each costs 90,000 ₴/mo

Grows the funnel, but free users still burn inference

Optional. You currently own 100%. Raising extends runway but sells part of the company.

Before you advance

Projected signups

290

Projected MRR

0 ₴

227k ₴

Runway

6.6 mo

294 ₴

—

Inference on all your active users outweighs revenue — your free tier is bleeding money. Convert more, price higher, or drop to a cheaper tier.

Save a plan to reuse it and fast-forward months.