Monetization
Turn your AI engineering skills into a sustainable business.
Building AI products is one thing. Building AI products that are financially sustainable is another. The mistake most AI founders make is underestimating token costs — pricing their product before calculating what a power user actually costs them in API calls. I've done the math so you don't have to.
A user on a $20/month plan who sends 50 messages a day can easily generate $27 in OpenAI API costs using GPT-4o — meaning you lose $7 per customer. This track explains the five pricing architectures (message limits, credit systems, BYOK, per-seat, outcome-based) and the cost optimization techniques (model routing, prompt caching, output compression) that make AI SaaS viable.
I also cover the full technical side: integrating Stripe for recurring billing with usage-based overages, building a credit ledger in your database, and tracking per-user token spend in real time. By the end of this track, you'll have the business model clarity and the technical implementation to launch an AI product that doesn't lose you money at scale.
📚 Learning Path
- Understanding token costs and margins
- The 5 AI SaaS pricing architectures
- Credit systems and quota enforcement
- Stripe integration for recurring + usage billing
- Real-time cost tracking per user