Hey there,
Traditional Product Market Fit frameworks are killing AI products. After working with 30 AI teams, I've seen the same pattern: teams using "build-test-sell" approaches struggle while those embracing continuous discovery thrive. The difference? Understanding that AI products grow through functional discovery you never programmed. GitHub Copilot's biggest value wasn't planned. Hugging Face evolved from chatbots to the largest AI library. Harvey AI converted 4,000 sceptical lawyers in one week. This isn't luck; it's the natural evolution of AI product management when you apply the right discovery system.
☝🏼Download this Visual Notes to get the complete breakdown of the Iron Triangle framework, my four-step discovery system (Power-Problem Match, Learning & Adapting, Teaching the Market, Growing While Staying Strong), the 4 critical guardrails that prevent epic fails, and the biggest mistakes destroying 80% of AI products. These aren't theoretical concepts; they're the exact playbook I use with real AI Product teams to navigate chaos and ship products that actually work. Whether you're a team of 2 or 200, if you're building AI products, this changes everything.
Let’s Build What Matters!
Ravi Bheesetty
