McKinsey's AI leader moved to head a $2B AI workforce - Matthew Fitzpatrick [Invisible]

Is the traditional SaaS model officially dead ? On this episode of BILLIONS, I’m sitting down with Matthew Fitzpatrick, the man Fortune 500 CEOs called when they didn’t know what to do with AI.Matthew walked away from one of the most prestigious roles in tech, leading 1 000 engineers at McKinsey’s QuantumBlack Labs to lead Invisible Technologies.Invisible is the "invisible" engine behind the AI revolution. They don't just build software; they provide the RLHF (Reinforcement Learning from Human Feedback) and the data that trains the models the entire world is building on. With $100M raised at a $2B+ valuation, Matthew is proving that the future isn't in selling tools, but in selling outcomes.In this masterclass, we break down:The McKinsey Exit: Why a top AI leader "jumped ship" for a $2B startup.The Death of SaaS: Why "Outcome-based pricing" is replacing the subscription model.The Enterprise Gap: Why 90% of companies are failing to get AI into production.The Scaling Laws: The truth about data bottlenecks and the future of AI training.Process as Code: How Invisible integrates human intelligence with AI to solve "impossible" problems.TIMELINE : 00:00 The data bottleneck: Why Enterprise AI is currently "stuck"01:01 Why McKinsey’s AI chief left to lead a $2B unicorn02:33 The "Four Platforms": How Invisible actually works05:58 SaaS vs. Outcomes: The pricing model of the future09:19 Why the "AI Bubble" reality check is coming15:12 The "Capability Gap" holding back the Fortune 50022:15 RLHF & Data: Building the workforce behind the major models31:42 "Process is Code": The new architecture for billion-dollar companies41:10 Matthew’s advice for founders: Don't just build a "wrapper"48:20 The future of the "Invisible" empireREFERENCES :Mary MeekerElon Musk Étude MIT SloanÉtude NBER (National Bureau of Economic Research)Article BloombergMcKinsey & Company Quantum Black Invisible Technologies SwissGear Y CombinatorWeCP (We Create Problems)Databricks SnowflakeJevons paradox Reinforcement learning from human feedback (RLHF)Chain-of-thought reasoning Revolut