In this episode, we sit down with former DeepMind researcher and founder Kylan Gibbs to unpack the brutal lessons behind building half a billion-dollar consumer AI company in just four years. After leaving one of the world’s most elite AI research labs, Kylan chose to bet on product, scale and real consumers.
He explains:
•Why he left DeepMind to build a consumer-first AI company
•The biggest mistake AI founders make when designing products.
•Why complex structures and overengineering kill scalability
•The real bottlenecks in consumer AI: cost, speed, and reliability.
•Why most AI products are impressive demos, not real businesses.
•How building under real-world constraints shaped Inworld’s success.
•What founders must prioritise if they want to build enduring AI companies.This episode is a must-watch for AI founders, builders, investors, and anyone serious about turning cutting-edge technology into real, scalable products.