Micheal Lanham is a best-selling author, innovator, and AI engineer based in Calgary, Canada. His career spans an unusual breadth of domains: games, graphics, GIS, enterprise software, and machine learning. He has worked as a lead AI developer, architect, and manager across industries ranging from oil and gas to fintech, and that variety has given him a rare perspective on how AI techniques transfer between fields.

Micheal is a prolific technical author with more than ten books to his name, including Evolutionary Deep Learning, Hands-On Reinforcement Learning for Games, and AI Agents in Action. His writing connects research ideas to working code, making topics like evolutionary computation, deep reinforcement learning, and generative AI accessible to practicing engineers and game developers alike.

Over two decades, Micheal has watched the ideas born in game AI, multi-agent systems, and evolutionary algorithms evolve into the LLM-driven agents of today, and he draws on that history in his work and talks on modern AI tooling and agent design. Today he focuses on building intelligent systems that combine deep reinforcement learning, evolutionary methods, and generative AI, helping teams understand both where these techniques came from and where they are going next.