01 / REVIEW
Agent architecture reviews
Understand where your agent system holds up, where it breaks, and what to improve next.
A written report with prioritized findings and next steps.
Explore architecture reviewsMicheal Lanham · Author & AI practitioner
Systems that
learn, adapt,
and improve.
I write books and build software around AI agents and evolutionary learning. I help teams design better agent systems through architecture reviews and hands-on training.
Learn by doing: play The Proof GateGather context
Bring together the task, relevant knowledge, and feedback from the environment.
Select a step to explore.
- Published books
- 12
- Years in software
- 20+
- Books in development
- 3
Published with Manning, O’Reilly, Apress, Packt, and BPB.
Work with me
Move your agent system forward.
A second set of eyes on your architecture. Practical training for the people building it.
02 / LEARN
AI agent training workshops
Help your team build, evaluate, and reason about agent systems through practical work.
A curriculum tailored to your team, delivered remotely or on-site.
Explore team workshopsSelected books
Ideas you can build on.
Start with practical agent systems, explore evolutionary learning, or follow the work on agents that improve themselves.
Manning · Early access
Self-Improving Agents
Developers exploring how to measure, guide, and evaluate improvements to an agent system.
Explore this book
Manning · 2026
AI Agents in Action, Second Edition
Python developers ready to build agents with tools, memory, evaluation, and multi-agent workflows.
Explore this book
Manning · 2023
Evolutionary Deep Learning
Developers exploring how genetic algorithms can search, tune, and evolve neural networks.
Explore this bookLearn by doing
Put an idea to the test.
About 5 minutes · No account needed
The Proof Gate
Decide when a self-improving machine has earned the right to change. Explore proof, evidence, and the judgment behind shipping an improvement.
About Micheal
A career spent making ideas work.
I’m Micheal Lanham, a software practitioner and author based in Calgary, Canada. Over more than 20 years, I’ve worked across games, graphics, geoscience, and machine learning.
I began using neural networks and evolutionary algorithms in game development around 2000. That work still shapes what I write and build: systems that learn from experience, and practical ways to understand whether they are improving.
Today my focus is AI agents, evolutionary learning, and the tools that help teams put those ideas into practice.
Let’s talk
What are you working on?
Tell me about your agent system, your team’s learning goals, or a question about the books.