Kai Renner 
Learn the core design patterns for building multi-agent orchestration systems. Step-by-step guide covering supervisor, pipeline, and swarm architectures with real examples.
If you’ve ever built an AI agent that suddenly returns “I’m not sure” where your code expected a numeric price, or watched a production pipeline crash because a language model decided to invent a field name on a whim — you already understand why structured output enforcement is one of the most important skills in … Read more
You’ve built your first AI agent. It works beautifully in development. Then you deploy it to production — and the invoice arrives. Welcome to one of the most important engineering challenges in modern AI development: keeping inference costs under control without sacrificing performance. Whether you’re running a customer support agent handling thousands of conversations daily … Read more
Every skilled human conversation partner does something remarkable: they remember what was said five minutes ago, an hour ago, and sometimes years ago — and they know which memories actually matter right now. Building AI agents that can do the same is one of the most practical and rewarding challenges in agent engineering today. If … Read more
You built an AI agent. It works great on your laptop. You deploy it to production — and three days later, a user reports it gave completely wrong advice. You check the logs. There are no logs. You have no idea what happened. This scenario plays out constantly in AI engineering teams that ship first … Read more
Learn how to build production-grade AI agents with robust tool calling, error handling, and fallback strategies. Step-by-step guide with Python examples for beginners and advanced engineers.