Building AI Agents: The Fundamentals

Everyone's building agents. Most are building them wrong. Not because they lack skill, but because they lack the right mental models. Before you write a line of code, you need to understand what agents actually are and how they differ from everything else you've built. Here are twelve rules that will save you from the mistakes we made. 1. Understand the Loop An agent is not a chatbot with tools. It's not RAG with extra steps. It's a system that perceives, reasons, and acts in a loop until a goal is achieved. Flow Outcome Chatbot Question > Response Single answer RAG Question > Retrieve > Response Answer with context Agent Goal > Reason > Act > Observe > Repeat Task accomplished The difference is autonomy. A chatbot answers. An agent accomplishes. Years ago, our first "agent" was basically a chatbot with a for-loop. It would answer, we'd manually feed the answer back in, repeat. It took us three weeks to realize we'd reinvented the agentic loop badly. This loop has a name: the agentic l