Building an LLM-Based Agent: Step 0

Newcomers to the LLM world often start by "chatting for fun," but very quickly they run into a bigger question about how to make it not only answer, but actually do work. From that moment, they begin to touch on the idea of an agent, meaning a system that can accept a goal, break down tasks, use tools, and self-check results to get real work done. This first post serves as the foundation for the entire series. We will not go far yet and focus on one concrete thing: building a minimal yet correct chat framework that we can later upgrade into an agent without rewriting everything from scratch. Once this framework is stable, we will see that two factors determine quality from the very beginning, namely how we package context using messages and how we write prompts in a clear and disciplined way.