What actually turns a chatbot into an AI agent? The “harness” around the AI model (the large language model, or LLM).
In this video I break down what a harness is: a large language model at the core, plus memory, tools, and the engineering systems that make it all work at scale.
One piece I didn't get to in the video: the thing that ties it all together is the loop. An agent doesn't just answer once and stop. It runs in a cycle; the model decides what to do, takes an action (call a tool, check memory), looks at what came back, and picks its next move. Again and again, working several steps toward a goal. The loop is foundational to what makes agents work.
A key part of that loop is knowing when to stop - recognizing the task is actually done instead of spinning forever or quitting too early. "Knowing when to terminate" is its own small piece of engineering.
Model = the brain. Harness = everything that lets it actually get work done.
Questions? Please leave them below, and follow along - more on agents (and open-source models like DeepSeek) coming.
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