How large language models work, from tokens and context windows to prompting, hallucinations, and the case for building systems around models.
5 posts
Customer support is a useful capstone example because one message can require retrieval, tool use, memory, routing, and approval boundaries at the same time.
A useful AI system is defined less by whether it is called an assistant or an agent than by how much control it has over the next step.
Large language models produce fluent, confident text. That confidence is the problem. A model can sound authoritative about a property listing that no longer exists, a tax rate that changed last quarter, or a school rating from three years ago. It has no mechanism to check. It was not designed to...
In the previous post, we sent a single line to an LLM — "Plan a trip to Helsinki" — and got back an itinerary full of specific-sounding details: restaurant names, transit directions, day-trip logistics. It was fluent and plausible, but several of those details turned out to be wrong. The model wa...
You type a sentence into an AI application. Seconds later, it returns several paragraphs of fluent, well-organized text that reads like it was written by a knowledgeable human. That experience is now routine. What is not routine — and what matters if you plan to build anything on top of these sys...