Module 1 · LLM foundations

Every agent in this lab starts on top of a single building block: a large language model that turns text into text. By the end of this module you will know what an LLM actually does, why a chat app like claude.ai is an agent built on top of one, how the system prompt shapes its behavior, why long conversations cost more, and how temperature trades determinism for variety.

1What is an LLM?An LLM — large language model — is the software behind tools like ChatGPT and Claude. You give it text, it gives you text back. It got good at this by… 6 min

2LLM vs. agent: what you're actually buildingWhen you use claude.ai or Claude Code, you're using an agent — software that wraps a raw LLM with a conversation loop, memory, tools, and a system prompt.… 7 min

3Prompts and system rolesA conversation is a list of messages, each tagged with a role: system (the rules), user (what the person types), and assistant (what the model said… 7 min

4Tokens, context, and why chats cost more over timeLLMs are stateless — they remember nothing between calls. To keep a conversation going, the agent re-sends the entire history every turn. History is… 7 min

5Temperature and samplingTemperature is the randomness dial. Low temperature makes the model pick the most likely next token almost every time (consistent, predictable); high… 5 min

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