Foundations
LLMs and How to Actually Use Them
- What a language model is, at a working level
- Tokens, context windows and temperature — what they change in practice
- System instructions versus user input
- Prompting that is not folklore: what actually affects output
- Structured output, and why JSON matters more than clever wording
- Grounding: giving the model the facts it needs
Workflows versus Agents
- The difference between a deterministic workflow and an agent
- Anatomy of an agent: model, instructions, tools, loop, stop condition
- When you should not use an agent
- First look at cost and latency