Talking to AI
Before we build anything, you need to understand the technology. This module covers how large language models work, how to communicate with them effectively, and the different ways they can support business work.
What you'll be able to do
By the end of this module you'll understand what an LLM actually is and why it behaves the way it does, how to write prompts that produce useful output, and how to choose between using AI as a builder versus using it as a thinker inside a workflow.
How this module is structured
Five sub-pages, in order:
1. What is an LLM?
A working definition of large language models, their emergent capabilities, and two ways they support business work.
2. Prompting as context design
How to write prompts that work — structure, context, and the patterns that turn vague requests into useful outputs.
3. From prompt to output
The spectrum from single-turn chat to autonomous agents, and how to choose the right mode for a given task.
4. Use case: Customer Segmentation
End-to-end: turn a flat 800-row customer CSV into three actionable segments overnight using an LLM.
Why this comes first
Everything else in the course assumes you understand what you are working with. A clear mental model of how LLMs generate output — and where that process can go wrong — is the foundation for using them effectively in later modules.