Module 2 of 6Lesson 3 of 3~12 min
Understand the anatomy of an LLM assistant
Behind a simple chat window sit several building blocks, and each one carries product decisions a PM needs to understand. This lesson helps you explain to your team what happens when a user sends a message to an LLM assistant, and identify where quality, cost and risk are decided.
Lesson objective
By the end of this lesson, you will be able to explain to a team what happens on every message (application, system prompt, history, context, tools, model) and to locate where each product decision is made.
Topics covered
- how LLMs work
- AI assistant
- system prompt
- context window
- assistant architecture
Where it fits
Frame the assistant
Does my product need an assistant, and to do what exactly?
Lessons in this module
- Identify a use case worth an assistant
- Write the framing brief
- Understand the anatomy of an LLM assistant (this lesson)
What you will learn in this module
This lesson is part of the course Build an AI assistant for your product
- Identify a use case that justifies an AI assistant and write its framing brief (problem, users, allowed actions, out of scope, success criteria).
- Choose and justify a knowledge strategy (instructions, injected context, RAG, fine-tuning) and a conversation memory strategy.
Related courses
- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
Design a RAG architecture that fits your product
3 hr 30 min
- AI & ProductAdvancedRegular practice: you already use the tools or work on this topic.
Evaluate an AI feature: test sets, metrics and LLM judges
3 hr
- AI & ProductExpertAdvanced level: for deeper mastery and specialization.
Ship and monitor an AI feature in production
3 hr