Module 4 of 6Lesson 2 of 3~14 min
Choose how the assistant gets its knowledge
Not all the information your assistant needs is obtained the same way, and picking the wrong lever is costly. This lesson teaches you to choose, for each information need, between instructions, injected context, RAG and fine-tuning, then defend that choice with your engineering team.
Lesson objective
By the end of this lesson, you will be able to choose and justify, for a given information need, between static instructions, context injected by the application, RAG and fine-tuning.
Topics covered
- RAG vs fine-tuning
- knowledge base
- AI assistant
- injected context
- AI strategy
Where it fits
Give it the right knowledge
How does the assistant get the right information at the right time?
Lessons in this module
- Manage context and conversation memory
- Choose how the assistant gets its knowledge (this lesson)
- Specify a RAG system with your team
What you will learn in this module
This lesson is part of the course Build an AI assistant for your product
- 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