RAG explained without the jargon: a practical playbook
Most LLMs confidently answer questions using knowledge that stopped updating months or years ago. RAG fixes that, and this playbook shows you exactly how to build it without getting lost in the technical weeds.
Go deeper, free lessons
Retrieval-augmented generation (RAG): giving models your data
Choosing the right approach: prompt, RAG, fine-tune, or agent
Evaluating outputs: how do you know it works?
The AI tools landscape: APIs, no-code, and vector databases
Hallucinations: why confident answers can be wrong
Full transcript…
The skinny
The skinny isn't ready yet — notes appear once the transcript is processed.