Definition
RAG (Retrieval-Augmented Generation)
A technique where a model first looks up relevant information from documents or databases, then uses it to write a more accurate, up-to-date answer.
How founders on the podcast use it
Retrieval augmented generation, giving a model external notes instead of true built-in memory.
40,000 Models, One API Key, and a $25M Bet on Open SourceA technique where an LLM retrieves relevant chunks of text before generating a response, typically using vector similarity search. Effective for single-document lookup; prone to missing cross-document relational context.
Legal AI: Why Lawyers Are Finally Free to ThinkA method of giving an LLM access to external documents by converting them into vectors and retrieving relevant chunks before generating a response. The foundation of enterprise AI search.
Enterprise AI for $20 a MonthPointing a model at your own documents so its answers are grounded in your data rather than its training.
Tokens Go to Zero, Energy Goes to Zero: What Do You Build When Intelligence Is Free?Hear it on the podcast4 episodes
Learn the language of AI-native founders
Every week: the new terms, tools, and workflows founders are using, straight from the podcast.