Hey guys! I just sat down with @Patrick Chouinard for one of the coolest deep dives we've done in the community. Patrick has become our community's go-to AI expert and one of the most helpful resources we have. He's quietly been building something most teams pay a vendor $50k a year for. He's turning every community call we've ever recorded (two and a half years of two to three hour conversations) into a queryable "community brain." You'll soon be able to ask it anything that's been discussed and get a real answer with citations. Here's the part that broke my brain. Standard RAG completely falls apart on transcripts. The question gets asked at minute 6, the conversation drifts, and the real answer shows up at minute 41. A normal chunker has no idea those two moments belong to the same idea. Patrick solved it by adding an LLM analysis layer BEFORE chunking that restructures the transcript into self-contained units of knowledge. You can watch the full breakdown above! Here's everything we covered: ✅ Why traditional chunk-and-embed fails on non-linear data ✅ The LLM analysis layer that turns raw transcripts into RAG-ready knowledge ✅ How Patrick picks the cheapest model that's still smart enough for each step (Kimi K2.5 for restructuring, Sonnet 4.6 for the signal extraction) ✅ Why he chose LanceDB over Pinecone (and when you'd flip that decision) ✅ Running the whole thing locally with Ollama, Open Web UI, Gemma 4 4B, and gpt-oss:20B for more complex retrieval ✅ Using Claude Code to build a custom chunker instead of fighting with a library ✅ Real cost math. About 40 cents per two hour episode and under $100 to process the entire archive The wildest part is the price. Once the embeddings are built, querying is free forever because everything runs on your own machine. No SaaS, no per-token cost, no IT review. Patrick is also planning to open source the full pipeline once a few rough edges are ironed out. So if you've been wanting to build something like this for your own team, agency, or client, you'll have a working blueprint to start from.