Most conversations about AI memory jump straight to reconciliation—handling conflicts when the system learns you moved but still has your old address. But none of that matters without the pipes to get data in and out cleanly. This episode breaks down a practical two-flow architecture: prompt-context separation for persistent personal memory across AI interactions, and voice-note capture with smart namespacing. We explore why atomic context facts beat monolithic blobs for vector search precision, how to structure retrieval queries around the user not the topic, and why source-type namespacing is less useful than topic-based classification. Plus, a concrete walkthrough of the production pipeline using webhooks, n8n, and output schema constraints.
Episode #761296 — open it directly at myweirdprompts.com/761296