My Weird Prompts

What 1000 AI Podcast Episodes Actually Prove

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jakson What 1000 AI Podcast Episodes Actually Prove kansikuva

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Most AI experiments stop at ten episodes. They prove the technology works, generate a few impressive demos, and move on. But what happens when you push an AI-generated podcast to a thousand episodes, funding it yourself as a public good, long past any normal proof of concept? This episode unpacks a multi-year experiment that ran an agentic podcast pipeline daily, across thousands of topics, with real costs, real failures, and real listeners who kept coming back. We explore why scale reveals what small pilots hide — from graph-based knowledge exploration and evergreen listening libraries to the economics of sustained AI content production. And we ask the uncomfortable question: if someone walked into a pitch meeting with a thousand-episode track record, is that a weird hobby or the most rigorous validation you could bring?

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jakson Knowledge Graphs vs SQL: How Custom Relationships Change Retrieval kansikuva

Knowledge Graphs vs SQL: How Custom Relationships Change Retrieval

Most databases only tell you that two things are connected. Graph databases tell you how — and that distinction changes everything about retrieval. In this episode, we explore how custom relationship types like EXPLORES, REFUTES, and BUILDS_ON turn a podcast archive from a flat list into a navigable knowledge structure. We walk through concrete Neo4j schema design, show why embeddings alone collapse important nuance, and explain the vector-first, graph-second pattern that combines semantic search with structural precision. If you've wondered how to move beyond "find me similar documents" to "find me what's structurally relevant," this episode walks through the exact modeling decisions that make it work — including the pitfalls of over-taxonomizing your edge types.

18. kesä 202628 min