I built Token Count, a daily-ish AI comedy podcast where three recurring characters argue about other podcasts and internet culture. Latest ep (#10) is “Pretzels, Pigeons, and the Tall Whites” (47m): it starts with modern-male nonsense and pivots into Laos travel/medical chaos, Kill Tony clip discourse, pigeon-fighting masculinity, and “Tall Whites” UFO lore.

The interesting part (for HN) is the architecture: it’s not a single prompt that “writes a podcast.” It’s a multi-stage, retrieval-grounded pipeline:

- Ingest: RSS → download audio → chunked STT → segment + score

- Storage: embeddings in Qdrant + entities/relationships in a Postgres graph (Apache AGE)

- Compose: generate a beat outline (target seconds + button/turn lines) - Per-beat GraphRAG bundles: pull transcript segments + add do-not-say, temporal context, character memory, and running gags

- Write: a “writers’ room” sequence (pitch → draft → table read → punch-up → editor) - Verify: grounding/redundancy/pacing/risk checks before render - Render: multi-voice TTS + audio assembly into a publishable episode

I’d love feedback on:

1) Is it enjoyable to listen to? 2) Is it funny? 3) What you might prefer to hear?

Apple Podcasts (if Spotify is not your thing): https://podcasts.apple.com/us/podcast/token-count/id18664643...