# Hypernym

- **Event:** [Agentic Memory & Context Engineering Hackathon](https://cerebralvalley.ai/e/mongoDB-hackathon)
- **When:** Sat, Oct 11 at 9:00 AM – 10:00 PM (PDT)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Nick Lulofs](https://cerebralvalley.ai/u/hype), [Chris Forrester](https://cerebralvalley.ai/u/elationate)
- **GitHub:** https://github.com/HypernymAI/HyperMongoVoyage/
- **Gallery:** https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery/2

A chat-first “vibe” recommender for movies that uses two agents to converge on intent: BEST (Llama) argues for the most on-vibe pick; WORST (Claude) argues for the intentionally off-vibe counterexample. Users can fork either agent into threads—BEST accumulates include-tags, WORST accumulates exclude-tags—so intent sharpens fast.
Under the hood, we assemble a candidate set from MongoDB (sample_mflix), pass the same candidates to both models via ch.at (OpenAI-compatible), and return strict-JSON “receipts” (strong/weak details + tags_hit/tags_miss). It’s a general pattern for ambiguous preference search and showcases how evidence selection differs across models on the same corpus.

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Markdown version of https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery/2. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt