# GenCache

- **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:** [Harsh Manoj Jain](https://cerebralvalley.ai/u/harshmjain), [Tejasva Jaitly](https://cerebralvalley.ai/u/neiljaitly)
- **GitHub:** https://github.com/tejasvajaitly/shack15
- **Demo video:** https://youtu.be/USR2mn8HSHo
- **Gallery:** https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery/71

We've built a seeded RAG system that uses a lightweight knowledge cache to minimize redundant retriever calls. The LLM first tries to answer a query using cached context from previous questions; if it determines that the information is insufficient, it triggers the retriever to fetch new data and updates the cache. This approach allows semantically related or follow-up questions to be answered instantly from the existing cache, reducing latency, cost, and retrieval frequency while keeping responses contextually consistent across a conversation.

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Markdown version of https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery/71. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt