MongoDB plans an AMA on production RAG and AI agents

MongoDB is preparing a Reddit AMA with Max Marcon, Director of Product at MongoDB, Mikiko Bazeley, Staff Developer Advocate, and Yang Li, Senior SA. The session will cover , RAG, agents, and how to build AI apps that work in real production use. A MongoDB employee is collecting practical questions from people who build RAG systems.

The suggested questions focus on where information should live: retrieval, prompts, tool calls, or memory. They also ask how teams can tell whether retrieved information is actually improving answers. Other topics include keeping information fresh, handling , filtering by metadata, and deciding when a general database plus is enough versus when a more specialized system is needed.

Another key question is what tends to fail first when agents use RAG as a tool and move from a prototype to production.

Key points

  • MongoDB is preparing a Reddit AMA about RAG, agents, and production AI apps.
  • The session includes MongoDB product, developer advocacy, and solutions leaders.
  • The collected questions ask what belongs in retrieval, prompts, tool calls, and memory.
  • The discussion may cover how to check whether retrieved information actually helps.
  • Production issues include freshness, , , and whether is enough.
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