🤖 Agentic apps need databases that adapt — not rigid schemas that break when your LLM decides to add a field. RAG pipelines need #VectorSearch that doesn't force you into a separate data silo. Developers need tools that actually understand their #AI workflows. Amazon DocumentDB is evolving for this new era. Join this stream as we cover: ✅ Flexible schema for agentic behavior — MongoDB-compatible API lets your AI agents store dynamic, evolving data structures without predefined schemas ✅ Native vector search for RAG — Store & query vectors directly in DocumentDB. No sync pipelines. No consistency drift ✅ DocumentDB 8.0 reduces index build time by up to 30x — parallel HNSW indexing means you can rebuild indexes frequently, keeping your AI answers fresh ✅ DocumentDB MCP server — Give Kiro, Claude, Cursor & other AI tools direct access to your database through Model Context Protocol \ ✅ AWS plugin integration — Estimate costs, configure instances & get database settings right fro...