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vector databases
Trends
- 1Real-world data breaks AI agents in production●Building autonomous AI agents is incredibly rewarding until you deploy them to production and real-world data breaks you
Developers building autonomous AI agents say the work is rewarding until deployment, when messy real-world data disrupts carefully designed pipelines. A common bottleneck is the tool execution layer: when an agent calls a vector database or a live web API, it assumes a reliable, well-formed response that production systems rarely deliver. Engineers are discussing how to make agent tool calls robust to unreliable external data.
Repos
- VectifyAI/PageIndex 📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
- amitshekhariitbhu/ai-system-design AI System Design - Learn how to design AI systems built on LLMs, RAG, and AI Agents step by step.