The Engineering Behind Enterprise AI

  • Why RAG Systems Sometimes Answer Questions Nobody Asked

    A Production Lesson Every AI Engineer Eventually Learns   One of the most surprising moments when deploying a Retrieval-Augmented Generation (RAG) system to production is watching users become frustrated by an AI that appears highly intelligent but somehow feels socially unaware.   The user says: Thank You The AI responds: According to the my knowledge…

    Amit Patriwala

  • The Hidden Context Window Problem in RAG Systems: A Real Production Incident with vLLM and Qwen3

    When Your 32K Context LLM Fails at 4K Tokens: A Production vLLM Troubleshooting Guide   One of the most common misconceptions in Generative AI systems is: “The model supports 32K context, so my application automatically supports 32K context.”   In production, that assumption can lead to unexpected failures.   Recently, we encountered a production issue…

    Amit Patriwala