Shuhua Xu

Guest Author

Shuhua Xu is a Lead Data Engineer with 13 years of experience across data engineering and data science. He focuses on large-scale enterprise data platforms, distributed systems, LLMs, AI agents and AI-assisted engineering workflows. He has actively integrated LLMs into enterprise engineering workflows and has been involved in building multiple AI agents within his current organization.

Messy data

Enterprise AI agents are only as reliable as the messiest documents behind them

Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individual AI applications. While this approach works well for isolated assistants and copilots, it treats enterprise knowledge as application-specific context rather than a shared enterprise asset.