A data readiness checklist for AI agents covering lineage, freshness, access control, PII, schema stability and evaluation data.
Data & AI Engineering
Context Engineering for Enterprise AI Agents: Beyond Prompt Engineering
Context engineering for AI agents goes past prompts: retrieval design, chunking, memory, tool context and how each one fails.
RAG Guardrails: Stopping Agents That Leak or Hallucinate in Production
RAG guardrails that stop agents leaking or hallucinating in production, mapped to the specific risk each control removes.
Bronze to Gold in Practice: Making Fragmented Enterprise Data AI-Ready
A practical walkthrough to make fragmented enterprise data AI ready, from raw sources to a gold layer an agent can safely query.
End-to-End Data Engineering Is Broken: Here’s How Databricks, the Medallion Architecture, and AI Agents Fix It
AI cannot rescue a broken data foundation. End-to-end data engineering — source ingestion, Bronze/Silver/Gold, certified BI, and governed AI agents — is the discipline that turns raw enterprise data into intelligence executives actually trust. The future state isn’t data plumbing. It’s intelligence engineering.