Build LLM apps that leaders can trust without heavy CI/CD. In this hands‑on workshop, you’ll implement grounded retrieval on Azure Databricks, combine keyword and vector search and enforce “cite‑or‑fail” so every answer shows sources or refuses safely. Add safety filters (PII/toxicity), light policy‑as‑code tests, and runtime evaluation to catch regressions before users do. We’ll instrument telemetry & traces that link prompt --> data --> answer for auditing and debugging, then discuss simple rollout patterns (shadow/canary) and cost/performance tuning. You’ll leave with a working notebook repo, datasets, and a practical checklist to move from prototype to reliable production on Databricks.