Production Patterns: 10 Databricks GenAI Engineer Decisions | Databricks GenAI Engineer Cert

Learn the ten production decisions that separate working GenAI systems from prototypes on Databricks. This deep-dive covers the Agent Rule of Two, Vector Search endpoint selection, MLflow scorers vs judges, MCP management, Unity Catalog registration patterns, AI Gateway vs Model Serving governance, RAG eval triad diagnostics, hallucination vs prompt-injection defenses, lineage instrumentation, and decision qualifier words that map directly to exam questions. What You'll Learn Master the engineering patterns that senior Databricks architects apply in production—and the same patterns the certification exam tests. Walk through ten real production scenarios, understand why common approaches fail, and learn the decision rules that prevent cost overruns, SLA breaches, and audit failures. Key Topics • Agent Rule of Two: threat boundary and when to drop a capability leg • Vector Search endpoint types: storage-optimized vs standard cost-latency tradeoffs • MLflow scorers, judges, and metrics: the hierarchy and where to use each • MCP managed vs external vs custom: implementation effort and governance coupling • PyFunc vs ChatModel vs ResponsesAgent: registration signatures and what each unlocks • AI Gateway vs Model Serving: governance planes in the request path • RAG eval triad: retrieval relevance, groundedness, and answer correctness diagnostics • Hallucination vs prompt injection: two threat models, two defense directions • Unity Catalog lineage: automatic capture vs manual instrumentation • Qualifier words: how "least overhead," "lowest latency," and "governance-first" map to engineering decisions CHAPTERS 0:00 Introduction 0:42 What Goes Wrong Without These Patterns 2:23 The Ten Decisions Overview 3:39 Decision 1: Agent Rule of Two Boundary 5:42 Decision 2: Vector Search Endpoint Selection 7:50 Decision 3: Scorers vs Judges vs Metrics 9:33 Decision 4: MCP Managed vs External 12:14 Decision 5: PyFunc vs ChatModel Registration 14:13 Decision 6: AI Gateway vs Model Serving 15:45 Decision 7: RAG Eval Triad Diagnostics 17:26 Decision 8: Hallucination vs Prompt Injection 19:12 Decision 9: Unity Catalog Lineage 21:10 Decision 10: Qualifier Words and Tradeoffs 23:04 How Decisions Couple in Practice 24:00 Key Takeaways RESOURCES 🔗 Databricks GenAI Engineer Exam: https://www.databricks.com/learn/cert... 📋 Full Playlist: https://www.youtube.com/@StackLessons... ABOUT StackLessons creates hands-on exam prep content for cloud & AI certifications. Like & Subscribe for more content! PRACTICE QUESTIONS Need more practice questions? Visit https://certcompanion.com/exams #Databricks #GenAI #ProductionPatterns 📌 Chapters 0:00 Introduction 0:42 What Goes Wrong Without These Patterns 2:23 The Ten Decisions Overview 3:39 Decision 1: Agent Rule of Two Boundary 5:42 Decision 2: Vector Search Endpoint Selection 7:50 Decision 3: Scorers vs Judges vs Metrics 9:33 Decision 4: MCP Managed vs External 12:14 Decision 5: PyFunc vs ChatModel Registration 14:13 Decision 6: AI Gateway vs Model Serving 15:45 Decision 7: RAG Eval Triad Diagnostics 17:26 Decision 8: Hallucination vs Prompt Injection 19:12 Decision 9: Unity Catalog Lineage 21:10 Decision 10: Qualifier Words and Tradeoffs 23:04 How Decisions Couple in Practice 24:00 Key Takeaways #Databricks #GenAI #ProductionPatterns