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Databricks Context Engineer Associate Study Guide

Databricks Certified Context Engineer Associate

The Databricks Certified Context Engineer Associate exam is for engineers who design, assemble and govern the information AI agents receive at inference time on Databricks. It covers context failure modes, system prompts and few-shot design, retrieval with Databricks AI Search and Genie, memory with Lakebase and MLflow, MCP tools, compaction, and context for multi-agent and long-horizon tasks.

  • Databricks certification
  • Associate level
  • 7 exam sections

This guide is free, with no sign-up. It explains every Databricks Context Engineer Associate exam topic in plain English, one chapter at a time. Read them in order or jump straight to the topic you need.

  • 7chapters
  • 18topics
  • 5diagrams and exhibits
  • 1 h 35 minfast track
Start with Foundations of Context Engineering
  • Every topic follows the same simple pattern: what it is, how it works, common mistakes
  • Diagrams and real command output where a picture explains it best
  • Exam tips and worked subnetting and IPv6 practice, with answers

How the exam is weighted

Each domain is worth this share of the exam, so spend your study time in proportion. Select a domain to open its chapter.

Chapters

Open a chapter to see its topics and how long each takes.

1Foundations of Context Engineering3 topics · 15 min fast trackFailure modes, attention budget, long context decay, reasoning modes and the Databricks agent stack.
  1. 1Context Failure Modes and Their Fixes5 min
  2. 2Attention Budget and Long Context Degradation5 min
  3. 3Reasoning Modes and the Databricks Product Stack5 min
Read the chapter overview →
2System Prompt and Instruction Design2 topics · 10 min fast trackGenie space instructions and trusted SQL, few-shot example choice, prompt fixes and token tradeoffs.
  1. 1Building a Production Ready Genie Space5 min
  2. 2Few-Shot Examples and System Prompt Tuning5 min
Read the chapter overview →
3Knowledge Retrieval and Genie Configuration4 topics · 21 min fast trackTask context, RAG with AI Search, chunking, Genie curation and Unity Catalog governance.
  1. 1Task Context Elements and Retrieval Timing5 min
  2. 2RAG Pipelines, Chunking and AI Search Configuration6 min
  3. 3Unity Catalog Metadata and Genie Space Curation5 min
  4. 4Retrieval Failure Modes and Authoritative Source Governance5 min
Read the chapter overview →
4Memory Architecture with Lakebase and MLflow3 topics · 16 min fast trackSession vs long-term memory, Lakebase state, memory retrieval, intent and MLflow 3 comparison.
  1. 1Memory Types and Persistent Memory with Lakebase6 min
  2. 2Retrieving Memories from Lakebase5 min
  3. 3Intent Resolution and Comparing Configurations in MLflow 35 min
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5Tool Design, MCP, and Agent Context2 topics · 11 min fast trackProgressive disclosure for MCP tools, Agent Skills, tool choice, clear descriptions, output clearing.
  1. 1Progressive Disclosure for MCP Tools and Agent Skills6 min
  2. 2Tool Selection, Descriptions and Clearing Tool Outputs5 min
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6Context Compression and Compaction2 topics · 11 min fast trackWhat compaction keeps or drops, prompt tuning, trimming and trade-offs.
  1. 1What Compaction Must Keep and What It Can Drop6 min
  2. 2Tuning Compaction, Trimming and the Cost Trade-Off5 min
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7Multi-Agent and Long-Horizon Task Design2 topics · 11 min fast trackShared context, dispatch, sub-agent outputs, boundaries and long-horizon plans.
  1. 1Shared Context and Dispatch in Multi-Agent Systems6 min
  2. 2Sub-Agent Outputs, Agent Boundaries and Long-Horizon Strategies5 min
Read the chapter overview →

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The full Databricks Context Engineer Associate question bank has 600 questions, with timed practice exams and an explanation for every answer.

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