AI-201 study guide · 2026

The 6 AI-201 domains, explained

6 domains and 26 official objectives. AI Agents carries the most weight at 35%. Each guide explains what the domain covers, how its questions are framed and where candidates lose marks.

Questions
60 scored multiple-choice (plus up to 5 unscored)
Time
105 minutes
Passing score
72%
Outline
Salesforce Certified Agentforce Specialist Exam Guide (AI-201), six sections, aligned to the Spring '26 release (current as of October 2026)

Exam blueprint

Bar widths follow the official weights. Weight ranges are drawn at their midpoint.

  1. 1 20% Domain 1: Prompt Engineering, 20%
  2. 2 20% Domain 2: Data 360 Fundamentals, 20%
  3. 3 35% Domain 3: AI Agents, 35%
  4. 4 10% Domain 4: Testing, Deployment, and Maintenance, 10%
  5. 5 10% Domain 5: Governance and Observability, 10%
  6. 6 5% Domain 6: Multi-Agent Orchestration, 5%
  1. 1 Prompt Engineering
  2. 2 Data 360 Fundamentals
  3. 3 AI Agents
  4. 4 Testing, Deployment, and Maintenance
  5. 5 Governance and Observability
  6. 6 Multi-Agent Orchestration

All 6 domains

26 official objectives 63–75 hrs suggested study

  1. Domain 01 20%

    Prompt Engineering

    Prompt Engineering covers Prompt Builder from first use case to live template: choosing template types, granting access, grounding with Salesforce and Data 360 data, writing clear instructions, and the Einstein Trust Layer controls that protect every request.

    Inside this domain

    • Given business requirements, identify when it's appropriate to use Prompt Builder.
    • Identify access controls governing prompt templates.
    • Identify the considerations for using a prompt template type such as field generation and flex types.
    • Given a scenario, identify the appropriate grounding technique.
    • and 4 more objectives

    Watch for Flex for everything

    Objectives
    8
    Questions est.
    ~12
    Study time est.
    12–14 hrs
  2. Domain 02 20%

    Data 360 Fundamentals

    Data 360 Fundamentals explains how agents and prompts find trusted answers in unstructured content: the Agentforce Data Library, chunking, vector and hybrid search indexes, and the retrievers that feed relevant passages into retrieval-augmented generation.

    Inside this domain

    • Explain the considerations of Agentforce Data Library and its concepts.
    • Explain foundational concepts of Data 360 such as chunking, indexing, and retrievers.

    Watch for Model blame

    Objectives
    2
    Questions est.
    ~12
    Study time est.
    11–13 hrs
  3. Domain 03 35%

    AI Agents

    AI Agents is the largest section: how agents reason, how Agent Script and topics, instructions and actions shape behavior, how to add deterministic control, which agent type fits, how channels and the Agent API connect agents, and whose permissions an agent uses.

    Inside this domain

    • Explain how an agent works and its basic building blocks of agent script.
    • Explain the components and benefits of hybrid reasoning, including how Agent Script functions in Canvas and Script View.
    • Given a use case, manage deterministic behavior for the agent using mechanisms like filters, variables, and template expressions.
    • Given a scenario, select and configure standard topics, custom topics, standard Agent actions, and custom Agent actions.
    • and 4 more objectives

    Watch for Stronger instructions

    Objectives
    8
    Questions est.
    ~21
    Study time est.
    22–25 hrs
  4. Domain 04 10%

    Testing, Deployment, and Maintenance

    Testing, Deployment, and Maintenance covers the application lifecycle for agents and prompt templates: building test sets in Testing Center, reading evaluation results, and moving agents and templates safely from sandbox to production with their dependencies.

    Inside this domain

    • Given a scenario, test an agent using Testing Center.
    • Explain how Testing Center evaluations work.
    • Identify the considerations for deploying an agent from sandbox to production.
    • Identify the considerations for deploying a template from sandbox to production.

    Watch for Test in production

    Objectives
    4
    Questions est.
    ~6
    Study time est.
    8–10 hrs
  5. Domain 05 10%

    Governance and Observability

    Governance and Observability is about running agents after go-live: monitoring health and adoption, tracing sessions to see why an agent acted as it did, reading agent analytics, and using optimization insights to improve topics, instructions and actions.

    Inside this domain

    • Explain the process for managing and monitoring agents.
    • Explain agent analytics and agent optimization

    Watch for Dashboard for a complaint

    Objectives
    2
    Questions est.
    ~6
    Study time est.
    6–8 hrs
  6. Domain 06 5%

    Multi-Agent Orchestration

    Multi-Agent Orchestration covers when several agents beat one: the single-org multi-agent (SOMA) pattern with an orchestrator routing to specialist agents, and the open protocols, Model Context Protocol and Agent2Agent, that connect Agentforce with outside tools and agents.

    Inside this domain

    • Given a scenario, determine whether a Single-Agent (SOMA) architecture is appropriate for scalability and control.
    • Explain the purpose of existing open standard multi-agent protocols such as MCP and A2A.

    Watch for More agents scale better

    Objectives
    2
    Questions est.
    ~3
    Study time est.
    4–5 hrs

Try one

Practice questionDomain 3: AI Agents

A telecom company's Service agent must check that a customer has verified their account before the Change Plan action can run. In testing, the agent occasionally calls Change Plan directly when customers insist. What should the Agentforce Specialist do?

Choose one answer

One trap from every domain

The answer that looks right, and the clue that gives it away.

  • Domain 1

    Flex for everything

    Clue The scenario names one field on a record page.

  • Domain 2

    Model blame

    Clue The response quotes the wrong document.

  • Domain 3

    Stronger instructions

    Clue The step must never be skipped.

  • Domain 4

    Test in production

    Clue Actions update or create records.

  • Domain 5

    Dashboard for a complaint

    Clue A specific customer conversation is named.

  • Domain 6

    More agents scale better

    Clue The scenario lists only a few distinct topics.

Other Artificial Intelligence & Machine Learning certifications

Study guides for exams that overlap with AI-201.

Practise what you read

AI-201 domains: common questions

How many domains are in the AI-201 exam?

AI-201 has 6 domains with 26 official objectives between them: Prompt Engineering, Data 360 Fundamentals, AI Agents, Testing, Deployment, and Maintenance, Governance and Observability and Multi-Agent Orchestration.

Which AI-201 domain carries the most weight?

AI Agents is the heaviest at 35%, followed by Prompt Engineering (20%). The lightest is Multi-Agent Orchestration (5%). Weights come from Salesforce's official outline.

What is the AI-201 exam format?

Questions: 60 scored multiple-choice (plus up to 5 unscored). Time allowed: 105 minutes. Passing score: 72%.

How long should I study for AI-201?

Our planning estimate is 63–75 hrs across all domains, split by weight. It is an editorial estimate, not an official figure, so adjust it to your experience and to how you score on practice questions.

Where should I start?

Start with AI Agents, because it carries the most marks, then work down by weight. Use the checklist on each domain page to confirm you can do what the domain asks before moving on.

Which outline is this guide based on?

This guide follows Salesforce Certified Agentforce Specialist Exam Guide (AI-201), six sections, aligned to the Spring '26 release (current as of October 2026), published by Salesforce. It was last reviewed in October 2026.

Domain names, weights and objectives come from Salesforce's official outline (Salesforce Certified Agentforce Specialist Exam Guide (AI-201), six sections, aligned to the Spring '26 release (current as of October 2026)). Question counts and study hours are editorial planning estimates, not official figures. Last reviewed October 2026.