About the Salesforce Certified Agentforce Specialist Exam

The Salesforce Agentforce Specialist Certification is for individuals who design and implement prompt templates and agents. The exam validates a candidate’s ability to build agents that reason and act across Salesforce and external channels. It targets Administrators, Developers, and Architects who configure Prompt Builder for grounding, leverage Data 360 for retrieval, and manage the Development Lifecycle of agents from testing to production.

Audience Description: Salesforce Certified Agentforce Specialist

The Salesforce Certified Agentforce Specialist candidate is proficient in configuring and managing AI agents and prompt templates on the Salesforce Platform. The candidate has a comprehensive understanding of Salesforce Platform configuration and the ability to align AI agents to complex business use cases. Successful candidates demonstrate the skills to deliver personalized, context-aware interactions using Agentforce tools and capabilities.

A successful candidate typically has 1 year of experience with Salesforce platform configuration and standard objects, including Data 360. This includes hands-on experience building agents in Agentforce Agent Builder and creating prompt templates in Prompt Builder. Furthermore, the candidate is familiar with testing tools such as Agentforce Testing Center and established deployment patterns from Sandbox to Production.

A candidate for this exam has the knowledge and skills to:

• Engineer Agentforce agents using next-generation authoring (NGA).
• Manage the Agent and Prompt Template Lifecycle, including ideation, building, testing, deployment, and observation.
• Implement sophisticated grounding for agents and prompt templates using Data 360 concepts such as chunking, indexing, and retrievers.
• Maintain governance by applying the Trust Layer and managing specific model access.
• Orchestrate systems using existing open standard multi-agent protocols, including Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication.
• Determine appropriate architectures, such as Single-Agent (SOMA), to ensure scalability and control.

A candidate for this certification is not expected to:

• Have extensive knowledge of configuring and fine-tuning large language models (LLMs).
• Understand the basics of coding languages such as Apex or Python.
• Possess expertise in external AI tools.
• Understand transformer architecture.
• Perform return on investment (ROI) calculations or white space analysis.
• Have experience with Marketing Cloud, Heroku, Commerce Cloud, MuleSoft, Tableau, Slack, Quip, or Industry Clouds.

Purpose of This Exam Guide

This exam guide is designed to help you prepare for the Salesforce Certified Agentforce Specialist Exam. This guide provides information about the target audience, the recommended training and documentation, and a complete list of exam objectives. Salesforce highly recommends a combination of on-the-job experience and self-study to maximize your chances of passing the exam.

About the Exam

Here are details about the Salesforce Certified Agentforce Specialist Exam.

• Content: 60 multiple-choice questions and up to five unscored questions
• Time allotted to complete the exam: 105 minutes
• Passing score: 72%
• Version: Exam questions align to the Spring ’26 release.
• Registration fee: USD 200, JPY 30,000, plus applicable taxes as required per local law; JPY 30,000
• Retake fee: USD 100, JPY 30,000, plus applicable taxes as required per local law; JPY 30,000
• Delivery options: Proctored exam delivered onsite at a testing center or in an online proctored environment; find more information on scheduling an exam here.
• References: No hard-copy or online materials may be referenced during the exam.
• Prerequisite: None
• Language offerings: English, French, Japanese, and Spanish

This exam may contain up to five additional unscored questions to gather performance data. Unscored questions are randomly integrated and have no impact on your final exam result.

Exam Outline

The Salesforce Certified Agentforce Specialist Exam measures a candidate’s knowledge and skills related to the following objectives.

Prompt Engineering: 20%

• 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.
• Explain the process for creating, activating, and executing prompt templates.
• Explain how to implement best practices for writing effective prompts.
• Identify the security and privacy features of the Trust Layer.
• Explain how to manage and prevent specific models from being accessed.

Data 360 Fundamentals: 20%

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

AI Agents: 35%

• 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.
• Explain the process for connecting agents to various channels such as digital experience, email, voice, and Slack.
• Explain the security context in which the agent is actually running, and how it impacts agent action execution.
• Given a scenario, identify when to use an Employee or Service agent.
• Given a scenario, identify when it’s appropriate to use Agent API.

Testing, Deployment, & Maintenance: 10%

• 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.

Governance & Observability: 10%

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

Multi-Agent Orchestration: 5%

• 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.