
You will be able to use record summary prompt template and use it on flexi page
You will be able to use field description prompt template and use it on flexi page
Create a flex template to capture user free-text input and prompt template to process it, then invoke prompt template in apex to get response and view results in debug log.
You will learn to use and create flows and agent actions and will be able to create using agentforce.
Create a user using custom agentforce actions with flows, collecting required fields like alias, email, first name, last name, nickname, profile id, applying defaults, and outputting the generated user ID.
You will learn the capabilities of Agentforce for developers, It can create test methods, generate code and explain also.
In this lecture, we will know how to make rest api callout and generate responses.
Learn to fetch real-time city weather using the open weather API by building a flow, configuring named credentials, and exposing an agent action for Einstein Copilot.
Create an apex class with an invocable method Get Case Data and integrate it into a field generation prompt template to generate a count record summary with related cases.
Master the template-triggered flow inside a prompt template to fetch related account cases, loop through records, and generate summaries, replacing Apex class in Salesforce agent workflows.
Use a prompt template as an agent action to generate a grounded account record summary with related cases, leveraging the Apex class and prompt template setup for Salesforce.
Learn to deactivate a Salesforce customer account using an email service and a prompt template, with Apex class that sets the account's active field to no and creates a case.
Create a prompt template with a file object, upload a restaurant menu image, ensure the AI model supports images, and refine a prompt to obtain a JSON response.
Extract information from notes and attachments to power AI agents in Salesforce Agentforce, enabling efficient data capture and deployment.
Create some sample data to support building and deploying AI agents in Salesforce Agentforce, giving learners practical practice with agent data.
Create a new topic with instructions for your agent, ensuring correct responses, and activate the agent before deploying it to the community website.
Enable omnichannel and activate enhanced omnichannel routing to optimize agent assignment, then log agents in automatically in a new window and save the settings.
Learn how to create routing configurations to direct AI agents within Salesforce Agentforce, enabling efficient deployment of AI agents across workflows.
Ensure the service agent is active to create an omnichannel flow, then confirm the flow appears in the connections tab under inbound omnichannel.
The site agent runs correctly, but typing indicators were missing until publishing the embedded service deployment after changes; now the typing indicators appear.
Learn how to create a service channel in Salesforce Agentforce and select the messaging session object, avoiding duplicates when a channel already exists.
Create and manage presence statuses for a human agent online on messaging channels, add new options, and use busy to bypass extra settings.
Create or reuse a queue to route sessions to human agents, transfer occurs to agents in the selected queue, using the existing messaging queue with one user already added.
Provide present status access to the agent user using a permission set, then enable service cloud user settings so the agent can see conversations.
Create an outbound omnichannel flow that routes the AI agent conversation to a human, fetches a contact, creates a related case, and updates the messaging session with the case ID.
Deactivate the agent, add the outbound omnichannel flow in the agent builder connections tab, and save it. Define escalation instructions to transfer to a human agent when needed, then activate.
Enable knowledge settings to access the knowledge tab in the service console. The walkthrough covers enabling settings in setup, keeping them unchanged, with no knowledge articles yet.
Assign knowledge, article, object, and field access for the agent user by selecting its username and opening user details, then add required permissions to a permission set, including knowledge object.
Add fields to knowledge articles to save additional information. Expand knowledge articles by including these fields to store more details.
Configure a permission set and connected app for API access, then call the agent API in Postman by managing client credentials, starting sessions, sending messages, and ending sessions.
Update the command line interface with sfdx, install the agent force plugin and vscode extension, create a yaml agent specification file, and deploy to auto-create topics and actions.
Salesforce recommends employee agents over the deprecated agent force default. They are user specific, preconfigured with topics and actions, protected by the Einstein Trust layer, and support order details.
Connect the Salesforce MCP server to Postman by creating an external client, configuring OAuth 2.0 with PKCE, obtaining the consumer key and secret, and testing with SQL queries.
Connect and test the Salesforce MCP server with ChatGPT to validate AI agent integration within the Mastering Salesforce Agentforce course.
Connect with Claude to validate AI agent integrations on the Salesforce Agentforce platform, and test the interoperability of built agents in real-world scenarios.
Create Apex REST classes for the MCP server, deploy a global post method to create accounts, and generate open API specifications before testing via VS code.
Learn how to use a custom apex rest class in Claude to build and deploy AI agents for Salesforce Agentforce.
Create an Apex action for the MCP server using an invocable method to update a case status by case ID, validate inputs, and deploy without an open api specification.
Connect the Salesforce MCP server in Cursor by configuring a callback URL and enabling the MCP API with JSON web token based access tokens and proof key for code exchange.
In today’s fast-paced digital world, AI-driven automation is revolutionizing how businesses operate. Salesforce Agentforce is your practical, step-by-step guide to building intelligent AI agents using cutting-edge Salesforce technologies like Apex, Flows, Prompt Builder, and Agentforce APIs.
Whether you're a Salesforce Developer, Admin, or Consultant, this course equips you to create powerful, scenario-based AI agents that handle real-world business tasks—like lead qualification, case resolution, customer engagement, and meeting scheduling—automatically.
What You’ll Learn:
Core Concepts of Agentforce AI: Understand what AI agents are in Salesforce and how they work behind the scenes
Hands-On Agent Creation: Build agents with custom Apex logic, declarative Flows, and Prompt Templates
Use of Prompt Builder: Learn how to create dynamic prompts using text, images, and context variables for personalized interactions
Deep Dive into APIs:
Use the Agent API to trigger and manage agents programmatically
Work with MIAW (Messaging In App and Web )API to integrate AI models seamlessly into your flows
Explore Models API to select and fine-tune the right AI model for your use case
Context Variables & Filters: Use context to tailor agent behavior based on user role, record data, and interaction history
Data Library Integration: Learn how to use Agentforce's Data Library by connecting files, knowledge articles & web search
Real-World Scenarios: Build agents for industries like sales, customer support, and field service
Agent Deployment: Best practices for deploying and scaling agents across your Salesforce org
Mask Sensitive Information: Best practices for masking sensitive data during agent conversation
Extract Information From Files : Extract information from Files And Notes & Attachments in prompt builder.
Agentforce DX : Create Agents Using CLI commands and Testing(Coming Soon).
MCP : What is MCP and How to Create Custom MCP Server in Salesforce. How to connect Salesforce MCP Server to different MCP Clients like Postman, Claude & ChatGPT
Create MCP Actions using Apex REST, Flows, Apex Actions, Named Query API and Aura Enabled Methods