Salesforce Agentforce is a powerful AI tool that helps automate tasks, answer questions, and guide users—all with minimal human help. But how does it actually work? And what are its key parts? Let’s explore how Agentforce agents are built and how they operate.
The Core Building Blocks of an Agent
Every Agentforce agent is made up of five key components:
Agent: The AI assistant itself. It’s designed to reduce workload and boost productivity by handling routine and complex tasks. Agents can work independently, spot opportunities, and take action within the rules you set.
Topics: These are categories of tasks the agent can handle. For example, a topic like “Deal Management” might include actions to find contacts, log calls, or create to-do items.
Actions: These are the steps the agent takes to complete a task. Actions can include sending messages, updating records, or drafting emails using Salesforce data. You can use built-in actions or create custom ones for your business.
Reasoning Engine: This is the brain that helps the agent decide what to do. It reads the user’s message or trigger, picks the right topic, and plans how to reach the goal using available actions.
Large Language Model (LLM): This is the smart technology that helps the agent understand language and respond naturally. The reasoning engine calls the LLM multiple times during a task to make sure the agent understands and reacts correctly.
How Agentforce Works Step-by-Step
Let’s follow the journey of a user message through the Agentforce system:
1. A Message or Trigger Starts It All
The process begins when a user sends a message or when a trigger (like a lead assignment or data change) activates the agent.
2. The Agent Picks a Topic
The agent compares the message to all available topics and picks the one that best matches the task. If no match is found, it switches to an “Off-Topic” mode and tries to guide the user back.
3. The Agent Starts Reasoning
The agent uses the reasoning engine to:
Run actions like flows or Apex classes
Ask for more details or clarifying questions
Respond directly if it already has the answer
It follows topic instructions carefully—for example, asking for a model number before giving product info or verifying identity before sharing account details.
The agent loops through this reasoning process up to seven times to make sure it gets things right.
4. Final Response Check (For Service Agents)
Before replying, the agent checks if the answer is safe, accurate, and based on trusted data. If the response doesn’t pass, it creates a new one. If it still can’t help, it lets the user know.
5. The Agent Sends the Reply
Finally, the agent sends the message. The user can reply or ask something new, and the agent continues the conversation smoothly.
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