How to Build Custom Prompts for Agentforce AI Agents
Salesforce’s Agentforce represents a new era of AI-powered productivity, enabling businesses to automate complex workflows and deliver personalized customer experiences using intelligent, conversational agents. These AI-driven agents rely heavily on custom prompts to understand, respond, and act on user requests with context and accuracy.
But here’s the secret — the real power of Agentforce lies in how effectively you design these prompts. Crafting custom prompts tailored to your business logic and communication style can dramatically improve the quality, precision, and reliability of AI responses.
In this guide, we’ll explore how to build effective custom prompts for Agentforce AI agents, step-by-step. You’ll learn prompt design principles, advanced techniques, and real-world best practices that help your agents think, speak, and act more intelligently.
Understanding Custom Prompts in Agentforce
Before creating custom prompts, it’s important to understand how they work within Agentforce.
Agentforce leverages the Einstein 1 Platform, integrating Data Cloud, Einstein Copilot, and the Trust Layer to power generative AI capabilities securely. Prompts act as structured instructions that tell the agent how to think and respond based on user input.
What is a Prompt?
A prompt is the text or instruction given to an AI agent that defines its behavior or guides its response. In Agentforce, prompts help the AI:
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Understand user intent
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Access relevant data from Salesforce objects
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Perform actions like updates, queries, or case creation
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Maintain consistent tone and context across interactions
Why Custom Prompts Matter
While Agentforce comes with pre-built templates and Copilot actions, custom prompts allow you to:
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Adapt AI tone to your brand voice
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Include domain-specific vocabulary
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Add contextual logic for different departments (e.g., sales vs. service)
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Ensure compliance and reduce hallucinations
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Boost accuracy and response relevance
In short, custom prompts turn your Agentforce setup from “generic AI assistant” to a specialized enterprise-grade virtual expert.
Step 1: Define the Objective of the Prompt
Every custom prompt must begin with a clear purpose. Define what you want your Agentforce agent to achieve.
Ask yourself:
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What type of query or action should this prompt handle?
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What kind of tone or language fits my business?
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Should the agent retrieve, summarize, or generate content?
Example Objectives
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“Assist sales reps by summarizing recent lead activity.”
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“Help customer service agents draft empathetic responses for delayed shipments.”
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“Generate internal notes for support cases using structured case details.”
Clarity at this stage prevents confusion later when testing or deploying prompts.
Step 2: Structure the Prompt Effectively
A well-structured prompt helps Agentforce understand context and deliver accurate responses. A good prompt generally includes:
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Role Definition: Tell the agent who it is (e.g., “You are a Salesforce support assistant.”)
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Task Instruction: Describe what the agent needs to do.
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Context Data: Include relevant Salesforce records or data points.
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Output Format: Specify how the response should appear (e.g., bullet points, summary, JSON).
Example Prompt Template
Prompt:
“You are an intelligent Salesforce AI assistant helping support agents resolve cases faster. Given the case details below, summarize the issue, suggest the next best action, and format the response as bullet points.”
Input:
Case: ‘Customer reports product malfunction after update’
Status: ‘Open’
Priority: ‘High’
Expected Output:
Summary of issue
Suggested next steps
Recommended resolution timeline
This structured approach gives your Agentforce agent a clear, contextual roadmap for generating accurate results.
Step 3: Use Variables and Dynamic Data
Static prompts can only go so far. For scalable automation, your prompts should adapt dynamically based on user inputs or Salesforce records.
Agentforce supports dynamic placeholders that fetch live data from Salesforce objects.
Example
“You are assisting a sales manager. Summarize the opportunity for {{Opportunity.Name}}, currently in stage {{Opportunity.StageName}}, with an expected revenue of {{Opportunity.Amount}}. Provide a one-sentence overview of the deal’s progress.”
This ensures every response is personalized and data-driven, eliminating the need for manual customization.
Best Practices for Dynamic Prompts
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Use only relevant fields — too much data can confuse the model.
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Validate data before passing it into the prompt.
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Keep placeholder names consistent across templates.
Step 4: Control Tone, Style, and Brand Voice
Your AI agents should communicate in a tone that matches your company’s identity. Whether you want the agent to sound professional, friendly, or analytical, tone control is achieved through stylistic guidance in the prompt.
Example
“Respond in a professional yet empathetic tone suitable for a customer service agent. Avoid jargon and keep sentences short and clear.”
Or for marketing use:
“Write in an engaging, conversational style that reflects our brand’s optimistic and innovative personality.”
Tone Guidelines
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Use active voice for clarity.
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Maintain consistency across different departments.
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Avoid emotionally neutral or robotic phrasing unless needed for compliance.
Step 5: Add Context Awareness
Agentforce’s AI performs best when it understands contextual background — past interactions, user preferences, or case history.
You can include memory-based context or session history in your prompts to improve personalization.
Example
“You previously helped this customer with a billing issue. They now have a follow-up question about refund status. Continue the conversation with awareness of the prior context.”
This technique reduces repetitive responses and makes AI interactions more human-like.
Step 6: Test and Refine Prompts
Prompt design is an iterative process. Even small wording changes can affect output quality.
Testing Methods
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Use sandbox environments in Salesforce to test prompts before deployment.
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Compare multiple versions of a prompt to measure clarity and accuracy.
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Collect feedback from users to refine tone and relevance.
Metrics to Evaluate
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Response time
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Accuracy rate (based on test data)
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Hallucination frequency
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User satisfaction score
Continuous tuning helps ensure that your custom prompts evolve alongside your business processes.
Step 7: Secure Prompts Using the Einstein Trust Layer
Security and compliance are central to Salesforce’s AI architecture. When building prompts, ensure sensitive or personally identifiable information (PII) is protected.
Best Practices
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Use data masking for fields containing personal details.
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Enable Trust Layer filtering to prevent unintentional data leakage.
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Restrict prompt access using Salesforce permissions and role hierarchies.
With proper governance, you can create high-quality, compliant prompts without compromising security.
Step 8: Automate Prompts Across Workflows
Once your prompts are tested and optimized, integrate them across multiple workflows for maximum efficiency.
Common Use Cases
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Sales Cloud: Auto-generate follow-up emails or proposal summaries.
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Service Cloud: Draft knowledge articles or troubleshoot instructions.
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Marketing Cloud: Personalize campaign content dynamically.
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Field Service: Provide on-site engineers with real-time diagnostic suggestions.
By embedding prompts within Salesforce Flows, Apex classes, or API-driven automation, you turn Agentforce into an always-on intelligent collaborator.
Step 9: Version Control and Documentation
To maintain prompt reliability, document every iteration and maintain version control.
Documentation Should Include:
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Prompt name and purpose
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Variables used
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Input and output formats
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Version number and update date
Tools like GitHub or Salesforce’s DevOps Center can help you manage and track prompt changes efficiently.
Step 10: Leverage Feedback for Continuous Learning
The best AI agents improve over time through human feedback loops. Encourage your users — sales reps, service agents, or marketers — to rate AI responses and provide feedback.
Implementation Tips
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Create feedback buttons in chat interfaces.
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Store ratings in a custom Salesforce object.
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Use analytics dashboards to identify top-performing prompts.
Iterating based on real-world input helps you maintain precision and user satisfaction.
Common Mistakes to Avoid
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Overly long prompts: Keep instructions concise; avoid unnecessary details.
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Vague instructions: The AI performs best when you give direct, clear commands.
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Ignoring tone: An inconsistent brand voice confuses customers.
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Not testing in real contexts: Always validate prompts with real business data.
Avoiding these pitfalls ensures smoother Agentforce performance and user trust.
Example: A Custom Prompt in Action
Scenario: A customer service team wants Agentforce to draft case summaries.
Prompt:
“You are a Salesforce support assistant. Summarize the case below in 3 bullet points, focusing on the main issue, resolution status, and next step. Use an empathetic, customer-friendly tone.”
Input:
Case: “Customer reported delayed shipment and requested refund.”
Status: “In progress”
Priority: “High”
Output:
Customer reported shipment delay and asked for refund assistance.
Refund process has been initiated.
Follow up with confirmation once refund is processed.
This simple yet structured prompt improves efficiency, consistency, and response quality.
Conclusion
Building custom prompts for Agentforce AI agents is both an art and a science. It requires understanding how language, structure, and data work together to shape intelligent behavior. By defining objectives clearly, using dynamic data, and testing continuously, you can craft prompts that deliver accurate, brand-aligned responses every time.
Agentforce’s flexibility allows you to transform everyday workflows — from sales calls to customer support — into seamless, AI-driven experiences. With thoughtful prompt engineering, you don’t just automate tasks; you elevate human-AI collaboration to a new standard of productivity and intelligence.
In 2025 and beyond, the organizations that master prompt design will lead the way in AI-powered business transformation.
