Show & Tell Series: Building and Deploying Securely with Agentforce

Agentforce is the agentic layer of the Salesforce platform, empowering businesses to deploy autonomous AI agents across any business function. It provides a comprehensive suite of tools for creating and customizing agents, along with a rich library of pre-built skills for sales, service, marketing, commerce, Tableau, Slack, partner ecosystems, and more. However, effectively developing and deploying these sophisticated agents requires a robust and secure Application Lifecycle Management (ALM) strategy to ensure successful and risk-mitigated implementations.

The Importance of a Secure ALM for Agentforce

Developing Agentforce agents involves intricate interactions with data, workflows, and customer experiences within the Salesforce ecosystem. A robust ALM strategy is crucial for:

• Data Security: Protecting sensitive customer and business data within the Salesforce environment from unauthorized access or accidental exposure during development and deployment.
• Service Continuity: Minimizing disruptions to critical business processes and ensuring uninterrupted customer service within the Salesforce platform.
• Quality Assurance: Enforcing rigorous testing and quality control measures throughout the Agentforce development cycle to ensure agent performance meets expectations.
• Compliance: Adhering to Salesforce security and compliance standards, as well as any industry-specific regulations.

The Role of Sandboxes in Secure Agentforce ALM

Sandboxes play a pivotal role in this secure ALM framework for Agentforce. They provide isolated environments within the Salesforce ecosystem where developers can:

• Prototype and Experiment: Safely test new Agentforce features, modify existing agent behaviors, and experiment with different configurations without impacting live customer interactions or core business processes.
• Conduct Thorough Testing: Rigorously test Agentforce agent behavior, identify potential issues, and refine their performance within the secure sandbox environment before deploying to production.
• Minimize Risks: Identify and mitigate potential risks, such as data breaches, service disruptions, and compliance violations, early in the Agentforce development cycle, minimizing the impact on live systems.

A Practical Example: Implementing Warranty Transfers

Let’s consider the implementation of warranty transfer functionality for an e-commerce customer using Agentforce.

Development in a Salesforce Sandbox: Developers can utilize a sandbox to build and test the new Agentforce action that triggers the warranty transfer process. With data cloud support inside a sandbox, we can provide the critical data layer needed for succesful Agentforce implementations. The developers can experiment with different logic, integrate with relevant Salesforce objects and flows, and refine the agent’s behavior without affecting live customer interactions or core business processes.

Rigorous Testing within the Sandbox: While there is built in testing capability inside the Agent Builder for turn by turn testing, given the non deterministic nature of the agents, we need more thorough testing to ensure we have the required results. With Testing Center, developers can test their changes across hundreds of test cases and iterate them to perfection.

Controlled Deployment to Production: Once thoroughly tested and validated in the sandbox, the changes can be carefully packaged and deployed to production Salesforce environments using familiar tools — thanks to the Metadata API support.

And thats how we can make Agentforce implementations real for our enterprise customers. By integrating security throughout our development process. We can drive innovation while maintaining trust and ensuring compliance.