Agentforce Guide to Achieving Reliable Agent Behavior

Agentforce Guide to Achieving Reliable Agent Behavior

Get guidance and best practices to help you build agents that operate with creativity and control.

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The rise of agentic AI presents both incredible opportunities and unique challenges. As AI agents become more integrated into business operations, the focus on trust extends beyond data security to encompass the accuracy and reliability of these agents. That's exactly why I'm excited to share our newest Agentforce Guide, written by Olfa Kharrat, Director of Product Management and Reinier van Leuken, Senior Director of Product Management, designed to help you navigate this complex terrain and build agents that operate with creativity and control.

The Agentforce Guide to Building Reliable Agents addresses a fundamental tension: the inherent non-deterministic nature of large language models (LLMs) that power AI agents and the desire to use generative AI in the enterprise. While the dynamic nature of LLMs is what allows for creative problem-solving and adaptable responses, it can clash with the need for predictable, deterministic business results. This guide provides a comprehensive framework for striking this crucial balance, ensuring that agents can operate with both innovation and control.

Build agents that operate with creativity and control

At the heart of this guide are the five levels of agentic control, a layered strategy to help you achieve "guided determinism". Here's a quick look at this framework:

• Level One: Reasoning with Instruction-Free Topic & Prompt Action Selection
  This foundational level provides agents with maximum freedom, allowing them to select actions based on ongoing conversation and descriptions of topics and actions.
• Level Two: Agent Instructions
  By introducing explicit instructions, rules, guidelines, guardrails, and examples, this level enhances consistency and ensures adherence to established company processes.
• Level Three: Data Grounding
  Connecting the agent's understanding and responses to external knowledge sources like databases is critical at this level. This ensures accuracy, provides up-to-date information, and builds trustworthiness.
• Level Four: Agent Variables
  This level empowers agents to work with variables, facilitating personalized interactions, context retention, and dynamic adjustments based on specific data points within a session.
• Level Five: Apex, API, and Flow Actions
  The most advanced level integrates agents with Salesforce's core functionalities, enabling them to perform complex actions, manipulate data, trigger workflows, and interact seamlessly with other systems, transforming the agent into a powerful business tool.

In an era where AI agents are becoming indispensable, understanding how to ensure their reliability and compliance is key. Discover practical strategies for developing agents that are not only innovative but also consistently deliver on business objectives. Explore the full guide here.

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As Director of AI Product Marketing, I lead content and customer strategy for all things Agentforce, including the Agentblazer community.