AI agents are set to become ubiquitous in our daily lives. Here’s how they work and how they are transforming business and application development alike.
Agents are assistive and autonomous software systems. Based on user input or environmental conditions, they reason, plan, and take action to achieve given tasks or goals. They are like intelligent digital assistants, equipped with the aggregated knowledge and experience of human experts, and access to all relevant data.
Agents are set to become ubiquitous across every area of our lives, and to profoundly transform how businesses operate and interact with customers. For example, a service agent can act as your company’s most knowledgeable technical support representative, available 24/7 to handle every request. A marketing agent, much like a self-driving car, can use “sensors” (real-time data) to detect changing business conditions and respond proactively (adjust pricing, launch a campaign, and so on).
The ultimate application composition platform
The most transformative aspect of this new software paradigm is that it enables agents to handle unanticipated requests without predefined requirements. Imagine an agent equipped with dozens or even hundreds of actions. It could compose them in a virtually infinite number of ways, including in ways never anticipated, enabling it to solve new problems on the fly. This is the ultimate form of application composition.
For example, at Salesforce, our industry-leading applications (including Sales Cloud, Service Cloud, Marketing Cloud, Commerce Cloud, and Industries) are broken down into granular actions that can instantly enable Salesforce’s Agentforce Agents with a wealth of capabilities across various topics. Agentforce Agents can compose and orchestrate these actions in any number of ways, providing users with a seamless and unified experience across the business. In addition, developers can extend the standard Agentforce agents’ capabilities with custom actions powered by code, APIs, Salesforce flows, or prompt templates. Finally, you can deploy your agents in Slack and chat with them as you would with a teammate.
Actions empower agents with the following essential capabilities:
Access to private company data: Actions provide agents with access to your customer and enterprise data. When giving any agent access to data, it’s important to ensure that the agent doesn’t disclose data to unauthorized users. Using Agentforce Agents, access to data is governed by permissions and sharing models. The same permissions and sharing models apply regardless of where the data is accessed from: traditional applications or agents.
Ability to take action: Actions enable agents to execute logic and integrate with external systems. Standard Agentforce actions have that ability built-in: They can act on sales, service, marketing, commerce, and industries. In addition, developers can build custom actions that can act on Salesforce or external systems using code, APIs, flows, and prompt templates.
Different levels of autonomy
Agents can have different levels of autonomy. For example:
Assistive agents (sometimes referred to as copilots) collaborate with humans, enhancing capabilities rather than acting alone. Copilots often require human input and feedback to refine suggestions or actions.
Autonomous agents operate independently without direct human supervision. Agentforce Agents, unlike other autonomous agents, have the capability to seamlessly hand off tasks to humans as needed.
Regardless of an agent’s autonomy level, establishing appropriate guardrails is crucial to ensure reliability, adherence to business practices, and data security and privacy, as well as to prevent hallucinations, toxicity, and harmful content.
Agentforce Agents use a multilayered approach to enforce guardrails:
Einstein Trust Layer: The Einstein Trust Layer enables agents to use LLMs in a trusted way, without compromising company data. It uses a secure gateway, data masking, toxicity detection, audit trails, and more to control LLM interactions.
Instructions: When defining an Agentforce Agent, you can use natural language to provide clear instructions, including what to do and what to avoid, effectively setting the guardrails for its behavior.
Shared metadata: Salesforce metadata defines overarching rules that are enforced regardless of whether the data is accessed from traditional applications or agents. This includes permissions, sharing models, validation rules, and workflow automation to guarantee data security and adherence to business practices.
Agent Analytics: This observability tool provides insights into agent and action performance, usability, and reliability, enabling you to identify areas for improvement.
AI Test Center: A unified testing framework, the AI Test Center supports batch testing for agents, prompt templates, retrieval-augmented generation (RAG), and model use cases.
Ready-to-use agents for sales and service
Salesforce recently announced agents for Sales and Service:
Agentforce Service Agent revolutionizes customer service with its ability to understand and take action on a broad range of service issues without preprogrammed scenarios, helping make customer service far more efficient.
Agentforce SDR Agent autonomously engages with inbound leads, in natural language, to answer questions, handle objections, and book meetings for human sellers.
Agentforce Sales Coach Agent autonomously engages in role-plays with sellers, simulating a buyer during discovery, pitch, or negotiation calls.
You can use these agents out-of-the box, but Agentforce also enables you to customize them, extend them, and create your own agents.
Create and customize agents with Agentforce
Salesforce Agentforce brings humans together with autonomous agents powered by AI, data, and action. It provides the features and tools you need to create, customize, and deploy trusted agents and other innovative AI applications, complete with the right guardrails and supervision. Let’s take a closer look and walk through the key components.
Summary: How Agentforce Agents are transforming business and application development
Agents are set to become ubiquitous in every area of our lives. They can reason, orchestrate tasks, and take action, delivering personalized experiences at scale. By combining the language and reasoning capabilities of LLMs with software building blocks, they are transforming how businesses operate and how software is built.
Agentforce Agents are leading this transformation with key differentiating characteristics, including:
Trusted. Agentforce protects your data using the Einstein Trust Layer and the same metadata, permissions, and sharing models as traditional Salesforce applications.
Powerful. Agentforce Agents make use of industry-leading Salesforce applications to deliver transformative experiences across sales, service, commerce, marketing, and industries.
Grounded in unified data. Agentforce Agents deliver more accurate and relevant outcomes by grounding AI in all the relevant data made available and unified by Data Cloud.
Low-code tools. Agentforce Agents can be built, customized, tested, and managed using a set of low-code tools including Agent Builder, Prompt Builder, Model Builder, Flow Builder, and more.
