AI

Think of an Agentic AI workflow as being like a team of people with different roles. Each person on the team will have a role, and know exactly how to perform that role. This allows for the team to process complex workflows and solve problems at every step. An AI agent is an AI solution that has a role and is specifically trained to perform actions in that role. This allows for multiple AIs to be able to work together to process complex needs just like the team of people.

Because you can have multiple AI Agents working together, you can basically build anything that you could describe to a group of people to do. You can have Agents which are LLMs (large language models) that chat with human beings either internally in Salesforce, or externally to clients or partners. These chat bot agents can decide what to do with the chat based on guidelines that have been given to it. The agent can decide to ask another agent to gather information from Salesforce records, or external data. A third agent can be asked to process this data to get insights, and then provide that information to the chat bot agent. This is an example of a very simple workflow which can be extrapolated into much more complex scenarios.

Agentforce is a black box. Your data, questions, and setup are all securely yours and none of it will get out of the system or be used to train other systems. This is all contained within Salesforce's security and is encrypted and secure throughout every part of the process.

With Agentforce, the best first step is to make sure that you specify the guidelines for every Agent. This allows you to tell each one what it can do, what it can NOT do, and rules around how it should perform its role. The cool thing about an agentic workflow is that you can have both hard coded checks, and other AI agents which check the output before anything is done. These tools allow you to make extremely well defined rails for these systems to make sure that they provide value without going off those rails.