When interacting with an Agentforce Employee Agent in Slack:
Agentforce Employee Agents operate using a per-user session model.
Each time a user invokes the agent:
This design is required because Employee Agents may perform operations such as:
All of these actions must occur within the authenticated user's security context.
Agentforce does not support shared multi-user sessions.
As a result:
The requirement to explicitly @mention the agent is an intentional product design decision.
If the agent remained active after an initial invocation, it could automatically respond to every subsequent message posted by the invoking user within the thread.
This could lead to situations where:
Requiring an explicit @mention ensures that users maintain control over when the agent participates in a conversation.
Although Agentforce creates a new session for every invocation, the Slack integration provides thread history as contextual input.
This means:
Thread history acts as a transcript rather than a shared conversational session.
To ensure the best experience when collaborating with Agentforce in Slack:
To interact successfully with Agentforce Employee Agents in Slack:
https://slack.com/intl/en-in/help/articles/36218786859667-Use-Agentforce-in-Slack
005388402

We use three kinds of cookies on our websites: required, functional, and advertising. You can choose whether functional and advertising cookies apply. Click on the different cookie categories to find out more about each category and to change the default settings.
Privacy Statement
Required cookies are necessary for basic website functionality. Some examples include: session cookies needed to transmit the website, authentication cookies, and security cookies.
Functional cookies enhance functions, performance, and services on the website. Some examples include: cookies used to analyze site traffic, cookies used for market research, and cookies used to display advertising that is not directed to a particular individual.
Advertising cookies track activity across websites in order to understand a viewer’s interests, and direct them specific marketing. Some examples include: cookies used for remarketing, or interest-based advertising.