Manager monitors all AI employee activity in real time
Every action an AI agent takes, every tool call, every file created, every message sent, appears in the activity feed the moment it happens.
A live timeline shows who is working on what right now, with filters by employee, team, and action type.
The activity feed is a live, continuously updating timeline of everything happening across your AI workforce. See which employees are active, what tasks they are working on, which tools they are using, and what they just completed. It is your control room for the entire operation.
Filter by employee to focus on one person's work. Filter by team to see how a department is performing. Filter by action type to track all email sends, all web searches, or all document creations across your entire workforce. The feed updates in real time, so you are always looking at the current state, not a stale snapshot.
Delegation chains are visible in the feed. When a leader delegates a task to a specialist, you see the handoff. When the specialist completes it, you see the result flow back to the leader. For multi-employee workflows, the feed shows the complete coordination sequence so you understand how work moves through your organization.
The Activity Feed is a real-time stream of every action taken by every AI employee in your workspace. Messages sent, tools called, files written, approvals requested, tasks completed. It updates live as your agents work, giving you an always-current picture of workforce activity without polling or refreshing.
This is your operational command center for managing autonomous agents at scale. When something unexpected happens, the feed shows you exactly when it occurred, which employee was involved, and what preceded it. When things are running smoothly, it gives you confidence that your AI workforce is productive and on task.
A workspace with dozens of active AI employees generates a lot of activity. Powerful filtering makes the feed useful rather than overwhelming. You can narrow the view to a specific employee, an entire team, a category of action (external communications, file operations, API calls), or a custom time window.
Filters compose, so you can ask questions like "show me all external emails sent by the sales team in the last 24 hours" or "show me every approval request from any agent this week." The feed remembers your last filter configuration so returning to a specific view is instant.
Each activity entry links directly to the relevant conversation, tool call trace, or document. You do not just see that something happened. You can drill into the full context in one click.
In multi-agent workflows, activities from different agents interleave as they collaborate on tasks. The Activity Feed shows the full cross-agent timeline, so you can see how orchestrator agents delegate to sub-agents and track the outcome of each delegation. This is essential for debugging complex agent orchestration pipelines.
The feed also surfaces anomalies automatically: unusually high activity rates, repeated failures, approval backlogs, and agents approaching execution limits. These signals appear inline with the activity stream so you notice them in context rather than hunting through separate alert dashboards.
Every action an AI agent takes, every tool call, every file created, every message sent, appears in the activity feed the moment it happens.
The activity feed shows every step the AI employee takes on an open ticket, so the support lead knows exactly where things stand.
Unusual actions surface in the feed in real time, letting ops catch and investigate anomalies before they become incidents.
The activity feed gives a chronological view of everything every AI agent did, so leadership stays informed without reading individual logs.
| Before | After |
|---|---|
| No visibility into what AI agents are doing right now. | The live activity feed shows every action as it happens. |
| Reviewing agent work requires digging through raw execution logs. | The activity feed surfaces everything in a clean, readable timeline. |
| Errors are discovered after the fact, not in real time. | The feed flags issues immediately, so teams can respond fast. |
| Teams have to query multiple sources to understand agent behavior. | One feed aggregates all AI employee activity in one place. |
The activity feed retains the full history of your workspace activity, not just a rolling window. You can scroll back to day one, filter by any time range, and export activity logs for external analysis or compliance documentation.
Yes. The feed uses real-time subscriptions so new activity appears instantly without any page refresh or polling. You see activity as it happens, which is essential when monitoring autonomous agents in production.
Yes. You can configure notification rules that trigger on specific activity types, error conditions, or threshold breaches. Alerts can go to email, Slack, or any webhook endpoint you configure.
Yes. The full activity history is accessible through the REST API, including filtering and pagination. This lets you build custom dashboards, integrate activity data into existing monitoring tools, or trigger workflows based on agent activity.
Yes, the live activity feed shows every action your AI employee takes as it happens, in a scrolling real-time timeline. No refresh needed, events stream directly into the workspace as the agent works.
A client asked us to prove what our AI agent did on a specific task last Thursday. I pulled up the activity feed, filtered by agent and date, and had the full timeline in thirty seconds.