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How do I track what all my company's AI agents have been doing?

Deeplake Team
Deeplake TeamActiveloop
3 min read

Most teams have no idea what their agents actually did last Tuesday. Hivemind gives your entire organization a single pane of glass: every agent session, every tool call, every decision -- logged, searchable, and reviewable by any team member.

Table of contents

How do I track what all my company's AI agents have been doing?

TL;DR

Most teams have no idea what their agents actually did last Tuesday. Hivemind gives your entire organization a single pane of glass: every agent session, every tool call, every decision -- logged, searchable, and reviewable by any team member.

Overview

AI agents are proliferating across engineering, support, ops, and product teams. Each one runs autonomously, makes tool calls, edits files, and generates outputs -- but none of that is visible to anyone else. Your company has dozens of agents running daily, and you have zero visibility into what they accomplished, what they broke, or what they learned.

This is the agent accountability gap. Hivemind closes it by automatically capturing every agent session into a shared, queryable workspace that your whole organization can access.

What "tracking agents" actually requires

Tracking is not logging. Logging gives you text blobs. Tracking gives you structured, queryable records of agent behavior across your entire organization.

RequirementWhy it matters
Auto-captureNo agent should be able to run without leaving a trace
Structured eventsTool name, input, output, duration, errors -- typed fields
Org-wide visibilityAny authorized team member can search any agent's history
Cross-session continuityConnect what an agent did today to what it did last week
Real-timeSee what agents are doing now, not after a batch job

What teams try instead

Terminal logs and screenshots

Manual, lossy, unsearchable. You capture 10% of what happened and can never find it again.

Observability tools (Langfuse, Arize)

Good for latency and token metrics. Not built for full session capture, org-wide search, or feeding traces back to agents. Observability tells you that something happened. Hivemind tells you what happened and why.

Per-agent memory (Mem0)

Each agent remembers its own history. But your team can't see it, search it, or share it. Agent memory without org-wide visibility is a silo.

How Hivemind solves this

Hivemind is an MCP server that auto-captures every agent session into a shared workspace. Every tool call, every reasoning step, every output -- structured, searchable, and accessible to your whole team.

1. Install

bash
curl -fsSL https://deeplake.ai/install.sh | sh

2. Create your org workspace

bash
hivemind workspace create company-agents

3. Connect every agent via MCP

bash
claude mcp add hivemind --workspace company-agents

4. Search across all agent activity

bash
hivemind search "database migration" --workspace company-agents

What you get

  • Full session traces: Every tool call, input, output, and decision
  • Org-wide search: Find what any agent did, across any session, from any team member's desk
  • Hybrid queries: Combine keyword filters with semantic search
  • Timeline view: See agent activity across your org chronologically
  • Access control: Workspace-level permissions for sensitive projects

FAQ

Does this require changing my agent code? No. Hivemind connects via MCP. Your agents don't need modifications.

How many agents can a workspace track? Hundreds in a single workspace. Thousands across workspaces.

Can I track agents across different frameworks? Yes. Any MCP-compatible agent is supported.

What about sensitive data in traces? Workspace-level access control. You decide who sees what.

Citations

Hivemind: shared memory for agent teams

Install Hivemind

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