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W&B HiveMind is a shared dashboard for AI coding sessions. The dashboard shows what your team is doing with agents, what that work costs, and what it produces, with leaderboards, team views, efficiency insights, and more. A lightweight HiveMind daemon runs on each developer’s machine, watches for coding-agent activity, and sends session transcripts to the HiveMind service. HiveMind is designed for a dual audience:
  • Developers and AI practitioners can review past sessions, search their team’s history, and improve how they work with coding agents.
  • Engineering leaders can track AI coding adoption, spend, and outcomes across teams and repositories.

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Quickstart

HiveMind and its documentation live on a dedicated site: hivemind.wandb.tools.

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1. Install the HiveMind daemon

On each team member’s local system, install the client, authenticate, and start the daemon. Choose the method that fits your platform.
Download and install HiveMind using the signed standalone binary:
curl -fsSL https://hivemind.wandb.tools/install -o hivemind-install.sh | sh
hivemind login
  • On macOS, the standalone binary requires Apple Silicon. On an Intel Mac, use uv instead.
  • Privileged access (sudo) is not required.
  • The installer registers a background service (launchd on macOS, systemd on Linux) so the daemon keeps running and starts on login.
  • Upgrades automatically with no action required.
For details about distributing and installing the standalone binary with fleet rollout tools like JAMF, Intune, Mosyle, Kandji, or Workspace ONE, see MDM in the HiveMind documentation.
The HiveMind daemon watches for coding-agent activity and sends session transcripts to the HiveMind service.

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2. Access the HiveMind dashboard

After the HiveMind service starts receiving information from your team, access the HiveMind dashboard to track, understand, and refine your team’s AI usage over time. From the HiveMind dashboard, your team can:
  • See sessions across agents: One daemon captures sessions from every supported agent, with no per-agent configuration.
  • Track spend and usage: View estimated cost over time, cost by model and team, token usage, and cost per merged pull request. Cost figures are estimates from published model pricing and session token counts, not billed amounts from your AI vendors.
  • Measure outcomes: Connect agent activity to pull requests, merge rates, and how much agent-written code survives.
  • Reuse past work: Use @hivemind inside Claude Code, Codex, or Cursor to search your team’s session history and bring relevant context into your current session.
  • Learn from history: Import existing sessions from local tools like Claude Code or Cursor to gain new insights from prior AI usage.
These screenshots show example pages in the HiveMind dashboard: a usage report, a leaderboard, and the detailed view of a session. Click a screenshot to view details.
HiveMind Usage dashboard with charts
HiveMind Leaderboard showing the top 15 users
HiveMind session details with insights

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Supported agents

HiveMind captures sessions from many coding agents, with no agent-specific configuration required. For example:
  • Claude Code
  • Codex
  • Cursor
  • Gemini CLI
  • GitHub Copilot CLI
  • OpenCode
  • Pi
For the full list, see hivemind.wandb.tools. With the daemon running, your session appears on the dashboard within around 30 seconds of using a supported agent.

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HiveMind and Weave

If you already use W&B Weave, it works together with HiveMind. They cover different stages and answer different questions.
  • Weave observes what your AI application does in production, tracking LLM and agent traces, evaluations, and quality.
  • HiveMind observes how your team builds software with AI coding agents, tracking sessions, spend, and productivity.

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Next steps

See the HiveMind documentation for full details about setup, permissions, the CLI reference, troubleshooting, and more.