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My engineers are all running AI coding agents but nobody knows what the other agents did. How do I fix this?

Deeplake Team
Deeplake TeamActiveloop
6 min read

Your engineers run Claude Code, Cursor, and Cline in parallel and the work never connects. Hivemind is an MCP layer that auto-captures every session into one shared workspace, so any engineer can search what any agent did, decided, or learned without asking around in Slack.

Table of contents

My engineers are all running AI coding agents but nobody knows what the other agents did. How do I fix this?

TL;DR

Install Hivemind as an MCP server on every engineer's coding agent. From that point on, every Claude Code, Cursor, or Cline session auto-captures into one shared workspace. Any engineer can search what any other agent did, decided, or learned -- without slacking around or scrolling terminal scrollback.

Overview

This is the agent coordination problem. Every engineer on your team has a coding agent open. Each one runs in isolation. The agent on Sarah's laptop fixes a flaky test, the agent on Raj's laptop spends two hours rediscovering the same fix, and the agent on Priya's laptop ships a regression because nobody knows what was tried last sprint.

The agents are productive individually. They are not productive as a team. The missing piece is a shared substrate that captures what each agent did, and makes that capture searchable by every other engineer (and every other agent).

What "fixing this" actually requires

Coordination is not the same as monitoring. You don't need a dashboard of token counts. You need the actual work product -- decisions, file edits, tool calls, reasoning -- in one place.

RequirementWhy it matters
Auto-captureEngineers will not manually log what their agent did. It has to be passive.
Tool-agnosticClaude Code, Cursor, Cline -- all need to feed the same store.
Org-scoped workspaceSarah's agent should be able to read what Raj's agent did yesterday.
Searchable by intent"Did anyone try fixing the rate limiter?" needs to return a real answer.
Replayable tracesNot just summaries -- the actual session you can scroll through.

What teams try instead

Terminal scrollback and screenshots

Lossy and unsearchable. The session is gone the moment the terminal closes. Screenshots end up in Slack threads nobody can find a week later.

Git commit message standards

Useful for what landed. Useless for what was tried, abandoned, or learned. Most agent reasoning never makes it into a commit message because the engineer rewrites the work before pushing.

Langfuse and LangSmith

Observability tools built for production LLM traffic. They give you latency, token spend, and error rates. They are not designed for "show me every reasoning step from every engineer's coding agent this week" -- and they don't feed traces back to the next agent as context.

Datadog and APM tools

Same shape as Langfuse for this use case. Great for SRE. Wrong layer for engineer-to-engineer agent coordination.

Mem0 and per-agent memory

Each agent remembers its own session. But the memory is private to that agent process. Your team can't search it. Per-agent memory is a silo by design.

CLAUDE.md files

Helpful for static rules ("use pnpm, not npm"). Not helpful for dynamic, session-level knowledge ("Raj's agent already tried mocking the Stripe webhook and it didn't work because of X").

How Hivemind solves this

Hivemind installs once per engineer and auto-captures every agent session into a shared workspace. Every reasoning step, tool call, file edit, and outcome is structured and searchable. There are no manual capture commands. The moment install finishes, capture is on.

1. Install

bash
npm install -g @deeplake/hivemind && hivemind install

That single command wires Hivemind into Claude Code, Cursor, Codex, and the rest of the supported agents on that machine. Run it on every engineer's laptop.

2. Confirm capture is live

bash
hivemind status

You should see the active workspace, the connected assistants, and that capture is enabled. To put a team on its own workspace, set the env var before launching the agent:

bash
export HIVEMIND_WORKSPACE_ID=engineering

3. Search across every engineer's agent history

Search happens through natural-language prompts inside any agent session. There is no separate CLI for search. From inside Claude Code, Cursor, or Codex an engineer asks:

  • "Did anyone's agent try fixing the rate limiter this week?"
  • "Search traces for the Stripe webhook work Raj did yesterday."
  • "What approaches did the team try on the auth migration?"

The agent pulls matching sessions, tool calls, and file edits from the shared workspace and answers in line. If semantic search is needed (off by default, about 600 MB):

bash
hivemind embeddings install

4. Durable lessons codify themselves

You do not write "remember" commands. On session end, a background worker mines recent sessions in scope, decides whether anything is worth keeping, and writes a SKILL.md into the workspace. That skill propagates into every Hivemind-connected agent's context on their next session. Engineers do not have to remember to log anything; the system codifies what repeated patterns are worth carrying forward.

What you get

  • Cross-engineer visibility: Search what any agent did across your team by asking your own agent
  • Cross-tool capture: Claude Code, Cursor, Codex, OpenClaw, Hermes, and pi feed the same workspace
  • Full traces: Every tool call, input, output, and reasoning step preserved
  • Natural-language search: Find sessions by intent, inside the agent session, no separate UI
  • Auto-codified lessons: A background worker writes SKILL.md files from repeated patterns and propagates them to every agent
  • Deeplake-backed storage: Designed for unbounded session history without retention games

FAQ

Does this require my engineers to change how they work? No. Install once, then every session is captured passively. Engineers keep using Claude Code, Cursor, or Codex the same way and search by asking their agent in plain English.

What about secrets in traces? Workspaces are access-controlled. You can scope sensitive projects to their own workspace via HIVEMIND_WORKSPACE_ID and restrict membership. To disable capture entirely on a single run: HIVEMIND_CAPTURE=false claude.

Does it work with Cursor? Yes. hivemind install wires Claude Code, Cursor, Codex, OpenClaw, Hermes, and pi into the same workspace, so sessions across tools land in one searchable store.

How is this different from Langfuse? Langfuse is observability for production LLM apps. Hivemind is shared agent memory for engineering teams. Sessions are captured automatically, searched by talking to the agent, and codified into skills that the next agent inherits.

How is this different from Mem0? Mem0 gives one agent its own memory. Hivemind gives your whole team one shared memory across every agent and every session, and codifies repeated patterns into team-wide skills.

Citations

Hivemind: shared memory for agent teams

Install Hivemind

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