Team Brain: A Shared Memory Plugin for Claude Code That Stores Team Knowledge in Git

Team Brain is a Claude Code plugin that addresses the problem of AI coding assistants starting from zero each session by creating a shared memory system stored in Git. Instead of each team member's Claude having no knowledge of previous debugging sessions, decisions, or conventions, Team Brain stores this information in a .team-brain/ folder within your repository.
How It Works
Team members record knowledge as they work using specific commands:
/team-brain learn stripe webhooks retry 3x with exponential backoff/team-brain decide use REST over GraphQL for public API/team-brain convention always use async/await never .then()
Each entry saves as an individual markdown file in the .team-brain/ directory. The plugin automatically generates a BRAIN.md file that's capped at 180 lines, based on the observation that Claude applies instructions at 92% accuracy under 200 lines but drops to 71% above 400 lines.
Setup and Features
Installation requires cloning the repository to the Claude plugins directory:
git clone https://github.com/Manavarya09/team-brain.git ~/.claude/plugins/team-brainThen run /team-brain init in your project. On every session start, a hook checks for changes and loads the team brain automatically without manual configuration.
The cross-tool functionality generates .cursorrules for Cursor users and AGENTS.md for Copilot, ensuring team conventions apply regardless of which AI coding tool team members use.
The /team-brain onboard command reads everything and generates an onboarding document. According to the source, this allowed a new developer to become productive in 20 minutes instead of requiring a 2-hour walkthrough.
Technical Implementation
The system uses only files in Git with no servers, cloud services, or accounts required. Individual markdown files enable clean merging—two people can add knowledge on different branches without conflicts. This approach makes team knowledge persistent, version-controlled, and automatically available to all team members' Claude instances.
📖 Read the full source: r/ClaudeAI
👀 See Also

Phantom: A Persistent AI Agent Built with Claude's Agent SDK
Phantom is an open-source Bun/TypeScript process that wraps Claude's Agent SDK (Opus 4.6) with persistent vector memory, a self-evolution engine, and an MCP server interface. It runs continuously on its own VM or Docker Compose and communicates via Slack.
Hoplite (YC S26) Launches Cloud Deployment for Coding Agents with QA Previews
Hoplite lets you deploy coding agents in the cloud, porting over your local setup including sessions, memories, and MCP servers. It includes a custom harness and focuses on onboarding and previews for QA.

Code retrieval for AI agents: Why vector embeddings fail and per-file LLM graphs win
After a year of building a code indexing system, the team behind Bytebell found that vector embeddings on code chunks and Tree-sitter ASTs both fell short, while per-file LLM summaries stored in a Neo4j graph with semantic fulltext search significantly improved retrieval precision.

Multi-Agent Debate Approach Improves LLM Reasoning Quality
A developer experimented with a multi-agent debate approach using CyrcloAI, where different AI agents take on roles like analyst, critic, and synthesizer to critique each other's responses before producing a final answer, resulting in more structured and deliberate outputs.