Claude Code Team Collaboration: Multi-Agent Workflows & Knowledge Sharing
By Learnia AI Research Team
Claude Code Team Collaboration: Building Shared AI Workflows
Teams that effectively leverage Claude Code report significant productivity gains - but the key isn't individual mastery. It's organizational learning: capturing team conventions, sharing workflows, and orchestrating multiple AI agents for complex tasks. This guide shows you how to transform Claude Code from a personal tool into a team-wide force multiplier.
1. The Memory Hierarchy: CLAUDE.md as Organizational Knowledge
CLAUDE.md files aren't just configuration - they're your team's compounding memory system. Every mistake caught and documented becomes permanent knowledge that benefits everyone.
The Three-Level Memory Architecture
Memory Hierarchy:
- →Global -
~/.claude/CLAUDE.md(All projects) - →Project -
/project/CLAUDE.md(Team shared) - →Local -
/project/.claude/CLAUDE.md(Personal prefs)
Priority: Local > Project > Global
The Minimum Viable CLAUDE.md
Most projects only need three things:
# Project Name
Brief one-sentence description of what this project does.
## Commands
- `pnpm dev` - Start development server
- `pnpm test` - Run tests
- `pnpm lint` - Check code style
That's it for most projects. Claude automatically detects:
- →Tech stack (from package.json, go.mod, Cargo.toml, etc.)
- →Directory structure (via exploration)
- →Existing conventions (from the code itself)
Add more only when needed - when Claude makes a mistake twice because of missing context, add that context.
2. Continuous Context Updates
Don't just react to errors - proactively document discoveries during development sessions.
What to Capture by Category
| Discovery Type | CLAUDE.md Section | Example |
|---|---|---|
| Implicit convention | ## Conventions | "Services return domain objects, never HTTP responses" |
| Non-obvious dependency | ## Architecture | "UserService depends on EmailService for signup flow" |
| Test trap | ## Gotchas | "E2E tests require Redis running on port 6380 (not default)" |
| Performance constraint | ## Constraints | "Batch API calls to max 50 items (external API limit)" |
| Design decision rationale | ## Decisions | "Chose Zod over Joi for runtime validation (tree-shakeable)" |
3. The .claude/ Folder Structure
The .claude/ folder is your project's Claude Code directory for memory, settings, and extensions.
.claude/
├── CLAUDE.md # Local instructions (gitignored)
├── settings.json # Hook configuration (team shared)
├── settings.local.json # Personal permissions (gitignored)
├── agents/ # Custom agent definitions
├── commands/ # Custom slash commands
├── hooks/ # Event-driven scripts
├── rules/ # Auto-loaded conventions
├── skills/ # Knowledge modules
└── plans/ # Saved plan files
4. Single Source of Truth Pattern
When using multiple AI tools (Claude Code, CodeRabbit, SonarQube, Copilot...), they can conflict if each has different conventions.
Solution: One source of truth for all tools:
/docs/conventions/
├── coding-standards.md # Style, naming, patterns
├── architecture.md # System design decisions
├── testing.md # Test conventions
└── anti-patterns.md # What to avoid
Then reference from everywhere:
# In CLAUDE.md
@docs/conventions/coding-standards.md
@docs/conventions/architecture.md
# In .coderabbit.yml
knowledge_base:
code_guidelines:
filePatterns:
- "docs/conventions/*.md"
5. Custom Agents for Team Workflows
Agents are specialized sub-processes that Claude can delegate tasks to. They encapsulate expertise.
When to Create an Agent
Agent Template
Create agents in .claude/agents/:
---
name: code-reviewer
description: Use for code quality reviews, security audits, and performance analysis
model: sonnet
tools: Read, Grep, Glob
skills:
- security-guardian
---
# Code Reviewer
## Role Definition
You are a senior code reviewer with expertise in:
- Code quality and maintainability
- Security best practices (OWASP Top 10)
- Performance optimization
- Test coverage analysis
## Methodology
1. **Understand Context**: Read the code and understand its purpose
2. **Check Quality**: Evaluate readability, maintainability, DRY principles
3. **Security Scan**: Look for OWASP Top 10 vulnerabilities
4. **Performance Review**: Identify potential bottlenecks
5. **Provide Feedback**: Structured report with severity levels
Model Selection Guide
| Model | Best For | Speed | Cost |
|---|---|---|---|
haiku | Quick tasks, simple changes | Fast | Low |
sonnet | Most tasks (default) | Balanced | Medium |
opus | Complex reasoning, architecture | Slow | High |
6. Skills: Reusable Knowledge Modules
Skills are knowledge packages that agents can inherit - think of them as libraries of expertise.
Interactive Skill Builder
Create your own custom skill with this step-by-step wizard. Choose a skill type, configure its capabilities, and generate a ready-to-use SKILL.md file:
Why Skills?
Without skills:
Agent A: Has security knowledge (duplicated)
Agent B: Has security knowledge (duplicated)
Agent C: Has security knowledge (duplicated)
With skills:
security-guardian skill: Single source of security knowledge
Agent A: inherits security-guardian
Agent B: inherits security-guardian
Agent C: inherits security-guardian
Creating a Skill
Skills live in .claude/skills/{skill-name}/:
security-guardian/
├── SKILL.md # Main instructions
├── reference.md # Detailed documentation
├── checklists/
│ ├── owasp-top10.md
│ └── auth-security.md
└── examples/
├── secure-auth.ts
└── insecure-auth.ts
SKILL.md:
---
name: security-guardian
description: Expert guidance for security problems
allowed-tools: Read, Grep, Bash
---
# Security Guardian
You are a security expert specializing in:
- OWASP Top 10 vulnerabilities
- Authentication and authorization
- Input validation and sanitization
- Secure coding practices
## When Invoked
- Review code for security issues
- Audit authentication flows
- Check for injection vulnerabilities
7. Multi-Agent Orchestration Patterns
For complex tasks, orchestrate multiple agents working together.
Interactive Workflow Builder
Use this drag-and-drop tool to design multi-tool workflows. Combine research tools like Perplexity, coding assistants like Claude Code, and deployment platforms into seamless pipelines:
The Split-Role Analysis Pattern
Launch specialized agents with different perspectives:
Example prompt:
Analyze this PR with the following perspectives:
1. Senior Engineer: Architecture and patterns
2. Security Expert: Vulnerabilities and risks
3. Performance Engineer: Bottlenecks and optimizations
4. Junior Dev: Readability and documentation
5. QA Engineer: Testability and edge cases
The 7-Parallel-Task Method
For complete features, launch 7 specialized sub-agents in parallel:
- →Components → Create React components
- →Styles → Generate Tailwind styles
- →Tests → Write unit tests
- →Types → Define TypeScript types
- →Hooks → Create custom hooks
- →Integration → Connect with API/state
- →Config → Update configurations
All run in parallel, then final consolidation
8. Cost-Optimized Team Workflows
Use model orchestration for cost efficiency:
Orchestration Pattern:
- →Orchestrator: Sonnet 4.5 (plans and coordinates)
- →Workers: 3x Haiku (execute parallel tasks)
- →Validator: Sonnet 4.5 (reviews and consolidates)
Cost: 2-2.5x cheaper than using Opus everywhere
Cost Optimization Example:
Scenario: Refactoring 100 files
❌ Naive approach:
- Opus for everything
- Cost: ~$50-100
- Time: 2-3h
✅ Optimized approach:
- Sonnet: Analysis and plan (1x)
- Haiku: Parallel workers (100x)
- Sonnet: Final validation (1x)
- Cost: ~$5-15
- Time: 1h (parallelized)
9. TeammateTool: Experimental Multi-Agent
For truly complex orchestration, Claude Code includes an experimental TeammateTool for persistent multi-agent communication:
| Operation | Purpose |
|---|---|
spawnTeam | Create a named team of agents |
discoverTeams | List available teams |
requestJoin | Agent requests to join a team |
approveJoin | Team leader approves join requests |
| Messaging | JSON-based inter-agent communication |
Patterns:
- →Parallel Specialists: Leader spawns 3 teammates → Each reviews different aspect → Teammates work concurrently → Report back → Leader synthesizes
- →Swarm Pattern: Leader creates shared task queue → Teammates self-organize and claim tasks → Independent execution → Async updates
10. Team Onboarding Best Practices
Progressive CLAUDE.md Growth
Week 1: 5 rules → 5 mistakes prevented
Week 4: 20 rules → 20 mistakes prevented
Month 3: 50 rules → 50 mistakes prevented + faster onboarding
Multi-Machine Sync
Option 1: Git + symlinks
# Machine 1 (setup)
cd ~/claude-config-backup
git add agents/ commands/ hooks/ skills/
git commit -m "Add latest configs"
git push
# Machine 2 (sync)
cd ~/claude-config-backup
git pull
# Symlinks automatically sync ~/.claude/ directories
Option 2: Cloud storage symlinks
# Both machines - move ~/.claude/ to cloud storage
mv ~/.claude ~/Dropbox/claude-config
ln -s ~/Dropbox/claude-config ~/.claude
# Changes sync automatically via Dropbox
Summary: Team Collaboration Keys
- →CLAUDE.md as Organizational Memory: Capture mistakes once, prevent them forever
- →Three-Level Hierarchy: Global → Project → Local with clear precedence
- →Single Source of Truth: Align all AI tools to the same conventions
- →Agents for Expertise: Encapsulate domain knowledge in reusable agents
- →Skills for Sharing: Create knowledge modules that multiple agents inherit
- →Multi-Agent Patterns: Split-role analysis and parallel workers for complex tasks
- →Cost Optimization: Use model orchestration (Sonnet orchestrator + Haiku workers)
- →Continuous Updates: Capture discoveries during every session
Continue Your Learning
Ready to master team collaboration? Our Team Workflows Training Module provides hands-on exercises for building shared CLAUDE.md files, creating team agents, and orchestrating multi-agent workflows.
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FAQ
How do teams share Claude Code configurations?+
Commit CLAUDE.md, .claude/skills/, and .mcp.json to your repository. Every team member gets the same context, skills, and integrations automatically.
Can multiple developers use Claude Code simultaneously?+
Yes, use Git worktrees to create separate working directories. Each developer can run independent Claude sessions on different branches without conflicts.
How do we maintain consistent coding standards with AI?+
Define standards in CLAUDE.md and create enforcement skills. Claude will follow your conventions in all generated code. Use hooks for automatic linting and formatting.
Can Claude Code help with code reviews?+
Yes, create a code-reviewer skill that checks for security issues, performance problems, and style violations. Claude can review PRs and suggest improvements automatically.