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Building Your Agent Team
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Building Your Agent Team

A Practitioner's Guide to Multi-Agent AI Systems

Build a team of specialized AI agents that work together, instead of one general chatbot.

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  • By Sahar Carmel
  • 15 chapters
  • Updated Nov 1, 2026
  • 288 readers

What’s inside

  • Foundation
  • The 1% Opportunity
  • Starting Small -- Your First Proactive Agent
  • The Migration Path -- From One Agent to Many
  • Agent Architecture Deep Dive
  • The Communication Layer

What is Building Your Agent Team?

Build a team of specialized AI agents that work together, instead of one general chatbot. It walks through a real production system of seven Claude-based agents running in Discord, each with its own role, memory and knowledge base. You will learn to write agent definition files, route messages between agents, replace RAG with a book-based knowledge system, give agents persistent memory, and set up security scoping and a deployment pipeline, all drawn from working code in a live product.

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markdown · Listed Apr 11, 2026

  • agents
  • best-practices
  • anthropic
  • nano-claw

From the first page

This book distills the experience of building a production multi-agent AI platform from scratch. Seven specialized AI agents, each with distinct roles, personalities, and domain expertise, working together through Discord channels. The architecture, the patterns, the mistakes, and the lessons are all here.

This book is designed for two audiences. Humans will find a practical guide to building their own agent teams, from the first scheduled agent to a full multi-agent system with memory, knowledge, and inter-agent communication. AI agents will find a structured reference with clear headings, cross-references, and navigable chapters they can consult when building or extending agent systems.

No prior experience with multi-agent systems is required. Familiarity with TypeScript, Docker, and Claude (or similar LLMs) is helpful but not essential.

Preview · 2,000 of 134,811 characters

Nested Sub-Agents in OrchestKit: Adopting CC 2.1.172–2.1.173
Inside Claude Code: The Architecture
The Complete Guide to Building Skills for Claude
EDPB Guidelines for GDPR Compliance

Contents

  1. 01Building Your Agent Teamp.1
    1. A Practitioner's Guide to Multi-Agent AI Systemsp.1
    2. Table of Contentsp.1
  2. 02Foundationp.2
  3. 03The 1% Opportunityp.3
    1. Beyond Chatbots and Copilotsp.3
    2. What This Book Teachesp.3
    3. Written for Both Audiencesp.3
  4. 04Starting Small -- Your First Proactive Agentp.4
    1. The Problemp.4
    2. First Agent: Product Intelp.4
    3. Evolution: Email Outreachp.4
    4. The Email Infrastructure Hackp.4
    5. The "Latent Demand" Conceptp.4
    6. Practical Takeawaysp.4
  5. 05The Migration Path -- From One Agent to Manyp.5
    1. Phase 1: Claude Code with Loopp.5
    2. Phase 2: Larger Framework + Telegramp.5
    3. Phase 3: Minimal Framework + Discordp.5
    4. Why Framework Choice Mattersp.5
    5. The "Agent as a Person" Philosophyp.5
    6. The Agent Shaming Storyp.5
  6. 06Agent Architecture Deep Divep.6
    1. The Template vs. Instance Patternp.6
    2. Agent Definition Filesp.6
    3. Shared Context: COMPANY.mdp.6
    4. System Prompt Assemblyp.6
    5. Message Flow Architecturep.6
    6. The GroupQueue Patternp.6
    7. Registration and Statep.6
    8. Execution Modesp.6
    9. +2 more sections
  7. 07The Communication Layerp.7
    1. The Office Metaphorp.7
    2. Channel Routing Architecturep.7
    3. The Channel Registry Patternp.7
    4. Webhook Identity for Agentsp.7
    5. Message Filtering and Translationp.7
    6. The Visibility Principlep.7
    7. Mobile-First Agent Interactionp.7
    8. Key Takeawaysp.7
    9. +1 more section
  8. 08Knowledge System -- Books Over RAGp.8
    1. The Problem with RAGp.8
    2. Books as Agent Intelligencep.8
    3. How Agentic Book Reading Worksp.8
    4. Why This Beats RAGp.8
    5. Books for Different Purposesp.8
    6. Auto-Updating Booksp.8
    7. Practical Implementationp.8
    8. Key Takeawaysp.8
    9. +1 more section
See all 15 parts
  1. 09Memory and Dreamsp.9
    1. The Memory Architecturep.9
    2. Four Memory Typesp.9
    3. Memory Loading and Truncationp.9
    4. Post-Conversation Memory Extractionp.9
    5. The Dream Processp.9
    6. Why No Vector Databasep.9
    7. The Key Insightp.9
    8. Key Takeawaysp.9
    9. +1 more section
  2. 10Inter-Agent Communicationp.10
    1. Message Types Between Agentsp.10
    2. Policy Enforcementp.10
    3. Preventing Chaosp.10
    4. The Delivery Flowp.10
    5. Domain Separation Through Shared Contextp.10
    6. Agent Discoveryp.10
    7. Channel Mapp.10
    8. The Visibility Principle, Againp.10
    9. +2 more sections
  3. 11Operationsp.11
  4. 12The Development Workflowp.12
    1. WorkTree for Parallel Developmentp.12
    2. The PR Pipelinep.12
    3. The Session Separation Testing Principlep.12
    4. Testing Philosophyp.12
    5. Key Takeawaysp.12
    6. Cross-Referencesp.12
  5. 13Security and Permissionsp.13
    1. The Scoping Principlep.13
    2. Container Isolationp.13
    3. The Credential Proxyp.13
    4. Approval Rulesp.13
    5. The Communication Platform as Security Layerp.13
    6. Prompt Injection Considerationsp.13
    7. The Permission Spectrump.13
    8. Key Takeawaysp.13
    9. +1 more section
  6. 14Deployment and Operationsp.14
    1. Local Developmentp.14
    2. Cloud Deploymentp.14
    3. Database Strategyp.14
    4. Cost Optimizationp.14
    5. Scaling Patternsp.14
    6. Operational Toolingp.14
    7. Monitoring Without Overheadp.14
    8. Key Takeawaysp.14
    9. +1 more section
  7. 15Giving Agents Soulp.15
    1. The Three Layers of Agent Qualityp.15
    2. Layer 1: Long-Term Knowledge (Books)p.15
    3. Layer 2: Memory (Accumulated Feedback)p.15
    4. Layer 3: Examples (Reference Materials)p.15
    5. Books as Mentorsp.15
    6. The Anti-Patternsp.15
    7. The Proactive versus Reactive Tensionp.15
    8. The Philosophyp.15
    9. +2 more sections