The Agentic Systems Series
Welcome to the complete guide for building AI coding assistants that actually work in production. This comprehensive three-book series takes you from fundamental concepts to implementing enterprise-ready collaborative systems.
About This Series
Ever wondered how modern AI coding assistants actually work? Beyond the prompts and demos, there's a rich ecosystem of patterns, architectures, and engineering decisions that make these systems effective.
This series reveals those patterns. It's the missing documentation—a practical engineering guide based on real production systems, including deep analysis of Amp (the collaborative platform), Claude Code (Anthropic's local CLI), and open-source implementations like anon-kode.
The Three Books
Book 1: Building an Agentic System
The Foundation
A practical deep dive into building your first AI coding agent. This book analyzes real implementations to extract core patterns:
- Core Architecture - Reactive UI with Ink/Yoga, streaming responses, and state management
- Tool Systems - Extensible architecture for file operations, code execution, and external integrations
- Permission Systems - Security models that balance safety with productivity
- Parallel Execution - Concurrent operations without race conditions
- Command Systems - Slash commands, contextual help, and user configuration
- Implementation Patterns - Lessons from Amp and Claude Code architectures
Perfect for engineers ready to build beyond simple chatbots into production-grade coding assistants.
Book 2: Amping Up an Agentic System
From Local to Collaborative
Transforms single-user agents into enterprise-ready collaborative platforms. Based on extensive analysis of production systems:
- Scalable Architecture - Conversation management, state synchronization, and performance at scale
- Authentication & Identity - OAuth flows, credential management, and multi-environment support
- Collaboration Patterns - Real-time sharing, team workflows, and concurrent editing strategies
- Enterprise Features - SSO integration, usage analytics, and compliance frameworks
- Advanced Orchestration - Multi-agent coordination, adaptive resource management, and cost optimization
- Production Strategies - Deployment patterns, migration frameworks, and real-world case studies
Essential reading for teams scaling AI assistants from prototype to production collaborative environments.
Book 3: Contextualizing an Agentic System
Advanced Tools and Context
Deep dive into advanced tool systems and context management for agentic systems. This book covers:
- Tool System Architecture - Extensible frameworks for adding new capabilities
- Command System Design - Slash commands, contextual help, and configuration
- Context Management - Understanding and maintaining conversational context
- Implementation Deep Dives - Real-world tool system implementations and patterns
Perfect for engineers building sophisticated agent capabilities and context-aware systems.
Who This Is For
- Systems Engineers building AI-powered development tools
- Platform Teams integrating AI assistants into existing workflows
- Technical Leaders evaluating architectures for coding assistants
- Researchers studying practical AI system implementation
- Anyone curious about how production AI coding tools actually work
Prerequisites
- Familiarity with system design concepts
- Basic understanding of AI/LLM integration
- Experience with either TypeScript/Node.js or similar backend technologies
- Understanding of terminal/CLI applications (helpful but not required)
What's Inside
This series provides:
- Architectural Patterns - Proven designs from production AI coding assistants
- Implementation Strategies - Practical approaches to common challenges
- Decision Frameworks - When to use different patterns and trade-offs
- Code Examples - Illustrative implementations (generalized for broad applicability)
- Case Studies - Real-world deployment scenarios and lessons learned
The content is based on extensive analysis of production systems, with patterns extracted and generalized for your own implementations.
About the Author
Hi! I'm Gerred. I'm a systems engineer with deep experience in AI and infrastructure at global scale. My background includes:
- Early work on CNCF projects and Kubernetes ecosystem
- Creator of KUDO (Kubernetes Universal Declarative Operator)
- Deploying GPU infrastructure for AI/AR applications
- Building data systems at scale (Mesosphere → Kubernetes migrations)
- Early work on Platform One (DoD DevSecOps platform)
- Implementing AI systems in secure, regulated environments
- Currently developing specialized agent frameworks with reinforcement learning
I care deeply about building robust systems with excellent UX, from frontend interactions to infrastructure design.
Support This Work
I'm actively consulting in this space. If you need help with:
- Building verticalized agents for specific domains
- Production agent deployments and architecture
- Making AI systems work in real enterprise environments
Reach out by email or on X @devgerred.
If this work's valuable, you can support ongoing research through Ko-fi.
Ready to Start?
Choose your path based on where you are:
New to agentic systems? → Start with Book 1: Building an Agentic System
Ready for collaboration & scale? → Jump to Book 2: Amping Up an Agentic System
Want the big picture first? → System Architecture Overview
Let's build systems that actually work.