Stop fighting with fragile AI agent systems. Start building production-grade architectures that actually work.
Most developers building AI agent systems focus on prompts and models-but miss the critical foundation: architecture. The result? Systems that break in production, accumulate errors, and become unmaintainable.
Agentic AI Systems: Foundations, Patterns, and Architectures provides the systematic framework that's been missing. This book introduces the MUTTA architecture-a proven pattern for structuring AI agent services that are modular, maintainable, and reliable.
What You'll Learn This comprehensive guide takes you from fundamental concepts to production deployment:
Foundations & Architecture - The progression from simple prompts to autonomous agents-and when to use each
- How to structure agent systems as composable services with clear inputs and outputs
- The MUTTA pattern: Manager, Utilities, Tools, and Agents file organization
- Multi-agent coordination patterns: parallel, handoff, and systematic architectures
- The Rule of 20 and service depth constraints to prevent error accumulation
Data Quality & Error Prevention - Why "garbage in, garbage out" is critical for agent systems-and how to prevent it
- The embedding-based input alignment heuristic for minimizing errors
- Mathematical foundations of error propagation in sequential systems
- Recursive alignment techniques for multi-agent pipelines
Universal Reusable Patterns - RAG (Retrieval Augmented Generation): Overcome knowledge limitations and reduce hallucinations
- Navigator Pattern: Intelligently explore codebases, databases, and structured data
- Code Interpreter: Enable unlimited problem-solving through code execution
- Tool Selector: Manage thousands of tools without overwhelming context windows
Error Correction & Verification - Lazy Agent Check pattern for knowledge-based verification
- Overseer pattern for quality assurance and spot-checking
- Strategy selection based on action criticality (reversible vs. irreversible)
- Logical fault checking for mathematical proofs and reasoning tasks
Practical Applications - Complete case studies: chat service, academic researcher, marketing engine
- Templates and working code examples throughout
- How to encode MUTTA into coding agent rules (Cursor, GitHub Copilot)
- Best practices distilled from production systems
Who This Book Is For&
