Architecting Intelligence
Architecting Intelligence
Principles, Patterns, and Protocols for the Agentic Era
A work-in-progress book about the architecture of production multi-agent systems. From the author of Production-Ready AI Agents.
Status: Manuscript complete: 18 chapters, an epilogue and six appendices, now in private review.
Join the early-reader list →The Problem
The first generation of AI agents shipped on demos and optimism. The second generation needs engineering physics — deterministic boundaries around probabilistic systems, coordination protocols that survive real traffic, evaluation harnesses that catch failures before users do.
Most agentic frameworks teach you how to chain LLM calls. The manuscript examines what happens when those chains run in production and begin interacting with each other.
What's Inside
- Contracts and bounded agency — defining what agents may do and how they communicate intent
- Routing and stateful execution — choosing models, preserving state, and recovering work
- Evaluation, supervision, and security — containing probabilistic behavior in production
- Multi-agent coordination — designing systems in which agents interact without losing operational control
Who This Is For
This work is for engineers and technical leaders responsible for agent systems that must survive production traffic.
- Staff+ AI engineers building multi-agent systems that need to survive production traffic
- VPE/CTOs making architecture decisions about agentic infrastructure
- ML platform engineers building the evaluation and orchestration layer beneath agents
Chapter Overview
The book is organized in six parts.
Foundations
Stochastic behavior, agent contracts and the budgets that bound a system's work.
Control
Routing, stateful execution, human authority and recovery after interrupted work.
Context
Context engineering, memory, retrieval and structured knowledge.
Correction
Evaluation, observability, learning surfaces and safe changes to the system.
Containment
Tool design, untrusted inputs and scoped permissions for consequential actions.
Composition
Multi-agent choices and an end-to-end constructed reference system.
About the Author
Igor Bobriakov — author of Production-Ready AI Agents (2025), founder of ActiveWizards (10-year AI engineering studio, 50+ production deployments). I build the systems I write about.
This manuscript extends that production focus to systems in which agents coordinate, fail, recover, and scale.
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