Enterprise Architecture · AI Governance
Agentic
Agentic
Orchestration
From Agent Pilots to Enterprise Production
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From Agent Pilots to Enterprise Production
Request Early Access
"Building an impressive AI agent demo is easy. Running one in production — reliably, at scale, with governance — is where most enterprises get stuck."
Most enterprises are discovering this the hard way. Early pilots look promising. Then agents start making inconsistent decisions, failing silently, or taking actions that are hard to explain — let alone audit.
Drawing on production deployments across banking, telecommunications, healthcare, and beyond, this book bridges the gap between what AI agents can do in theory and what it takes to run them reliably in the real world.
Reasoning without orchestration is expensive chaos at best. This book shows you the way out.
How to orchestrate agents on a proven foundation, combining deterministic control with dynamic reasoning in a single model. BPMN meets LLMs — with production-ready patterns.
Calibrating agent authority to risk, with progressive commitment that escalates governance as stakes grow. Build AI systems your organization can actually trust.
Testing, analytics, instance operations, and evolution: the operational framework for production confidence. What it takes to run agents reliably, not just demo them.
Scaling from one process to hundreds with shared integration, governance, and observability. From pilot to enterprise-wide deployment.
What production actually looks like: VodafoneThree, NORD/LB, Goldman Sachs, and a global investment bank. Patterns from organizations that have shipped.
Where orchestration is headed: platforms that discover, design, and improve their own processes. The frontier of agentic systems.
Integration patterns, governance, and how agentic systems fit your existing IT landscape. The architectural decisions that determine whether agents scale or collapse.
Testability, observability, versioning, and the gap between demo and production. What your team needs to know before going live.
Team topologies, governance models, and scaling without things falling apart. The organizational side of deploying AI agents at enterprise scale.
"Agents are probabilistic by nature. Your governance model needs to account for that — not fight it."
"The deterministic/agentic split isn't a fixed architecture decision. It's something you actively manage and refine over time."
"Reasoning without orchestration is just expensive chaos."
This book is in active development. We're sharing early access copies with architects, engineers, and technology leaders who are working on these problems in production. If that's you, we'd like to hear from you.
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