Agentic Mesh

Foreword

We find ourselves at an unusual moment in the evolution of artificial intelligence. The excitement is real, the investments are enormous, and the technical breakthroughs are astonishing. Yet inside most companies, the story is quieter and more complicated. Many AI initiatives remain stuck in what people jokingly call “proof-of-concept (or POC) purgatory.” These initiatives look impressive in a demo, maybe even inspiring, but they rarely make it into the production systems that run the business. Teams are experimenting, executives are searching for return on investment, and somewhere between those two realities the work tends to stall.

This book arrives at exactly the right time. It shines a light on the gap between early promise and operational reality. And it answers a question that almost every enterprise is wrestling with: “What does it actually take to run agents in the real world at scale?”

I first crossed paths with Eric through an article he wrote comparing several agentic frameworks. The industry had been drowning in surface-level feature lists, but his work was different. He approached the problem like a scientist. Instead of asking what features a framework offered, he asked whether it could be trusted to operate inside an enterprise. He evaluated reliability, traceability, observability, and explainability. He proposed a grading system that held each framework to the standards that real production environments demand. I contacted him as soon as I finished reading ...