Article: From Microservices to Agents: the Next Evolution of Distributed Systems

Agentic AI systems shift distributed systems design from orchestrating services to orchestrating decisions made at runtime. Unlike microservices, agentic systems introduce non-deterministic execution paths driven by context, reasoning, and tool selection. Decision quality becomes a first-class reliability concern alongside latency, availability, and throughput. Production failure modes often manifest as silent degradation in reasoning quality rather than explicit system errors. Effective agentic architectures require bounded autonomy, evaluation loops, and hybrid deterministic fallback systems. This article is part of the "Agentic AI Architecture" article series. In this series, we try to establish agentic AI architecture as a new type of software architecture that will likely dominate the industry for years to come. The articles, written by industry experts, cover various elements and aspects of agentic AI architecture. We aim to present the latest trends and developments shaping the new type of architecture as it enters the mainstream. Over the past decade, microservices have reshaped how large-scale software systems are designed and operated. They enabled teams to decompose monoliths into independently deployable services, scale ownership boundaries, and evolve systems incrementally. For many organizations, microservices became the dominant model for building distributed systems at scale. At their core, microservices solved a fundamental problem: how…