In the early 2010s, software architecture underwent a fundamental shift as organizations moved from monoliths to microservices - unlocking not only technical advantages like reduced blast radius and more efficient scaling, but also enabling new organizational models built around small, autonomous teams.
Today, we’re witnessing a similar transformation in the world of AI agents, only at a dramatically accelerated pace. The initial push toward ever-larger, general-purpose agents is giving way to a more modular approach: smaller, narrowly scoped “micro-agents” that deliver better performance, flexibility, and composability.
But as with microservices, this shift introduces a new challenge: coordination. This is an orchestration problem.
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Principal Developer Advocate
Temporal Technologies
Cornelia has spent a career at the forefront of technological innovation, starting with image processing algorithm development, moving to web-centric computing in the late 1990s, and then more than a decade working in cloud-native software and DevOps platforms. As Senior Staff Developer Advocate for Temporal, she is now helping to drive the expansion of the “durable execution” distributed systems paradigm.
She is the author of Cloud Native Patterns: Designing change tolerant software.
Staff Product Manager, AI
Temporal Technologies
Ethan Ruhe is the AI Product Lead at Temporal, where he helps some of the world's most talented developers - including those at OpenAI, Scale AI, and Replit - orchestrate and scale their AI agent workflows. Prior to Temporal, Ethan was a founder and has held product roles at a number of high-growth startups. He earned his MBA with a focus in Statistics from The Wharton School and completed graduate computer science work at Georgia Tech, focused on Machine Learning.
