AI Native Systems: Autonomous Evolution at Machine Speed
Tamar Eilam, Fabio Oliveira, Michael Factor
1. Introduction: The Bottleneck in System Evolution and AI Native Systems
Modern software systems, especially those that serve AI workloads, are extraordinarily complex and must evolve continuously under pressure from new models, new hardware, changing usage patterns, and shifting business objectives. These pressures drive constant change, both in configuration and in code. Yet, even with increasingly powerful AI tools, improvement of such systems remains fundamentally human-driven. Engineers inspect logs and metrics, diagnose problems, open tickets, draft and review pull requests, extend tests, and orchestrate deployments through fragmented workflows. AI assists at each step, but progress is mediated by people, one decision at a time.