International Workshop: Envisioning AI-Augmented Software Development Life Cycle

Cloud Intelligence, a.k.a. AIOps, leverages AI and machine learning to design, build, and operate complex cloud platforms and services at scale. The advent of Large Language Models (LLMs) offers unprecedented opportunities to accelerate and deepen AIOps capabilities. In this talk, I will present concrete, real-world examples of how LLMs are reshaping core AIOps tasks, including anomaly detection, incident triage, root-cause analysis, and outage summarization, by extracting and synthesizing knowledge from diverse data sources, producing clear, actionable narratives, and functioning as human–AI copilots that continually improve through feedback.

I will then share the key learnings gained from embedding LLMs into AIOps workflows and briefly talk about how these principles are starting to influence other phases of the software development lifecycle, such as design, implementation, testing, and deployment. I'll conclude my talk with a set of open questions for discussion regarding trust, safety, and the evolving role of engineers in an AI-augmented environment.