Spec-Driven Evolution: How AI Agents Are Rewriting the OpenStack/K8s Pla...
Talkat KubeCon + CloudNativeCon + OpenInfra Summit + PyTorch Conference China 2026 · 2026-09-07..09-09·
summary
Spec-driven workflow uses three AI agents (requirements, implementation analysis, runtime evidence) that read specs, code and live clusters to produce reviewable artifacts for OpenStack Tacker and Kubernetes operators. Agents (using CloudSonic 5) find concrete defects: a startup crash from invalid comp.run args and HA race conditions that allow dual-active roles, reporting 4 high and 3 medium severities with line-level fixes and generated unit tests. A laptop demo creates Grafana/Prometheus dashboards, a leader–conductor refactor that reduces CPU and supports thousands of VNFs toward 99.999% SLA, cutting a 20–30 month validation path.
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chapters (10)
- 0:00AI agents in Telco engineering
- 3:59AI agents outperform prompting
- 7:16AI agent workflow and architecture
- 11:32Shared artifacts and collaboration
- 12:34AI code review for Kubernetes operator
- 17:28AI agents as quality reviewers
- 17:50Tucker project and AI scaling
- 24:41Live demo: AI-driven conductor refactoring
- 27:11Key takeaways and future
- 29:17Closing and discussion
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