Aiops

Fighting AI with AI — Lawrence Jones, Incident

Fighting AI with AI — Lawrence Jones, Incident

Lawrence Jones from Incident.io explains why their team needed AI to debug their complex AI SRE product. He details three powerful patterns: a CLI for agents to manage large evaluation files, serializing debug UIs into downloadable file systems for agent-based tracing, and multi-agent pipelines for fleet-scale failure analysis.

Live from Think 2026: AI operating model, VC funding & CAIO evolution

Live from Think 2026: AI operating model, VC funding & CAIO evolution

Live from IBM Think 2026, experts discuss the maturation of enterprise AI, moving from siloed applications to integrated, end-to-end solutions. The panel explores the rising trust in AI for strategic decisions, the evolving role of the Chief AI Officer (CAIO), and the state of AI investment, arguing that the field is broadening to solve specific business problems.

Architecting Self-Healing Enterprise Operations: AI + DevSecOps | Akshay Mittal | SW Engineer | 4K|E

Architecting Self-Healing Enterprise Operations: AI + DevSecOps | Akshay Mittal | SW Engineer | 4K|E

Explore the shift from reactive to predictive DevSecOps with Akshay Mittal. This discussion covers how AI-Augmented DevSecOps and Agentic Workflows are creating self-healing systems, the critical role of Explainable AI (XAI), and a four-layer architecture for building scalable, enterprise-grade AI solutions.

Architecting Self-Healing Enterprise Operations: AI + DevSecOps | Akshay Mittal  | SW Engineer | 4K

Architecting Self-Healing Enterprise Operations: AI + DevSecOps | Akshay Mittal | SW Engineer | 4K

Akshay Mittal discusses the evolution of enterprise AI, focusing on the crucial shift from reactive to predictive security through AI-augmented DevSecOps. He explores how to productionize agentic AI workflows using AIOps and Kubernetes, and emphasizes the non-negotiable need for explainable AI (XAI) in critical systems.

Enterprise AI Operations: The Missing Piece

Enterprise AI Operations: The Missing Piece

Rani Radhakrishnan, Principal at PwC, discusses the convergence of MLOps and IT operations, the practicalities of deploying AI agents, and the strategic considerations for scaling and sustaining AI initiatives in the enterprise. The conversation covers the shift from experimentation to ROI, the importance of human-in-the-loop processes, and the evolving skillsets required for future-ready IT.

AI, AIOps & Agentic AI in Data Storage Observability

AI, AIOps & Agentic AI in Data Storage Observability

Prabira Acharya explains that managing data storage without observability is like driving a car without a dashboard. The talk outlines the seven pillars of storage observability, the critical role of AI in analyzing vast amounts of data for anomaly detection and predictive analytics, and the evolution toward agentic AIOps for creating self-healing and self-managing storage infrastructures.