Agentic AI and AI SRE is everywhere in demos; but production-grade, self-healing operations are rare, because an agent can only remediate what your systems let it understand. This talk argues that reliable self-healing starts at design time, with AI-native engineering: build applications that emit the right signals (meaningful SLIs, structured events, rich context) so AI agents can detect, diagnose, and safely remediate issues on their own. Drawing on real-world experience delivering production systems in complex, regulated environments, we’ll cover: How to instrument for autonomy rather than dashboards, How to keep agents inside guardrails with auditability and human oversight built in from day one How self-healing translates into measurable outcomes: less toil, lower operational cost, and higher reliability. Attendees will leave with a practical approach to designing signal-rich applications and introducing safe, production-grade AI-driven self-healing into their own platforms.
Luca Lanziani is Head of DevOps and Platform Engineering at Nearform, where he helps engineering teams use AI in development in ways that actually improve delivery; not just how fast code gets written. His work sits at the intersection of AI Engineering, Platform Engineering, and software delivery, with a focus on the full path from intent to production: specs, agent workflows, review, testing, deployment, and clear ownership once software is live. Luca builds his AI Engineering work on a deep platform and DevOps background: workflows, review systems, automation, and accountability, so AI-assisted development holds up in real organizations, not just demos. Deepak is the Global Head of Consulting at Nearform. He’s a technology transformation leader who specialises in delivering large-scale platforms and solutions across data, AI, cloud and modern engineering practices. He’s helped deliver complex change at enterprise scale for some of the world's largest brands, lately with key focus on AI Native Engineering and AI SRE.
