AI SRE: Reduce MTTR by 50% with Autonomous Incident Resolution

Incidents are still one of the biggest drains on engineering teams. On-call engineers spend more time investigating than fixing, RCAs get written after the fact if at all, and the same incidents keep recurring. The teams closing that gap aren't adding more process – they're letting AI agents handle the investigation while engineers stay in control of the decisions.

In this session, we'll show you how Port customers use agentic workflows to lower MTTR and move toward proactive remediation. We’ll share the patterns, walk through workflow configuration including integration with common tools in your stack – such as PagerDuty, DataDog, AWS – then build it live and hand you a customizable agentic workflow you can have running the same week.

What you'll walk away with:

• A clear model for where agents fit in your incident response process - and where humans should stay in the loop
• A working agentic workflow that responds to incidents, surfaces the right context, and suggests remediation automatically
• Patterns from engineering teams already running this in production
• A concrete path to autonomous incident remediation, with the interim steps that hold up in practice

Live build, from scratch, with Q&A at the end.