Show HN: RunbookAI – Stop scrolling dashboards at 3 a.m., let AI investigate (github.com)

RunbookAI has launched a new tool aimed at enhancing the efficiency of on-call engineers during incident investigation, particularly for teams operating on AWS and Kubernetes. This innovative platform enables rapid hypothesis-driven investigations, helping to quickly identify root causes of incidents while maintaining auditability through structured workflows. By integrating features like approval-gated remediation and operational memory, RunbookAI allows engineers to move from alert to understanding significantly faster, ultimately reducing downtime and improving operational resilience. The tool is built with SRE best practices in mind, utilizing a combination of runbook-guided context and advanced querying capabilities to streamline the investigative process. Users can interact with RunbookAI through straightforward command-line prompts, where the AI suggests hypotheses based on incident data and system metrics, ensuring that corrective actions are taken only after proper approval. With its integrations for incident management platforms like PagerDuty and OpsGenie, as well as contextual support from Claude Code, RunbookAI not only accelerates the triage process but also fosters continuous learning by capturing insights during each investigation, making it a significant advancement for AI/ML applications in operational settings.