How SRE Teams Can Build Trustworthy AI Agents With Safe Failure Controls

Site Reliability Engineering is increasingly incorporating agentic AI to assist with alert triage, root cause analysis, and incident mitigation, but establishing trust in these systems remains a core challenge. Experts argue that trust in SRE AI agents must be engineered through grounded telemetry, explicit safety boundaries, progressive autonomy, auditability, and continuous real-world evaluation. A key architectural principle separates the AI's reasoning layer from its actuation layer, ensuring that a deterministic safety mechanism validates permissions, assesses risk, and simulates actions before any change is executed in production. Human approval is required for high-risk or low-confidence actions, while the system monitors post-action outcomes and triggers fallbacks if needed. Google's experience with AI in SRE underscores the importance of strict guardrails and least-privilege access to reduce blast radius and maintain operational control.