SigNoz argues AI is deskilling SREs by automating routine cognitive tasks—alert grouping, runbook execution, log anomaly detection, and auto-remediation for known failures—leaving humans only with novel Tier 3 incidents. Citing Lisanne Bainbridge's 1983 "Ironies of Automation" paper, the article explains that as automation handles 95% of work, operators lose practice for the critical 5%, degrading expertise without awareness. Research supports this: endoscopists using AI saw unassisted polyp detection drop from 28% to 22%, and pilots relying on autopilot suffered measurable situational awareness loss, prompting FAA manual-flying mandates. SREs now stop reading raw logs, forming hypotheses, or building mental architecture models because AI summarizes, suggests root causes, and maps dependencies. This creates a vicious cycle: degraded skills increase AI reliance, further eroding capability. "Never-skilling" threatens juniors who never develop foundational intuition. Proposed mitigations include deliberate inefficiency—mandating human handling of automatable incidents—and designing human-in-the-loop systems that maintain cognitive engagement rather than passive supervision. SigNoz builds AI assistants that keep humans in control, leveraging their observability data layer for context-aware capabilities, aiming to supercharge SREs for the decisive 5% rather than replace them.