DevOps Engineer Explains How AI Speeds Up Troubleshooting Without Replacing Expertise

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A DevOps engineer describes how AI tools have changed their workflow not by automating decisions, but by shortening the time between detecting a problem and forming a testable hypothesis. The engineer uses ChatGPT for communication and reasoning, Claude for coding and Kubernetes tasks, and an AWS DevOps Agent for infrastructure investigation. One practical use case involved using ChatGPT to polish a Slack summary after independently completing an EKS cost analysis, keeping the actual technical investigation human-led. The engineer also uses AI as a sounding board to surface overlooked factors before making infrastructure changes, such as instance downsizing. A key principle throughout is knowing when to trust AI output and being careful never to paste sensitive configuration data into any of these tools.

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