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DevOps in 2026 has become diluted, often reduced to automation tools and pipelines rather than its original purpose of closing feedback loops between intent and outcome. Patrick Debois, who coined the term, argues that AI and platform engineering recreate the same tensions DevOps addressed: shifting responsibility, maintaining visibility, and ensuring shared understanding. AI transforms developers from producers to reviewers, introducing non-determinism that makes DevOps principles more critical. Platform engineering, when done right, continues DevOps ideals by creating golden paths that enable teams to focus on outcomes. The core challenge remains unchanged: aligning people, process, and technology to deliver reliably at scale, with engineering culture as the foundation that determines whether automation and AI actually work.

Let’s Look at DevOps

Posts around deployment tools and methods