What is happening to SDLC in the era of AI agents

▤ Summary

This article examines how AI agents are reshaping the software development lifecycle and pushing teams toward AI-native engineering workflows. It argues that traditional SDLC assumptions, tools, and metrics no longer capture how work gets done when AI handles more coding, review, and delivery tasks. The piece highlights the rise of SE 2.0 patterns, bounded autonomy, and new operating models for task management, code review, and DevOps governance. It also emphasizes that teams need stronger guardrails, observability, and outcome-based metrics to manage quality, risk, and productivity in AI-driven development. Overall, it frames AI adoption as a structural change in how software organizations build and ship products.

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