The traditional software development lifecycle is collapsing as AI agents transform how code gets built. Instead of discrete sequential stages, engineers now work with AI coding agents that handle everything from implementation to testing in one continuous flow. The old model with separate tools for requirements, design, implementation, testing, and deployment is becoming obsolete.

Engineers who started their careers after AI coding tools emerged don't recognize the traditional SDLC at all. They skip sprint planning, story points, and lengthy code reviews entirely. Instead of following rigid workflows, they simply describe what they want, review the AI-generated code, iterate, and ship. This isn't about moving faster through the same process—it's about eliminating the process itself.

Every stage of the traditional lifecycle is being reimagined. Requirements gathering becomes fluid iteration rather than upfront specification. System design shifts from pre-planning to real-time collaboration with AI. Testing happens simultaneously with code generation. Code review workflows are being replaced by automated verification and agent-to-agent review. Deployment becomes continuous and decoupled from release. The result is a fundamental shift from human-managed pipelines to AI-native development where engineers focus on intent and judgment rather than process management.