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The evolution and future of agentic AI in software engineering, distinguishing it from prior AI systems by its action-oriented, autonomous, and goal-oriented capabilities. It details the foundational architecture of AI agents, emphasizing components like reasoning engines, memory, planning, and tool use. The source then traces the historical trajectory of automated software development, from early compilers to modern AI assistants, positioning agentic AI as the latest paradigm shift. Furthermore, it outlines the Agentic Software Development Lifecycle (A-SDLC), explaining how agents can transform every phase from requirements to deployment, leading to significant economic and productivity impacts. Finally, the text addresses the crucial challenges of governance, risk, and trust in autonomous systems, highlighting the need for robust guardrails and the shifting roles of human developers in a collaborative human-agent team.