Software engineering is going through a major reset. AI, especially agentic AI, is changing it from a human-led sequence of tasks into an intent-driven, AI-orchestrated process. This covers design, development, testing, security, deployment, and maintenance. The author, Satish H.C. of Infosys, says AI acts like a new compiler. It turns human intent, business context, and rules into workflows and software. Early AI tools helped with coding, testing, and docs. The next step is structural. Teams state business goals as specs. AI agents then create stories, designs, code, tests, and release items. Developers define problems more clearly, add domain knowledge, and supervise agents working in parallel. The SDLC becomes less linear. Agents handle steps side by side with human checks at key points. Trust must be built in from the start through policy-as-code, monitoring, and rollback tools. Teams need specialists and generalists who can guide AI outcomes.
Software engineering is going through a major reset. AI, especially agentic AI, is changing it from a human-led sequence of tasks into an intent-driven, AI-orchestrated process. This covers design, development, testing, security, deployment, and maintenance. The author, Satish H.C. of Infosys, says AI acts like a new compiler. It turns human intent, business context, and rules into workflows and software. Early AI tools helped with coding, testing, and docs. The next step is structural. Teams state business goals as specs. AI agents then create stories, designs, code, tests, and release items. Developers define problems more clearly, add domain knowledge, and supervise agents working in parallel. The SDLC becomes less linear. Agents handle steps side by side with human checks at key points. Trust must be built in from the start through policy-as-code, monitoring, and rollback tools. Teams need specialists and generalists who can guide AI outcomes.