The dream of a single all-knowing AI running your entire SDLC is both admirable and widespread. But in reality, specialized agents with distinct responsibilities outperform generalist systems.

This talk makes the case for using multiple agents in the SDLC: planning agents that think like principal architects, testing agents that prepare code with adversarial precision, and review agents that enforce quality like seasoned QA engineers.

We’ll explore the technical foundations that make this possible, including deep codebase context engineering for specialization, essential MCPs and tool delegation, and developer workflow patterns that ensure AI-assisted development scales with both velocity and quality. Attendees will leave with practical knowledge to leverage agentic AI throughout the development lifecycle that deliver safer, smarter, and more reliable software.