MIT Technology Review Insights survey of 300 executives identifies agentic AI as the third major evolution in software engineering after open source and DevOps. The report states 51% of teams currently use agentic AI in limited fashion with 45% planning adoption within 12 months; ambitions target end-to-end PDLC and SDLC management at 72% of organizations within two years, projecting 37% average acceleration in pilot-to-production delivery (MIT Technology Review Insights, 2026). Primary coverage correctly notes integration and compute costs as top barriers yet understates the required shift in daily practices from code authorship to agent orchestration and output verification. McKinsey's 2023 generative AI productivity analysis estimates 45% of current software development tasks automatable, revealing patterns of role bifurcation between AI supervisors and specialized validators missed by the surveyed executives' incremental expectations (McKinsey & Company, 2023). Stanford AI Index 2024 documents 10-100x compute cost increases for agentic systems, confirming the report's challenges while highlighting unaddressed error rates exceeding 30% in multi-step software tasks. Gartner's 2025 emerging technologies report positions agentic AI at peak expectations with 80% of engineering leaders anticipating workflow redesign, synthesizing that organizational change lags technology exactly as seen in prior DevOps adoptions and exposing the original source's limited treatment of requisite new competencies in prompt engineering, agent governance, and AI system design (Gartner, 2025).