The Agentic Pivot: Engineering leaders share the reality of AI in the SDLC

AI adoption is universal. AI-native software delivery is not.

94% of engineering leaders say their teams use AI somewhere in the SDLC, and 36% already run agentic workflows with limited human intervention. But adoption alone isn't the differentiator anymore. AI has compressed the implementation phase—74% report accelerated code generation—while leaving the phases left-of and right-of code largely untouched. Planning, testing, review, and ship-and-monitor are now the new bottlenecks.

Close the gap between AI adoption and AI formalization

This is a research-backed playbook for CTOs, VPs of Engineering, and engineering leaders who need to:

• Move from experimental AI use to a formalized, AI-native system of work—only 6% of organizations say they have done so today.

• Build the systems needed for teams to trust AI-generated code, specifically the governance guardrails and foundational context to enable safe AI adoption.

• Redesign their SDLC around the four expanded phases—planning, testing, review, and ship-and-monitor—and not just shrink the implementation phase.

• Reinvest the dividends from AI, and why software quality, depth, and engineering capacity are the top priorities industry-wide.

You'll learn how to build an engineering system of work that gives human-and-AI teams the shared context, governance, and judgment they need to pull ahead in the next 12 months.