AI is making developers faster than ever — 63% of organizations now ship code to production more quickly since adopting AI coding tools. But speed without context is creating a new crisis. Downstream processes like testing, security, and deployment haven’t kept pace, and the data tells the story: 45% of deployments linked to AI-generated code lead to problems, and nearly three-quarters of organizations have already experienced a production incident caused by AI-generated code. This is the AI Velocity Paradox — and it’s the defining challenge for engineering leaders in 2026. In this session, Harness and Google Cloud introduce a fundamentally different approach: AI-powered delivery agents grounded in a Software Delivery Knowledge Graph. Rather than adding more automation to a broken pipeline, this model connects code, pipelines, infrastructure, incidents, and developer activity into a single intelligence layer — giving AI agents the context they need to act, not just execute. Prateek Mittal (Harness) and Google Cloud will show how forward-thinking engineering organizations are using Harness AI with Gemini Enterprise Agent Platform I capabilities to: Close the gap between coding speed and delivery safety with end-to-end lifecycle automation Cut incident recovery time and operational risk through AI agents that triage, diagnose, and self-heal Replace fragmented point tools with a unified platform that gives engineering leaders full visibility across the SDLC Reduce cloud waste through context-aware optimization, not just cost dashboards The takeaway: solving the AI Velocity Paradox isn’t about slowing down development — it’s about making everything after code as intelligent as the tools writing it. We’ll share a concrete blueprint for moving from reactive automation to proactive, agentic software delivery that turns AI speed into measurable business outcomes.