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As AI-assisted development accelerates release velocity, feature flags are evolving from simple rollout tools into a control plane for modern software delivery. In this episode of AppDevANGLE, Paul Nashawaty speaks with Michael Beemer (Dynatrace) and Andrew Norris (Dynatrace, former CEO of DevCycle) about how Dynatrace is bringing feature management, observability, and experimentation together to help teams ship faster without sacrificing safety. The discussion explores how feature-level observability closes the confidence gap created by continuous deployment, why separating deployment from release matters more in AI-driven SDLCs, and how teams can manage risk while increasing delivery speed. Built for developers, platform engineers, and product teams navigating high-velocity release environments. Key Highlights Why Dynatrace sees feature flags as a delivery control plane How observability data informs safer feature rollouts Feature-level insight vs. traditional service-level monitoring Managing AI-assisted and agentic code in production Using experimentation to connect releases to business outcomes Avoiding technical debt with full-lifecycle feature management