How to Control Cost and Quality as Agents Hit Production

Most AI agents never make it past the prototype stage, and the ones that do often blow past their cost and quality expectations. Hear from RapDev Solutions Architect and Datadog Ambassador Logan Rohloff and Datadog's Will Potts (AI Observability team) on the practical loop teams use to control cost, quality, and security before agents ship, catch drift and cost spikes once they're live, and define what "good" actually means for their use case. Includes a live demo of Datadog Agent Observability and a real customer example showing an 80% cut in mean time to resolution.