Most AI rollouts don't fail at go-live. They fail quietly in the weeks after — when leadership stops watching and the agent silently drifts.
This is the hard truth no one wants on the launch slide:
Your agent isn't a tool. It's a teammate. And like any good teammate, it needs oversight, feedback, and a system that gets it better over time.
Zachary Stauber recently published a must-read post for anyone leading AI adoption inside mid-to-large orgs. The most useful part is how Salesforce actually evaluates Agentforce performance in production.
What "production-grade AI ops" actually looks like
- Weekly, real-time, and monthly evaluation loops — different signals at different cadences
- Defining what "a good answer" means — and measuring it, not eyeballing it
- Using AI to test AI — synthetic eval traffic with grading agents
- Treating customer feedback as a hidden signal stream — the qualitative data that drives long-term trust
The takeaway for RevOps and CX leaders
Flashy launches make slide decks. Operational discipline makes flywheels. If your agent rollout doesn't have a weekly review, a measurement definition, and a retraining feedback loop, you're not running AI in production — you're running a long demo.