Renewals, holidays, and launches don’t need hardcoded rules. With reward signals, eligibility criteria, and timing action sets, agents adapt naturally to recurring patterns.

You don’t coach by chasing the trophy. You coach by tracking whether each play puts you in a stronger position. The same is true for customer engagement.

A/B tests help us see what works on average, but real users aren’t average, their motivations and contexts vary. That’s where agentic learning shines, adapting to individuals over time. The best results come when we layer the two: tests for clarity, agents for personalization.

Asking why an agent made one decision is like asking a human. The answer will sound right but miss the deeper truth. The real insight comes from system-level questions about patterns and priorities. Treat agents like teammates: give clarity, not interrogation.