10/17/2026
Your AI agent sounds brilliant. But did it actually do anything?
A customer asks, "Can you reschedule my appointment?"
❌ Slop: The AI explains how to reschedule.
➖ Better: It finds open time slots.
✅ Value: It moves the appointment, updates the system, and confirms the change.
Only one of those finishes the job, and that's the gap between AI that answers and AI that resolves.
In our latest blog, we recap the key lessons from our webinar with CEO Rebecca Clyde and CTO Chris Maeda on building enterprise AI agents that create real value. Inside:
🔹 Why confident, fluent AI can still be slop
🔹 Why you should start with the customer outcome, not "where can we add AI?"
🔹 Why demos prove one scenario works, while production has to handle everything you didn't rehearse
🔹 Why you should test how your agent fails, not just how it answers
🔹 Why, in healthcare, "Can the AI do it?" is the wrong question. The real question is "Should it?"
🔹 Why long conversations aren't a success metric when the customer leaves without what they came for
Plus an 8-point gut check to see whether your agent is truly enterprise-ready.
Chris put it best: treat these models like junior employees. Give them context, define their responsibilities, review their work, and expand their authority only as they prove reliable.
👉 Read the full post: https://buff.ly/MHBjnW3