The 88% failure rate matches what I see in the teams I talk to. The demo gap is the most common killer: an agent that works in a clean staging environment falls apart the moment it hits real user data. I now require every eval to include at least 20% production-sampled cases before I will sign off on a rollout. What is your take on the right ratio of synthetic to real data in an eval set?