The number that defines 2026’s AI landscape isn’t a benchmark score. It’s 88%. That is the share of AI agent pilot projects that, according to an Anaconda and Forrester Consulting study published in early 2026, never reach production. Not 88% that ta...
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Kartik N V J K
AI Developer | Making AI reliable, trustworthy & accessible to everyone | Active community contributor
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?