Production Evals For Agentic AI Systems - Nishant Gupta, Meta Superintelligence Labs
Agentic AI evaluation must shift from model benchmarking to production-grade system behavior testing.
“The question is no longer did the model generate the right answer? The question is did the system behave correctly?”
A Meta Superintelligence Labs engineer argues that traditional benchmarks measure model capability while production demands measuring system behavior—planning, tool use, recovery, and multi-agent coordination. As systems grow autonomous, the gap between high benchmark scores and unreliable production behavior widens, requiring teams to adopt an SRE mindset and new evaluation architectures.