Evaluation
Articles about Evaluation. Insights on AI agent governance, security, and agentic control from Prefactor.
The Offline-to-Online Evaluation Gap: Why Your Agent Tests Pass but Production Fails
Offline agent evaluations miss 30-40% of real-world failure modes. Here is how to layer trace-based and online evaluation to catch what test sets cannot.
Why AI Agents Fail Production Evaluation: The Reliability Gap Between Benchmarks and Real-World Deployment
Production AI agents fail at rates between 70, 95% depending on task complexity. Here is what evaluation frameworks miss and what to measure instead.
The Silent Failure Gap: Why 88% of AI Agents Fail Quality Evaluation Before Production Reaches Scale
88% of AI agent projects fail before production scale. Here is what the measurement gap looks like and how to close it before deployment compounds the cost.
Measuring what agents actually cost: hidden token overhead and efficiency gaps
A 4x token cost gap between identical agent outputs shows why instrumentation matters before you scale. Here is how to measure and fix it.
Agent Evaluation in Production: What to Measure and How to Prove It
A practitioner playbook for measuring AI agent quality in production: task success rate, drift, failure modes, and building an evidence chain from spans to sc
Ghost Actions: When Your AI Agent Does Things Nobody Asked For
Ghost actions are agent behaviors nobody requested. Here is what they look like, why standard monitoring misses them, and how to catch them before they cause
What Customers Ask Before They Trust Your AI Agent
The five questions enterprise buyers ask before they'll rely on your AI agent, and the evidence artifacts that answer each one before a deal stalls.