Monitoring

Assess

Techniques

Observing system behavior in production to detect failures and anomalies.

Why it's here

Placed in Assess: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 1 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.

Evidence (1)

7The New Stack·10/14/2026research
Why most AI pilots fail to reach production
An IDC and Lenovo study says 88% of AI proof-of-concept projects do not reach production, mainly because of unclear goals, poor data readiness, and limited in-house agentic AI expertise. The article argues that production success requires stronger operational controls such as logging, tracing, monitoring, timeouts, validation, and tighter permissions for each agent in a multi-agent system.