- In short
- Threshold alerts, such as cost spiking past a set percentage of a rolling average or p95 latency crossing the SLA line, catch sudden, sharp changes. Model drift, a gradual change in output distribution over time on stable inputs, is not well caught by simple thresholds and instead requires periodic comparison of output distributions. Matching the detection method to the shape of the change is the core skill.
Full concept guide coming soon
We are building the in-depth, exam-aligned guide for this knowledge point. In the meantime, explore the prerequisites and related concepts below, watch the official Anthropic Academy lessons, and start an adaptive study session to master it with Archie.
Watch and learn
Official Anthropic Academy lessons first, then hand-picked walkthroughs. Videos load only when you press play.
No videos curated for this concept yet
We are still curating the best official and community videos for this topic.
References & primary sources
Adaptive study
Master this concept with Archie
Practice it inside an adaptive study session. Archie, your Socratic AI tutor, tracks your mastery with Bayesian Knowledge Tracing and schedules the perfect next review.