Root cause and failure analysis/spoke/Phase 3
Cross-Run Pattern Detection: Finding Systemic AI Failures
/Truvyx Engineering/Draft
A method for turning repeated agent failures into prevention work.
This draft examines AI failure pattern detection. It uses the Truvyx multi-agent evaluation glossary for consistent technical definitions and connects the topic to a repeatable system-level evaluation practice.
Normalize runs
TODO: Draft this section with concrete examples, implementation guidance, and verifiable evidence.
Find concentrations
TODO: Draft this section with concrete examples, implementation guidance, and verifiable evidence.
Separate symptoms from causes
TODO: Draft this section with concrete examples, implementation guidance, and verifiable evidence.
Prevent recurrence
TODO: Draft this section with concrete examples, implementation guidance, and verifiable evidence.
Continue reading
Place this topic in the broader evaluation system with the related guides below.
- Root Cause Analysis for AI Agents: Moving Beyond "It Hallucinated"
- Multi-Agent Failure Patterns: A Taxonomy of Coordination Breakdowns
- Regression Monitoring for AI: How to Catch Silent Model Degradations
- What is Multi-Agent Evaluation? A Complete Guide for 2026
- The Definitive Glossary of Multi-Agent Evaluation Terms (2026 Edition)