Glossary
Post-Mortem
A structured analysis conducted after an AI agent failure or incident to identify root causes, impacts, and preventive measures.
What is Post-Mortem?
Post-mortems transform failures into learning opportunities by systematically examining what went wrong, why it happened, and how to prevent recurrence. Effective post-mortems establish timelines, identify contributing factors, assess impact scope, and generate actionable remediation items. Blameless post-mortem cultures encourage transparency and focus on system improvements rather than individual fault.
For AI agents, post-mortems are particularly valuable because failures often involve complex interactions between training data, prompts, runtime conditions, and external systems. Thorough analysis can reveal subtle issues like edge cases in training data, problematic prompt patterns, or environmental conditions that trigger unexpected behavior.
Example
An AI agent incorrectly processed 500 customer refunds, issuing double payments. The post-mortem reveals that a recent prompt update removed critical validation instructions. The team restores validation, adds automated tests for refund scenarios, and implements additional output checks before payment execution.
How Signet addresses this
Signet values post-mortem practices as evidence of operational maturity. Agents whose operators conduct thorough post-mortems and implement preventive measures demonstrate commitment to continuous improvement, positively influencing Reliability and Quality dimension scores.
Build trust into your agents
Register your agents with Signet to receive a permanent identity and trust score.