In plain English
This page explains why testing AI parts one by one is necessary but incomplete. Safe-looking parts can still produce unsafe behavior when combined.
- Why this matters: AI risk can come from the whole arrangement, not one obvious model.
- What to look for: data, memory, routes, adapters, tools, evaluators, updates, and rollback paths.
- Technical version below: the expert terminology remains available and is linked through the glossary.
The Limits of Component Certification
Certification must specify composition, environment, configuration, and permitted transitions.
Mechanism
The mechanism is interaction. Components exchange context through hidden state, prompts, outputs, adapters, memory retrieval, tool calls, evaluatorA system that judges whether an AI output or candidate is acceptable. Open glossary definition prompts, and release rules. Each interaction can change what the next component sees and what the system is allowed to do.
Evaluation implication
The evidence record should include the exact composition manifestA machine-readable record of the exact runtime composition used for an evaluation, release, incident, or rollback. Open glossary definition. A statement such as “Adapter C passed” is incomplete unless it says which base model, load order, router, prompt package, memory snapshot, evaluator, inference configuration, and deployment environment were used.
Practical control
Use composition-aware test suites, targeted higher-order samples, route-level canaries, independent judges, and rollbackReturning a system to an earlier known state. Open glossary definition packets that include all relevant runtime dependencies.