Lesson 812 of 1550
AI quality engineer: testing models like systems
Bring quality-engineering rigor to AI features — treating the model as a fallible component inside a larger system.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2component testing
- 3contract testing
- 4shadow traffic
Concept cluster
Terms to connect while reading
Section 1
The premise
AI quality engineering applies systems testing to a probabilistic component; AI can draft tests but cannot decide acceptance bars.
What AI does well here
- Draft contract tests for an AI component's input/output shape.
- Generate shadow-traffic comparison plans for new model versions.
What AI cannot do
- Decide acceptable error rates for your business.
- Replace production-incident learning.
Key terms in this lesson
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