Unit Test
What is a unit test?
Unit tests are automated tests that verify individual pieces of code—functions or processes—work as expected by testing their logic thoroughly. Engineers write unit tests for each function, often creating multiple test cases (half a dozen to a dozen) to verify that the code behaves correctly under different conditions.
Unit tests are a foundational practice in software engineering, providing confidence that individual components work properly before they're integrated into larger systems.
How do unit tests relate to AI development?
In the context of AI products, evals (evaluations) serve an analogous role to unit tests. While unit tests verify that deterministic code produces expected outputs, evals verify that AI applications perform as expected—accounting for the non-deterministic nature of AI outputs.
The parallel helps AI practitioners transfer quality practices from traditional software to AI products:
- Unit tests for code: Verify individual functions produce correct outputs
- Evals for AI: Verify AI systems produce acceptable outputs across diverse inputs
Both practices share a common goal: building confidence that the system works as intended.
Why are unit tests and evals both essential?
Just as unit tests are not optional for quality software development, evals are not optional for quality AI products. Both represent baseline practices for ensuring reliability and catching problems before they reach users.
In traditional software, engineers thoroughly test code logic with multiple assertions per function. In AI development, teams must similarly test AI behavior with comprehensive evals that cover important failure modes and edge cases.
The key difference: unit tests verify deterministic logic, while evals must account for variability in AI outputs and focus on patterns of behavior rather than exact matches.
Learn more:
- How I Designed & Implemented Evals for Product Talk's Interview Coach
- Building My First AI Product: 6 Lessons from My 90-Day Deep Dive
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