Evals
Automated tests that grade LLM outputs against expected behavior.
/ quick answer
Evals are the unit tests of AI systems. Each eval is an input, an expected property (exact match, LLM-judge score, latency budget), and a pass/fail. Ship without evals and you fly blind. Automated tests that grade LLM outputs against expected behavior.
/ frequently asked
What is Evals?
Evals are the unit tests of AI systems. Each eval is an input, an expected property (exact match, LLM-judge score, latency budget), and a pass/fail. Ship without evals and you fly blind.
What is an example of Evals?
An eval suite runs 200 real support questions nightly; a regression alerts if grounded-answer accuracy drops below 92%.
Why does Evals matter?
Automated tests that grade LLM outputs against expected behavior.
What should I learn after Evals?
Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →LLM-as-Judge
Using a strong model to grade another model's output.
- →AI Evals
Reproducible test suites that measure LLM output quality across model, prompt and code changes.
Related workflows
Turn this into a repeatable process.
- →Build an Internal Knowledge Bot
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- →Build a Tier-1 Customer Support Agent
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- →How to Create a Website with AI
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- →How to Build an AI Content System
A repeatable pipeline that turns one input into publish-ready content across every channel.
Related tool stacks
The tools that run it in production.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
Comparisons & alternatives
Pick between the options.
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- →Lovable vs Bolt
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- →OpenAI API vs Anthropic API
Choosing between the two leading LLM API providers for production apps.
- →Lovable vs Cursor
Prompt-to-app builder vs AI-assisted code editor — which one should you reach for?