Comparison
Eval-Driven Development vs LLM-as-Judge
Eval-Driven Development and LLM-as-Judge are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Eval-Driven Development
As soon as you have more than one prompt change per week or more than one engineer iterating on the same prompt.
A team's prompt PR template requires: eval set updated if behavior changed, baseline win rate ≥ 50%, no regressions on three named cases.
When you would reach for LLM-as-Judge
When you need to evaluate thousands of open-ended outputs cheaply and quickly.
MT-Bench: GPT-4 scoring 80 multi-turn questions.
Frequently asked
What is the difference between Eval-Driven Development and LLM-as-Judge?
Eval-Driven Development: Eval-driven development is the LLM analog of test-driven development: you write evals for behavior before changing the prompt or model, and every change is graded against the same eval suite. LLM-as-Judge: LLM-as-judge uses a strong LLM to score or compare outputs from other LLMs. It is how most production teams evaluate quality at scale when human review is too slow.
When should I use Eval-Driven Development vs LLM-as-Judge?
As soon as you have more than one prompt change per week or more than one engineer iterating on the same prompt. When you need to evaluate thousands of open-ended outputs cheaply and quickly.
Are Eval-Driven Development and LLM-as-Judge the same thing?
No. Eval-Driven Development is evaluation; LLM-as-Judge is evaluation. They are related but address different parts of the AI stack.