Comparison
Eval-Driven Development vs Offline Evaluation
Eval-Driven Development and Offline Evaluation 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 Offline Evaluation
Offline Evaluation comes up when the question is fundamentally about evaluation.
A RAG team's offline eval: 500 (question, gold answer) pairs, scored by LLM-as-judge on faithfulness and relevance, run on every prompt PR.
Frequently asked
What is the difference between Eval-Driven Development and Offline Evaluation?
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. Offline Evaluation: Offline evaluation runs a fixed dataset of inputs through a candidate model or prompt, scores each output, and reports aggregate quality — the standard way to compare changes before shipping.
When should I use Eval-Driven Development vs Offline Evaluation?
As soon as you have more than one prompt change per week or more than one engineer iterating on the same prompt. Offline Evaluation applies when you are focused on evaluation.
Are Eval-Driven Development and Offline Evaluation the same thing?
No. Eval-Driven Development is evaluation; Offline Evaluation is evaluation. They are related but address different parts of the AI stack.