What Is Eval-Driven Development? A Guide to Improving AI Agents Step by Step

At a glance

LangChain introduces eval-driven development (EDD), in which developers set evaluation criteria (evals) first and build the AI agent to meet them. Improving agents by feel becomes harder to judge over time, which is why this approach is useful. The article explains the process step by step.

Key points

1. 1

   EDD borrows from test-driven development (TDD) and sets success criteria before writing code.

2. 2

   Agents can give different answers to the same question and may have many correct answers, so ordinary tests alone are not enough.

3. 3

   The first step is to define in a short specification what the agent should and should not do, and to handle only one behavior at a time.

4. 4

   After making changes, results are compared through experiments, because fixing one problem can cause another.

Why it matters

This helps not only people who build AI agents but also users of these products understand the standards for judging whether performance has truly improved.