The Eval-Driven Product Cycle
The Eval-Driven Product Cycle(评估驱动的产品周期)
概述 / Overview
一套构建 AI 产品的循环框架,其核心在于将评估指标(Eval)作为产品需求文档(PRD)。区别于传统的功能交付模式,该产品闭环专注于定义成功标准,并利用强化学习不断提升指标表现。
来源 / Source
- •嘉宾: Brendan Foody
- •职位: CEO and Co-founder
- •公司: Mercor
核心步骤 / Core Steps
- •Define the Eval (The PRD/Rubric)
- •Run Experiments (Generate Outputs)
- •Measure Capabilities (Score vs Eval)
- •Reinforcement Learning (Update Model)
- •Iterate/Raise Bar
核心原则 / Core Principles
- •The model is the product; the eval is the PRD.
- •Success is measured by automated verifiers, not just human feel.
- •Reinforcement Learning (RL) climbs the eval metric.
- •Data shifts from pre-training volume to post-training quality.
适用场景 / When to Use
适用于构建 AI 原生产品或集成 LLM 能力,且需要对输出质量进行持续、系统性调优的场景。
常见错误 / Common Mistakes
单纯依赖“体感”,而非严谨、可量化的评估集。
实战案例 / Real-World Example
某 AI 实验室针对法律合同制定了“完美修订(Redline)”的评估准则,并持续开展实验,直到模型能够稳定达到该准则的评分要求。
金句 / Quote
"If the model is the product, then the eval is the product requirement document."