devtool
为什么大厂都在补 Harness？Agent 的竞争正在从模型转向运行时
While model capability is important, it's the runtime control layer of Harness that differentiates Agent products.
6.9Overall
Utility7
Onboarding6
Craft7
Niche fit7
Longevity7
Five dimensions scored independently; overall is a weighted average. Scores are only comparable within this same rubric.
Good for
Teams needing strong runtime control for AI products
Not for
Teams with low needs for runtime control in models
Project description
模型能力决定上限，但真正拉开 Agent 产品差距的，是模型与任务之间的运行控制层——Harness。Anthropic、OpenAI、DeepSeek 等大厂纷纷公开补 Harness，背后是 Context、成本与验证成为新瓶颈。本文从 AI 产品交付视角，拆解 Harness 边界与四条技术路线差异。 只看模型，已经解释不了今天的 Agent 产品差距。 同一个模型，接入不同的工具、上下文策
Alternatives
TensorFlow Extended (TFX)AirflowKubeflow