Importance of Terminology Unification in AI Agent Development
The latest AI agent glossary published by the Hugging Face team provides a practical development guide by organizing concepts that tend to be confusing in a rapidly evolving field. In particular, the distinction between “harness” and “scaffolding” is key to solving design challenges faced by agent developers.
Created based on discussions at ICLR 2026, this glossary uniformly explains concepts used in actual products such as Claude Code, Codex, and Hermes Agent. Developers can use these definitions from today to improve communication within their teams and achieve more efficient agent design.
(Source: Harness, Scaffold, and the AI Agent Terms Worth Getting Right)
Technical Relationship Between Models and Harnesses
Models themselves are simply LLMs (such as Claude, Qwen, GPT, Kimi, DeepSeek) that receive text as input and output text. Models alone do not have memory functions between calls and do not perform loop processing.
A harness plays the role of actually executing the intent expressed by the model when it makes tool calls. According to the official documentation of Claude Code, “Claude Code serves as the agentic harness around Claude,” and all elements other than the model are referred to as a harness.
This distinction allows developers to clearly separate the capabilities of models and the responsibilities of infrastructure. It enables a division of roles where models are responsible for inference and harnesses manage the execution environment and tool integration.
(Source: Harness, Scaffold, and the AI Agent Terms Worth Getting Right)
Behavior Control Through Scaffolding
Scaffolding functions as a layer of behavior definitions around the model. Specifically, it includes system prompts, tool descriptions, methods for analyzing model responses, and content to be remembered between steps (context management).
This layer shapes how the model recognizes and acts in the world during both training and inference. By adjusting the settings of scaffolding, developers can finely control the behavior of agents.
The distinction between scaffolding and harness is particularly important in training pipelines. When it is necessary to reason about each independently, this conceptual separation brings clarity to design. Hooks, resource management, and other infrastructure elements may also be included in the broad sense of scaffolding.
(Source: Harness, Scaffold, and the AI Agent Terms Worth Getting Right)
Summary
- By referencing Hugging Face’s glossary to unify agent development terminology within teams, it is possible to improve the efficiency of design discussions and the clarity of technical specifications.
- Designing with an awareness of the role separation between models and harnesses enables the construction of flexible architectures that can independently scale inference processing and tool execution environments.
- By systematically managing the setting parameters of the scaffolding layer, it is possible to establish a development process that efficiently derives agents for different purposes from the same model.