AI BriefingKey AI Agent Terminology Explained
Key point
This clearly defines easily confused concepts like Harness, Scaffold, and Model when building AI Agents.
Details
To address the phenomenon of terminology definitions becoming ambiguous due to the rapid development of the AI Agent field, this distinguishes and explains the concepts of Model, Scaffolding, Harness, and Agent.
Model refers to the LLM itself. It only performs text input/output functions and does not have its own memory or loop.
Scaffolding is the behavior-defining layer around the model. It includes system prompts, tool descriptions, context management (memory), and determines how the model perceives and acts in the world.
Harness is the execution layer inside the agent. It calls the model, handles tool execution, and determines when to stop the agent's operation. Harness Engineering, which covers error handling and guardrail design, is an important design area in both the model's reasoning and training stages.
Agent is the form in which Scaffolding and Harness are combined with a model. Beyond simply generating text, it refers to a system that, through a loop, gathers information, makes decisions, and leads to actual actions.
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