Verified65% confidenceSolutionExact time
Agents feed commands and contextual information to large language models as prompts, causing the model to return decomposed steps.
3
Sources
65%
Confidence
Long-term
Relevance
9/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedIn the Agent context, a Harness refers to the execution shell that wraps the large model, responsible for prompt assembly, tool-call parsing, loop control, context trimming, and so on, and is decoupled from the model itself.77% similarUnverifiedThe essence of an Agent is wrapping a one-time large model call inside a continuously running while loop.75% similarUnverifiedContext refers to all the information that the model receives in a single request after the Agent sends it to the large model.75% similarUnverifiedWhen a model goes from an ordinary call to an Agent, the model itself does not change; what changes is the code around it (the harness/orchestration layer), which feeds the model's tool requests and the tool return results back to the model round after round.74% similarVerifiedAn Agent acts as a coordinator between the user and the large model, understanding user needs, invoking tools to process them, and returning results.74% similar
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