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
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Related Claims
UnverifiedThe 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% similarUnverifiedAn Agent acts as a coordinator between the user and the large model, understanding user needs, invoking tools to process them, and returning results.74% similarUnverifiedIn the dual-track architecture, the background agent is suited for pairing with stable, fast, and economical models to execute already-decomposed subtasks, while the foreground agent needs to understand ambiguous natural language and decompose tasks, making it better suited for more capable flagship models.74% similarUnverifiedLarge models generally support a "System Prompt" mechanism, allowing developers to inject identity settings and behavioral instructions into the model before a conversation begins, causing the model to respond in the specified persona.73% similar
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