In AI systems, agent context control is the practice of managing the data and instructions an AI model can access during a task. It involves curating prompts, filtering data, and setting operational boundaries to ensure accurate, relevant outputs. This boosts efficiency and reduces hallucinations. It benefits developers, enterprise teams, and power users managing complex, multi-step AI workflows.
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