Ara Khan on Improving Coding Agents

AI Engineer26m 49s
Ara Khan discusses improving coding agents.
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    Ara Khan, a founding engineer at Cline, explains an experiment that used a separate agent to inspect coding-agent evaluation failures and propose harness changesAn AI agent harness is the software framework that packages a model with tools, instructions, context management, execution controls, and user interaction..

    The talk describes sandboxed tasksAn AI agent sandbox is an isolated execution environment that limits which files, processes, networks, credentials, and external systems an agent can access., failure categories and a repeated evaluation loopEvaluation is the systematic assessment of a system's behaviour or results against explicit criteria., while noting that changes should generalize beyond the immediate test cases.

    Ara Khan also discusses potential applications across inference and hardware and argues that engineers should seek problems that benefit from stronger models without being solved by scale alone. These are the speaker’s forecasts and views.

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    Video topic coverage

    • Agents & workflows100
    • Coding & tools88.5
    • Models & learning37.5
    • Infrastructure & compute27.1
    • Research & evaluation95.8
    • Safety & security17.7
    • Business & productivity0
    • Creative & media0
    • Robotics & perception0
    • Society & policy0

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    Ara Khan discusses improving coding agents. With WWW.ARTIFICIAL-INTELLIGENCE.VIDEO, 11 November 2026 and duration 26m 49s.

    Ara Khan describes using evaluation feedback to improve a coding-agent harness and reflects on engineering work.