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Deutsch(DE) Studie: Claude Code und Codex überschätzen benötigte Laufzeit systematisch, teils um das Zehnfache. Agenten-Orchestrierung braucht externe Zeitfenster, da inter

AI Models Claude Code and Codex Overestimate Task Runtime

A new study indicates that AI models like Claude Code and Codex systematically overestimate the runtime required for tasks, sometimes by a factor of ten. This inaccuracy necessitates external time-window management for agent orchestration, as internal estimations are unreliable. AI

IMPACT Inaccurate runtime estimations by AI models could hinder the efficiency and reliability of automated task execution and agent orchestration.

RANK_REASON The cluster reports on a study detailing performance issues with AI models, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]

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AI Models Claude Code and Codex Overestimate Task Runtime

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16 / 100
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The cluster reports on a study detailing performance issues with AI models, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
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model release
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 Deutsch(DE) · aisyndicate ·

    Study: Claude Code and Codex systematically overestimate required runtime, sometimes by a factor of ten. Agent orchestration requires external time windows, as inter

    Studie: Claude Code und Codex überschätzen benötigte Laufzeit systematisch, teils um das Zehnfache. Agenten-Orchestrierung braucht externe Zeitfenster, da interne Schätzungen unzuverlässig sind. https:// the-decoder.de/ki-agenten-habe n-kein-zeitgefuehl-und-wissen-es-nicht/ # KI …