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    Leaders are using AI more often, but adoption is not ability. As execution accelerates, accepted work—not generated output—becomes the real productivity measure.

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← AI knowledge base/Concepts & methods

AI task time horizon

METR's measure of the length of task, in human working time, that a model completes with 50% reliability; about one hour for frontier models in March 2025, doubling roughly every seven months.

Introduced
2025-03all 2025 milestones
Doubling time
≈7 months (2019–2025)

Linked from

  • Agent evaluationRepeatable testing of an AI agent's complete task, tool use, permissions and final system state against explicit acceptance criteria. A successful demo is not a production reliability estimate.

More concepts & methods

  • machine learningscientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions
  • deep learningspecialized form of machine learning that uses artificial neural networks to identify patterns in data
  • genetic algorithmcompetitive algorithm for searching a problem space
  • Altitude, depth and rangeFelix Rieseberg’s framework for ambition with AI models: speed repeats work faster, altitude targets outcomes, depth uses expert instruments and range combines disciplines.
  • Outcome-based promptingAsking an AI agent to pursue a specified change for a user or system, with evidence and boundaries, instead of merely producing a named deliverable.
  • AI outside judgeAn acceptance check outside an agent’s self-assessment, such as a deterministic test, held-out evaluation, measurement or separately briefed reviewer.

Sources

  • Primary documentation
GM.
George Moreas.

Senior product leader and hands-on AI builder writing about search, automation, ecommerce, and the systems changing how companies operate.

moreas.george@gmail.com
Boca Raton, FL

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