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Resource Constraints and Performance in Agentic AI Systems

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Progress toward more autonomous AI increasingly depends on agentic systems that combine a language model with tools, memory, state management, and multi-step execution. These mechanisms shape both task capability and operational burden. We compare OpenClaw and NanoBot as complete agentic systems using a paired primary benchmark and a more detailed instrumented subset of paired prompts. In the primary benchmark, the rate of full task completion was 31% for OpenClaw and 25% for NanoBot, a six-percentage-point difference with a 95% task-bootstrap interval from -3 to 15 percentage points, providin

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Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-08-28T03:49:45.000Z

First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.