Prime Agent: A Self-Improving RLM Harness

• URL: http://arxiv.org/abs/2608.23552v1
• Date: Mon, 24 Aug 2026 17:54:19 GMT
• Title: Prime Agent: A Self-Improving RLM Harness
• Abstract summary: Prime Agent is an open-source harness for long-horizon evaluation and coding-agent.<n>It standardizes execution, recovery, verification, and resource accounting while leaving strategy construction to the model.<n>Prime Agent raises ARC-AGI-3 RHAE Best@1 from 30% to 95.5% and matches or exceeds native and popular harnesses.
• Score: 5.540645425386541
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Language models are sequential processors, but long-horizon agency requires external information and computation beyond model weights and active context. Prime Agent is an open-source harness for long-horizon evaluation and coding-agent workflows. A persistent IPython REPL follows the Recursive Language Model abstraction for programmatic context processing and test-time compute, while Continual Harness preserves histories, memories, skills, prompts, and subagent specifications across trajectories. Recursive subagents coordinate through direct agent-to-agent communication, and the Agents View lets humans inspect and manage daemon-backed sessions. Prime Agent standardizes execution, recovery, verification, and resource accounting while leaving strategy construction to the model. This low-friction, expressive membrane prevents harness failures from becoming model failures and pushes measurement toward the model's true maximal underlying capability. Prime Agent raises ARC-AGI-3 RHAE Best@1 from 30% to 95.5% and matches or exceeds native and popular harnesses across long-context coding, GPU-kernel generation, emulator construction, and autonomous nanoGPT speedruns. On Factorio, we find refinement allows for continuous technology progression and dedicated subagents enable parallelized work. Code is available at https://github.com/PrimeIntellect-ai/prime-agent.

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