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Prime Intellect has open-sourced Prime Agent, an autonomous coding harness that leverages Recursive Language Models (RLM) to treat sub-agent delegation as function calls within a persistent Python REPL. This architecture allows agents to dynamically edit their own prompts and memory mid-run while achieving performance metrics on ARC-AGI-3 that exceed reported human expert baselines using Opus 5. The release offers significant implications for AI research labs and engineering teams seeking scalable, self-improving agent frameworks capable of handling long-horizon tasks without fixed tool schemas.

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Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel

MarkTechPost6 august 20264 min de cititArticolul și perspectiva sunt în engleză.

Prime Intellect has open-sourced Prime Agent, a coding and research harness built on two abstractions: the Recursive Language Model, which turns sub-agent calls into functions inside a persistent IPython kernel, and the Continual Harness, which lets the agent edit its own prompts, skills, memory, and sub-agent specs mid-run. With Opus 5 it reports 95.5% RHAE Best@1 on ARC-AGI-3, above the reported human expert baseline of 95.4%. The post Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel appeared first on MarkTechPost.

Prime Intellect has open-sourced Prime Agent, a self-improving coding harness designed around two abstractions: the Recursive Language Model (RLM) and Continual Harness. Fixed tool schemas and context compaction force a model to work around its own scaffolding. Prime Agent replaces both with a persistent Python REPL and a rewritable harness. With Opus 5, it reports 95.5% on ARC-AGI-3, above the reported human expert baseline of 95.4%. It is MIT-licensed. Yes, today. Prime Agent installs on Linux or macOS with…

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