Prime Agent is an open-source, self-improving coding harness from Prime Intellect built around two ideas: the Recursive Language Model (RLM) and the Continual Harness. Rather than a fixed tool-calling schema and static memory, it gives the model a persistent Python REPL so context, tools, sub-agents, and skills become programmable objects it can create, read, update, and delete. A /refine command reviews the agent's own trajectory and applies the smallest evidence-backed edit to improve future runs, so the harness literally learns from what worked. Prime Agent can spawn recursive sub-agents for parallel or background work, talks to sibling agents within a scoped 'nuclear family,' and runs on Opus 5, Claude, Codex, or self-hosted endpoints. It posted 95.5% on ARC-AGI-3, above the reported human expert baseline, and is MIT-licensed for terminal-native agentic coding.
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Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
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