Self-Improving RLM Agent 'Prime Agent' Released for Coding and Long-Horizon Autonomous Tasks

A new AI agent Prime Agent for coding and research tasks has been released. This agent is designed around two core abstractions, RLM (Recursive Language Model) and Continual Harness, to enhance its ability to perform long-horizon autonomous tasks.

Core Technical Architecture

• RLM (Recursive Language Model): A method that treats context like variables and utilizes recursive sub-agents like function calls. This allows complex tasks to be decomposed into sub-steps and processed.
• Continual Harness: Provides a persistent REPL (Read-Eval-Print Loop) environment, enabling the agent to continue tasks while receiving real-time feedback.

This architecture helps the agent go beyond simple command execution, allowing it to self-improve and achieve long-term goals in complex coding and research tasks.