RLMs, Harness Design, and AI Agent Efficiency
An executive analysis of Recursive Language Models (RLMs) and the strategic shift from brute-force compute to opinionated harness design. This brief explores how compositional generalization and code-based context management are redefining AI agent capabilities, offering actionable frameworks for optimizing multi-agent systems and reducing inference costs.