System 1 Harness

A structural pattern for managing ai-agent performance and safety by introducing a dedicated decision model (“harness) to regulate the continuous loop of a primary reasoning model.

Core Concepts

The Loop Problem: Standard AI agents often operate in a continuous loop driven by a single “reasoning model,” which can lead to uncontrolled execution or safety failures.
The Harness Solution: Introducing a “System 1” style harness allows for rapid, low-latency decision-making to gate, guide, or interrupt the reasoning model.
Jev-Powered Integration: Utilizing jev (a decision model framework) to optimize this harness, ensuring that agent actions are aligned with safety and performance constraints.
Agentic Search Dynamics: Effective agent loops require robust retrieval mechanisms. The integration of lexical scoring functions like BM25 within the agent loop has demonstrated “unreasonable effectiveness” for agentic search tasks, complementing semantic embeddings. See BM25’s Unreasonable Effectiveness in LLM-Driven Agentic Search for detailed analysis on leveraging BM25 for search inside an agent loop.