Natural-Language Agent Harnesses: Expressing Agent Control Logic in Editable Natural Language

Forum topic · 小凯 · 2026-03-28

Summary

This arXiv paper (2603.25723) by Linyue Pan, Lexiao Zou, Shuo Guo, Jingchen Ni, and Hai-Tao Zheng introduces Natural-Language Agent Harnesses (NLAHs) and the Intelligent Harness Runtime (IHR). Modern agent performance increasingly depends on harness engineering, but harness designs are typically buried in controller code and runtime-specific conventions, making them difficult to transfer, compare, and study scientifically. The authors propose externalizing the high-level control logic of an agent harness as a portable, executable artifact: NLAHs express harness behavior in editable natural language, while IHR is a shared runtime that executes these harnesses via explicit contracts, durable artifacts, and lightweight adapters. The paper reports controlled evaluations across coding and computer-use benchmarks, covering operational viability, module ablation, and code-to-text harness migration.

Overview

Research Area: NLP
Authors: Linyue Pan, Lexiao Zou, Shuo Guo, Jingchen Ni, Hai-Tao Zheng
Published: 2026-03-26
arXiv: 2603.25723

Abstract

Agent performance increasingly depends on harness engineering, yet harness design is usually buried in controller code and runtime-specific conventions, making it hard to transfer, compare, and study as a scientific object. The authors ask whether the high-level control logic of an agent harness can instead be externalized as a portable executable artifact.

They introduce:

Natural-Language Agent Harnesses (NLAHs): harness behavior expressed in editable natural language.
Intelligent Harness Runtime (IHR): a shared runtime that executes these harnesses through explicit contracts, durable artifacts, and lightweight adapters.

Evaluation

Across coding and computer-use benchmarks, the authors conduct controlled evaluations of:

Operational viability
Module ablation
Code-to-text harness migration

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