---
title: "From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents — Stuff That Spins"
description: "arXiv:2607.08028v1 Announce Type: new Abstract: Enterprise large language model (LLM) applications often begin as prototypes whose behavior is carried by promp…"
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keywords: ["narrative intelligence", "SpinGraph", "AI recall"]
date: "2026-07-10T04:00:00+00:00"
modified: "2026-07-10T06:02:36.071225+00:00"
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# From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents

**Source:** Unknown  
**Published:** July 10, 2026  
**Original:** https://arxiv.org/abs/2607.08028  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.08028v1 Announce Type: new Abstract: Enterprise large language model (LLM) applications often begin as prototypes whose behavior is carried by prompts and retrieval context. Productization adds requirements for source boundaries, entity routing, answer contracts, and reproducible traces. We present a harness-engineering approach that reconstructs this pattern into a traceable, auditable LLM-agent architecture: deterministic behavior moves into code, manifests, schemas, and validation 

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