Duplicate from ChenLiu1996/Agent-Harness-Engineering

Co-authored-by: Chen Liu <ChenLiu1996@users.noreply.huggingface.co>

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Agent_Harness_Engineering_Survey.pdf

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README.md

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+---
+license: cc-by-4.0
+language:
+  - en
+pretty_name: Agent Harness Engineering Survey
+tags:
+  - llm-agents
+  - agent-harness
+  - harness-engineering
+  - tool-use
+  - orchestration
+  - observability
+  - evaluation
+  - governance
+  - survey
+---
+
+
+<div align="center">
+
+  <font size="6">**Agent Harness Engineering: A Survey**</font>
+
+  ![](https://img.shields.io/badge/Total_Entires:_170+-pink)
+  [![Project Page](https://img.shields.io/badge/Project_Page-B9DEF1)](https://picrew.github.io/LLM-Harness/)
+  [![PDF](https://img.shields.io/badge/PDF-DADBDD)](https://picrew.github.io/LLM-Harness/main.pdf)
+  [![OpenReview PDF](https://img.shields.io/badge/Openreview_PDF-darkred)](https://openreview.net/pdf?id=eONq7FdiHa)
+  [![GitHub](https://img.shields.io/github/stars/Picrew/awesome-agent-harness.svg?style=social\&label=Stars)](https://github.com/Picrew/awesome-agent-harness)
+</div>
+
+
+This dataset hosts the PDF for **Agent Harness Engineering: A Survey**.
+
+This release contains only the survey PDF. For the curated resource list, please see the companion [project page](https://picrew.github.io/LLM-Harness/) or [GitHub repository](https://github.com/Picrew/awesome-agent-harness).
+
+
+## Abstract
+
+**The harness is becoming the binding constraint.** The rapid deployment of large language model agents in production has revealed a recurring pattern: task execution reliability depends less on the underlying model than on the infrastructure layer that wraps it, the agent execution harness.
+
+The paper is organized around three central claims:
+
+1. **Harnesses are independent system layers.** Real-world reliability is shaped by execution controls, feedback loops, governance, evaluation, and operational design, not only by model capability.
+2. **ETCLOVG separates production concerns.** Execution, Tooling, Context, Lifecycle, Observability, Verification, and Governance expose architectural boundaries that earlier frameworks often conflate.
+3. **A broad ecosystem map reveals gaps.** A systematic mapping of the open-source ecosystem surfaces adoption patterns across sandboxes, protocols, memory systems, orchestrators, observability platforms, benchmarks, and governance stacks.
+
+
+## Three Engineering Phases
+Read across 2022–2026, agent engineering has gone through a coherent shift in where the marginal effort lands. The three phases overlap in time and concept; they describe what the field has chosen to engineer, not a clean sequence of replacements.
+
+**2022–2024**: Prompt engineering. The primary lever is the input prompt text: instructions, few-shot examples, and reasoning templates, all optimized for a single model call.
+
+**2025**: Context engineering. The question shifts from "what is the input?" to "what should the model see at each step?" The scope expands to retrieval, compaction, tool-result ranking, and managing context-window saturation across turns.
+
+**2026–**: Harness engineering. As models become capable enough to attempt long-running tasks, the engineering focus expands to the full infrastructure wrapper: execution environment, tool interface, context, lifecycle, observability, verification, and governance.
+
+<div align="center">
+
+<img src="https://chenliu-1996.github.io/assets/harness_figure_teaser.png" width="70%"/>
+</div>
+
+
+## The ETCLOVG Taxonomy
+
+We organize the harness into seven layers. The first four describe the structural core of a harness; the last three describe the control plane around it. Compared with earlier six-component frameworks, Observability and Governance appear here as independent layers because, in production deployments, each has its own tooling stack and is owned by a different team.
+
+<div align="center">
+
+<img src="https://chenliu-1996.github.io/assets/harness_figure_taxonomy.png" width="80%"/>
+</div>
+
+
+## Timeline of Agent-Harness Systems
+
+The same shift is visible in the systems themselves. The ReAct era of 2022–2023 wrapped a single model loop with a while-loop, a prompt template, and a small tool dispatch table; AutoGPT and BabyAGI exposed the resulting failures, including execution runaway, context blowout, state loss, and unmonitored side effects, as infrastructure problems rather than prompt problems. Tool integration and multi-agent coordination from 2023–2024 added learned tool use (Gorilla, ToolLLM, Toolformer), role-playing organizations (CAMEL, ChatDev, MetaGPT, Mixture-of-Agents), the first agent benchmarks (SWE-bench, AgentBench, WebArena, GAIA), and the beginnings of protocol standardization (MCP, A2A). By 2025–2026 enough deployment experience had accumulated that “harness engineering” began to be named as a discipline of its own, accompanied by automated harness optimization and a wave of results in which only the harness was varied.
+
+<div align="center">
+
+<img src="https://chenliu-1996.github.io/assets/harness_figure_timeline.png" width="100%"/>
+</div>
+
+
+## Mapping Open-Source Projects
+
+The counts below reflect primary assignments in the current snapshot.
+
+<table>
+  <thead>
+    <tr>
+      <th align="left">Layer</th>
+      <th align="left">Scope</th>
+      <th align="right">Primary Projects</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td><span style="color:#7b61ff;">■</span>&nbsp;&nbsp;<b>E</b></td>
+      <td>Execution environment &amp; sandbox</td>
+      <td align="right">20</td>
+    </tr>
+    <tr>
+      <td><span style="color:#e9783a;">■</span>&nbsp;&nbsp;<b>T</b></td>
+      <td>Tool interface &amp; protocol</td>
+      <td align="right">12</td>
+    </tr>
+    <tr>
+      <td><span style="color:#d39b17;">■</span>&nbsp;&nbsp;<b>C</b></td>
+      <td>Context &amp; memory management</td>
+      <td align="right">9</td>
+    </tr>
+    <tr>
+      <td><span style="color:#3ca35c;">■</span>&nbsp;&nbsp;<b>L</b></td>
+      <td>Lifecycle &amp; orchestration</td>
+      <td align="right">47</td>
+    </tr>
+    <tr>
+      <td><span style="color:#2a9d8f;">■</span>&nbsp;&nbsp;<b>O</b></td>
+      <td>Observability &amp; operations</td>
+      <td align="right">15</td>
+    </tr>
+    <tr>
+      <td><span style="color:#9b3f99;">■</span>&nbsp;&nbsp;<b>V</b></td>
+      <td>Verification &amp; evaluation</td>
+      <td align="right">21</td>
+    </tr>
+    <tr>
+      <td><span style="color:#cf4d4d;">■</span>&nbsp;&nbsp;<b>G</b></td>
+      <td>Governance &amp; security</td>
+      <td align="right">14</td>
+    </tr>
+  </tbody>
+</table>
+
+## Looking for more?
+
+More information can be found on the [project page](https://picrew.github.io/LLM-Harness/) and the [Github repository](https://github.com/Picrew/awesome-agent-harness).
+
+
+## Citation
+
+If you use this survey, please cite:
+
+```bibtex
+@misc{li2026agentharness,
+  title={Agent Harness Engineering: A Survey},
+  author={Li, Junjie and Xiao, Xi and Zhang, Yunbei and Liu, Chen and Zhao, Lin and Liao, Xiaoying and Ji, Yingrui and Wang, Janet and Gu, Jianyang and Ge, Yingqiang and Xu, Weijie and Fang, Xi and Xu, Xiang and Zhao, Tianchen and Kim, Youngeun and Wang, Tianyang and Hamm, Jihun and Krishnaswamy, Smita and Huan, Jun and Reddy, Chandan},
+  url={https://openreview.net/pdf?id=eONq7FdiHa},
+  year={2026}
+}
+```