Harness

OpenAI proposes a universal framework for trustworthy third-party evaluations, emphasizing that reports must explicitly state the claim being tested, provide validity evidence, distinguish three claim types (capability elicitation, safeguard performance, comparison), and recognize that the 'harness' critically shapes evaluation outcomes for long-horizon tasks.

本期周刊以‘AI次方变革’为核心隐喻，系统串联杨斌的组织心智重构、Karpathy的Software 3.0范式、Demis的AGI三缺口，揭示AI已从‘+AI’工具叠加迈入底数质变驱动的指数级重构阶段。

2026 will be the year of AI Harness. Using engineering methods like guardrails, validation, and automation processors, unreliable AI Agents can be transformed into stable, controllable systems without modifying Prompts, marking key infrastructure for AGI.

Ordinary people should start with small tasks and use AI to improve efficiency, rather than being overly anxious about its impact.

LangChain introduces Managed Deep Agents, a customizable agent harness architecture supporting complex real-world tasks via execution environment, context management, delegation, and human-in-the-loop capabilities.

Leading AI companies are shifting from pure model development to end-to-end agent systems, with OpenAI, AI21, and DeepSeek all forming Agent/Harness teams—marking a paradigm shift from ‘models as product’ to ‘systems as product’.

This article introduces the Harness framework, an AI tool designed to automatically generate paper charts through a collaborative workflow involving designers, executors, validators, and revisionists.

DeepSeek demonstrates long-term thinking by adopting simple pricing to attract developers and gather real-world feedback data.

Tejas Kumar demonstrates through a GPT-3.5 Turbo browser agent case how unconstrained AI agents fail by hallucinating success when hitting login pages, showcasing the critical role of harness testing frameworks in ensuring agent reliability.

文章介绍了如何利用Skill Factory平台结合Harness CI/CD工具链进行自动化开发和部署，但内容较为基础，缺乏深度和新颖性。

Dewu improved SQL compliance to 95% using its self-developed warehouse governance platform Harness, enabling automated review, rule library expansion, and cross-team collaboration, significantly reducing data errors and boosting development efficiency.

The article cannot be accessed due to environmental issues and lacks sufficient technical depth on medical AI.

This approach enhances code debugging efficiency by using two AI agents in different frameworks, though the content is brief lacks technical details.