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博客园 - lightsong

LoRA unsloth比transformer库本身的微调有什么优点? offline-llms +++ transformer + peft 微调 Train and Fine-Tune Sentence Transformers Models Symmetric vs. Asymmetric Semantic Search Hierarchical Navigable Small Worlds (HNSW) Vision Transformer + BentoML ML Serving/编排工具 Introducing Gemma 3 270M: The compact model for hyper-efficient AI Utopia -- 企业世界模型 trustgraph semantica semantica vs graphti Industrial-Strength Natural Language Processing seata reference with springboot and other valuable demo outbox pattern with springboot Saga pattern with springboot 基于 Sentence Transformers 的具体应用案例 Vault with Keycloak as workload IAM Ontology Reasoning System ADR Claude Code的hook The AI-Native SDLC playbook Introduction to Dapper Introduction to FluentValidation Introduction to AutoFixture Introduction to FluentAssertions Understanding Return Types: IEnumerable, IReadOnlyCollection, and List Introduction to Refit Introduction to Carter
Harness engineering for coding agent users
lightsong · 2026-04-22 · via 博客园 - lightsong

Harness engineering for coding agent users

https://openai.com/zh-Hans-CN/index/harness-engineering/

https://www.anthropic.com/engineering/harness-design-long-running-apps

https://martinfowler.com/articles/harness-engineering.html

 Agent = Model + Harness

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 A well-built outer harness serves two goals: it increases the probability that the agent gets it right in the first place, and it provides a feedback loop that self-corrects as many issues as possible before they even reach human eyes. Ultimately it should reduce the review toil and increase the system quality, all with the added benefit of fewer wasted tokens along the way.

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出处:http://www.cnblogs.com/lightsong/ 本文版权归作者和博客园共有,欢迎转载,但未经作者同意必须保留此段声明,且在文章页面明显位置给出原文连接。