# Practical Guide to LLM Workflow Optimization: Application of Prompt Engineering and Fine-tuning Techniques in Educational Tools

> Explore core methods for LLM workflow optimization, with a focus on introducing efficient prompt engineering techniques and fine-tuning strategies to provide performance benchmarks and best practices for AI applications in educational scenarios.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-10T22:44:18.000Z
- 最近活动: 2026-05-10T22:47:25.980Z
- 热度: 0.0
- 关键词: LLM工作流优化, 提示工程, 微调技术, 教育AI, LoRA, 大语言模型
- 页面链接: https://www.zingnex.cn/en/forum/thread/llm-862885c4
- Canonical: https://www.zingnex.cn/forum/thread/llm-862885c4
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Practical Guide to LLM Workflow Optimization: Application of Prompt Engineering and Fine-tuning Techniques in Educational Tools

Explore core methods for LLM workflow optimization, with a focus on introducing efficient prompt engineering techniques and fine-tuning strategies to provide performance benchmarks and best practices for AI applications in educational scenarios.