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Source channel @githubtrending · Post #15180 · Sep 29

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#other You can use a set of markdown files to guide AI coding assistants step-by-step in building software features. This method breaks down your feature idea into a clear Product Requirement Document (PRD), then into detailed tasks, and finally lets the AI work on each task one at a time while you review and approve progress. This structured workflow helps you keep control, avoid errors, and track progress visually, making AI-assisted development more reliable and manageable. It works with many AI tools and improves the quality and clarity of AI-generated code, saving you time and reducing frustration during complex feature development. https://github.com/snarktank/ai-dev-tasks

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@githubtrending · Post #14909 · 07/03/2025, 02:30 PM

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#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm

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