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Understand Prompt is a repository by Phodal Huang that serves as a structured exploration and summary of prompt engineering practices across coding, art, and writing contexts, especially in the era of AI models like StableDiffusion and ChatGPT. It’s part tutorial, part reflection: the author writes about how prompts work (for image generation, article generation, code auto-generation) and shares notebooks, examples, and insights into how to design effective prompts, iterate them, and integrate them into workflows. The material is both conceptual (why prompts matter, how to think of them) and practical (code notebooks, examples). It aims to elevate prompts from ad-hoc text inputs to a disciplined part of the toolchain, helping developers/artists/writers get more reliable results from AI models. The repository also acknowledges that prompt engineering is model-specific and evolving, and invites readers to adapt patterns rather than blindly copy.
Features
- Tutorials on prompt engineering for image, text, and code generation
- Jupyter notebooks with detailed examples and exercises
- Discussion of underlying model behaviours and how prompts steer them
- Practical templates and patterns for prompt design
- Guidance on iterating, debugging and refining prompts
- Insights into integrating prompts into workflows beyond one-off experimentation
Project Samples
