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Select Topic AreaQuestion BodyI’ve been experimenting with GitHub Models for the first time, and I’m trying to understand the best way to run a basic AI workflow. I’m especially curious about how to structure prompts effectively, how to test model outputs, and how to organize everything inside a repository so the workflow feels clean and beginner-friendly. If anyone has simple examples, tips, or guidance, I’d love to learn from your experience. If you want a different vibe, here are two more examples you could use. |
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Exploring GitHub Models for your first AI project is a fantastic initiative! To make the most of it, I recommend:
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What a “basic AI workflow” usually looks like
At a high level, most simple AI workflows follow this pattern:
Input – text you want the model to work on
Prompt – instructions + context you give the model
Model call – sending the prompt to a model (via GitHub Models or API)
Output – model’s response
Evaluation – checking if the output is good, consistent, and useful
You don’t need anything fancy at first—clarity beats complexity.