This content originally appeared on DEV Community and was authored by shantanu basu
As software engineers, we’re constantly juggling code reviews, PR descriptions and feedback. Recently I’ve been testing GitHub Models (public preview) — a new feature that lets you prototype, evaluate and use LLMs directly inside your GitHub repositories.
One experiment: automatically summarising every Pull Request using a prompt stored as code (.prompt.yml) and a GitHub Action. The Action calls the chosen model (GPT-4o, Claude, Mistral, etc.) and posts a concise summary right back into the PR as a comment.
Why it’s exciting:
• Prompts & parameters are version-controlled alongside code
• Side-by-side model comparisons to balance cost vs. quality
• Easy to prototype in the Playground, then integrate in CI/CD
This small automation is already making reviews faster and more focused.
Curious to see what else we can build when AI becomes a first-class citizen in our repos.
Have you tried GitHub Models yet? How are you using it?
GitHubModels, #GitHubActions, #PromptEngineering, #AIInDev, #DevOps, #OpenSource, #MachineLearning, #GitHubCopilot, #AIWorkflow
This content originally appeared on DEV Community and was authored by shantanu basu
shantanu basu | Sciencx (2025-09-16T18:10:24+00:00) 🚀 Exploring GitHub Models (Public Preview) for AI in Development Workflows🚀. Retrieved from https://www.scien.cx/2025/09/16/%f0%9f%9a%80-exploring-github-models-public-preview-for-ai-in-development-workflows%f0%9f%9a%80-2/
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