# Treating Prompts Like Code: Building CI/CD for LLM Workflows on AWS
📰 Dev.to · Dhananjay Lakkawar
Learn to treat prompts like code and build CI/CD for LLM workflows on AWS for efficient AI development
Action Steps
- Create an AWS account and set up an IAM user with necessary permissions
- Build a CI/CD pipeline using AWS CodePipeline and CodeBuild to automate prompt testing and deployment
- Configure AWS CodeCommit to version control your prompts and track changes
- Integrate AWS CodeGuru to review and optimize your prompt code
- Deploy your LLM model to AWS SageMaker for scalable inference
Who Needs to Know This
AI engineers and DevOps teams can benefit from this approach to streamline their LLM workflow development and deployment
Key Insight
💡 Versioning and automating prompts is crucial for efficient LLM development and deployment
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🚀 Treat prompts like code and automate your LLM workflow with CI/CD on AWS! 💻
Key Takeaways
Learn to treat prompts like code and build CI/CD for LLM workflows on AWS for efficient AI development
Full Article
If you look at the codebase of an early-stage AI startup, you will almost always find a file named...
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