Improve Amazon Nova migration performance with data-aware prompt optimization

This article discusses a comprehensive approach for migrating generative AI workloads to Amazon Nova models, focusing on prompt optimization and performance improvement.

• Introduces a four-step workflow for model migration:
  1. Evaluate source model performance metrics
  2. Update prompts for Amazon Nova models
  3. Iteratively optimize prompts
  4. Conduct A/B testing and deployment
• Uses two prompt optimization techniques:
  1. Amazon Bedrock prompt optimization
  2. Data-aware optimization using DSPy framework
• Demonstrated performance improvements across three tasks:
  • Text summarization accuracy increased from 77.75% to 87.75%
  • Text classification accuracy improved to 87.5%
  • Question-answering semantic similarity rose from 52.71 to 57.15

The solution provides a systematic method for migrating and optimizing generative AI workloads to Amazon Nova models, with code and examples available on GitHub.