Migrate your prompts to new models and optimize them on Amazon Bedrock

This article introduces Amazon Bedrock Advanced Prompt Optimization, a new tool that automates prompt migration and optimization across multiple models using reinforcement learning-style feedback loops.

• Optimize prompts for up to 5 models simultaneously with quality, latency, and cost comparisons in a single job
• Three evaluation modes: AWS Lambda functions for concrete metrics, LLM-as-a-Judge for open-ended tasks, and steering criteria for brand voice and format
• Supports multimodal inputs including images and PDFs for document analysis and visual question answering tasks
• Real-world results show quality improvements ranging from +35% to +143% across summarization, function calling, and document VQA tasks
• Available via AWS console, boto3 SDK, and API with results including optimized prompts, evaluation scores, TTFT, and cost estimates
• Eliminates days of manual prompt iteration by providing metrics-driven workflow with quantified trade-offs between quality, latency, and cost

Advanced Prompt Optimization removes the manual bottleneck from prompt engineering at scale, enabling teams to migrate to newer models confidently and optimize performance without extensive trial-and-error cycles.