Migrate your prompts to new models and optimize them on Amazon Bedrock
AWS Machine Learning Jesse Manders ● Covered by 2 sources
Amazon Bedrock introduced Advanced Prompt Optimization, a tool that automatically optimizes prompts across up to 5 models simultaneously using reinforcement learning-style feedback loops. The system evaluates prompts against user-defined metrics (accuracy, F1 scores, or custom rubrics) and iteratively rewrites them, reporting quality scores, time-to-first-token latency, and inference costs for each model candidate. This replaces days of manual prompt tuning with a metrics-driven workflow, allowing teams to migrate to new models or improve performance on existing ones without manual re-evaluation cycles.
Why it matters
Amazon Bedrock Advanced Prompt Optimization optimizes your prompts for up to 5 models at once and compares original versus optimized performance across quality, latency, and cost. Migrate to a new model or improve your current one in minutes instead of weeks.
