Amazon Bedrock's New Prompt Tool Lets You Test and Migrate Models Without the Guesswork

Amazon Bedrock just released a tool that could save engineering teams hours of trial and error when tuning prompts for large language models. Called Advanced Prompt Optimization, it lets you compare original and optimized prompts across up to five models at once - handy if you're migrating to a newer model or just trying to squeeze more accuracy out of your current one.

The process is straightforward. You upload a JSONL file containing your prompt template, sample user inputs, ground truth answers, and an evaluation metric. The tool then runs a feedback loop: it sends your prompts to the chosen models, scores the responses using your specified metric, and rewrites the prompts to improve performance. You get back the original and final prompts, along with evaluation scores, cost estimates, and latency data.

You can choose from three evaluation methods: a Lambda function for concrete metrics like accuracy or F1 score; an LLM-as-a-judge with a custom rubric for open-ended tasks like summarization; or natural-language steering criteria for qualities like brand voice or safety constraints. The tool also supports multimodal inputs - PNG, JPG, and PDF files - making it useful for document and image analysis workflows.

Available today in multiple AWS regions, pricing is based on the same per-token inference rates as regular Bedrock usage. For teams juggling multiple models or struggling with prompt engineering, this could be a practical way to standardize and speed up the process.

Source: AWS