Evaluating AI Agents: A production blueprint with Strands and AgentCore should be explained through that lens before any broad claim is made. This post was co-written with Motorway and the AWS Prototyping and AI Customer Engineering (PACE) team. Motorway, a UK-based online car marketplace, runs a daily auction where up to 8,000 dealers bid on up to 2,500 vehicles. The piece keeps the context, impact, and follow-up signals in view so readers do not stop at the headline.
What happened
This post was co-written with Motorway and the AWS Prototyping and AI Customer Engineering (PACE) team. The floor is firmer here because the story is anchored by an official source, not only by second-hand reaction. On the internet and business side, the useful question is how much this change shifts user behavior, operating cost, or competitive pressure.
Practical impact for readers
Motorway, a UK-based online car marketplace, runs a daily auction where up to 8,000 dealers bid on up to 2,500 vehicles. Motorway worked with AWS Prototyping and AI Customer Engineering (PACE) to build an AI-powered dealer stock search agent that transforms how dealers find vehicles, replacing hours of manual filtering with natural language queries.
Details worth verifying
Together, Motorway and AWS built an end-to-end evaluation pipeline that reduced incorrect results from 1 in 8 queries to 1 in 50 and cut issue detection time from few hours to few minutes.
Who should act or wait
The pipeline combines the Strands Agents SDK with Amazon Bedrock AgentCore, a fully managed service for deploying and operating AI agents at scale. In this post, you will learn how to build this pipeline for your own agents:.
What is still unclear
A companion repository provides a deployable blueprint that you can adapt for your own agents. Although the blueprint uses AWS services, the core principles are essential and system-agnostic requirements for any production-ready AI agent. These principles include the three-layer evaluation framework and the use of the pass^k metric for consistency.
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