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. 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.
Motorway and AWS built an AI-powered dealer stock search agent that replaces manual filtering with natural language queries.
Two-phase evaluation strategy: build-time testing with strands-agents-evals and production monitoring with Amazon Bedrock AgentCore Evaluations.
Amazon Bedrock AgentCore optimization surfaces silent behavioral failures in production AI agents: the ones that pass every health check but still deliver wrong outcomes. Learn how insights discovers, explains, and ranks failure patterns across sessions so you can fix the highest-impact issues first.
Silent failures cause incorrect outcomes without error signals, such as unexecuted orders or incorrect inventory status.
AgentCore analyzes session traces to detect 11 behavioral failure types, including hallucination and incorrect actions.
Classic retrieval fails on multi-part, comparative, and exploratory questions. Agentic retrieval addresses this by using a planning loop with a foundation model to decompose queries, retrieve per intent, and evaluate sufficiency. This post covers why it's needed, how the AgenticRetrieveStream API works, and when to choose it over the standard Retrieve API.
Single-shot retrieval struggles with multi-intent queries.
Agentic retrieval uses a foundation model to plan, retrieve per intent, and iterate.
This paper presents a benchmark to evaluate whether AI models execute corrupted values from untrusted documents across ten consequential workflows. All tested models showed susceptibility, with attack success rates ranging from 1.7% to 63.3%. With ActionRail protection, zero manipulated actions reached the tool and zero false positives occurred.
New benchmark for value-poisoning attacks on AI agents.
Eight models from four providers tested; all were vulnerable.
An analysis of Linus Torvalds' stance on AI in Linux kernel development, arguing that while his position is reasonable, the AI hype machine is weaponizing his words to silence critics. The article discusses rhetoric, textual analysis (exegesis vs. eisegesis), and the 'King's Council' pattern.
Linus Torvalds states Linux is not anti-AI; critics may fork or leave.
Author finds Linus' stance reasonable but warns against weaponizing his words.
OpenAI is rolling out ChatGPT Health to all US users on Thursday, allowing users to connect medical records and health-tracking data. VP claims models reason better than clinicians, but health lead later tempers the claim. Meanwhile, a pastor sues OpenAI over allegedly dangerous medical advice from ChatGPT.
ChatGPT Health launches for all US users aged 18+ across free, Go, Plus, and Pro plans.
OpenAI executive initially claims model reasoning surpasses clinician level, but is later tempered by health lead.
Jefferies built an agentic AI trade assistant using Strands Agents, Amazon Bedrock, and MCP tools to enable traders to query data via natural language, reducing reliance on IT and accelerating insights.
Jefferies deployed an AI trade assistant integrating Strands Agents, Amazon Bedrock, and MCP tools.
Traders can ask natural language questions and receive SQL-generated insights and visualizations in real time.
This post shows you how to build multi-Region carrier performance dashboards in QuickSight using Highcharts custom visualizations to overcome native chart limitations. You will learn how to maintain data sovereignty across AWS Regions while creating unified visualizations through the QuickSight federated dataset capability. The solution includes production-ready chart configurations and addresses security, compliance, and scalability requirements.
Use Highcharts custom visualizations in Amazon QuickSight to overcome native chart limitations for multi-region carrier performance dashboards.
Maintain data sovereignty across AWS Regions using federated datasets.