- How the UK Amazon Quick User Group grew in 2026
The UK Amazon Quick User Group's 2026 roundup: three quarterly meetups, 150+ attendees, and customer stories from Arriva, Carsa, and Propulse Lab on using agentic AI and Amazon Quick to turn data into faster decisions, higher satisfaction, and scalable growth.
- Microsoft Research Focus – Edition #97
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Foc…
- Building intent-driven UI testing with Amazon Nova Act
Epsilon's Agentic Platform team delivers UI testing as a managed, multi-tenant service built on Amazon Nova Act and Amazon Bedrock AgentCore Browser Tool. Tests are written in plain English and run on browsers managed by AWS, giving every product team resilient, intent-driven …
- Build a repeatable PHP-to-Java migration engine with Kiro
Turn a PHP-to-Java migration from a one-time leap of faith into a measurable, repeatable process with Kiro. This post walks through a reusable engine: a mechanical discovery scanner and an eight-phase, parity-first workflow that treats the original PHP application as the speci…
- Claude Code Best Practices
A blog post covering tips and tricks that have proven effective for using Claude Code across various codebases, languages, and environments.
- Scaling Managed Agents with stable interfaces
Harnesses encode assumptions that go stale as models improve. See how Managed Agents is built around interfaces that stay stable as harnesses change.
- Expanding our partnership with GSA to bring Claude to all levels of government
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
- An updated Model Spec for more capable and beneficial AI
OpenAI’s updated Model Spec outlines five core values to guide more capable AI toward sound judgment, human agency, and faithfulness to human intent.
- Lend and borrow resources across teams with AWS Batch’s quota management for SageMaker Training jobs
AWS Batch quota management is a new scheduling capability you can use to divide GPU capacity into quota shares per team or project, automatically lend idle capacity across shares, and use preemption to run your highest-priority SageMaker Training jobs first, all without manual…
- How MoEngage turned over 400 APIs into agent tools with AgentCore Gateway
MoEngage turned roughly 400 private REST APIs across 7 AWS Regions into permission-scoped agent tools with Amazon Bedrock AgentCore Gateway. No per-service MCP servers, no public endpoints, and no 400-tool context bloat. See how OpenAPI specs, Cedar policies, and managed Amazo…
- Speeding up language models for travel applications
Two optimization techniques, when combined, can significantly improve a model’s speed and cost effectiveness without sacrificing quality.
- ChatGPT Enterprise at Zendesk: Putting Company Data to Work
“We have about 600 applications that have been built by different people in the company.” At Zendesk, teams across sales, marketing, and operations are building applications for their own work. ChatGPT Enterprise is available to every employee, and business users are asking qu…
- Accelerate agentic AI with NVIDIA Nemotron models on Amazon EKS and SageMaker HyperPod EKS
NVIDIA Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts model that pairs reasoning and tool use with multimodal understanding. This post explores its architecture and use cases, then shows how to deploy it on Amazon EKS, EKS Auto Mode, and Amazon SageMaker HyperPod…
- Into the Omniverse: How Developers Turn Ideas Into Simulations With Frontier AI Agents
Turning a simulation idea into a working application means assembling assets, connecting physics and rendering, and checking that the scene behaves as intended. Developers are combining frontier AI models with NVIDIA Omniverse libraries to help carry out that work — building a…
- Catching Bugs Before They Land: JiTTesting’s Human-on-the-Loop Approach at Full Scale
Over the last year we’ve been sharing our work leveraging large language models to catch bugs on the fly — a novel approach we call Catching Just-in-Time Tests (JiTTests). Now, we’re sharing the results and positive impact we’ve seen with Catching JiTTests deployed into produc…
- Can Frontier Models See Past a Decoy? Elorian Tests Visual Reasoning
A new decoy counting benchmark exposes a gap between seeing and reasoning. Elorian’s Glimpse tries to bridge it by thinking with images.