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Run an AI SRE Agent Entirely Inside AWS with Bedrock and S3: AURA

An on-call question returns the threshold and the escalation owner from your own runbooks, and the answer comes back without a call to anyone outside. AURA runs against Bedrock as its model provider, using Claude Sonnet 5 served by AWS in the same region. Authentication is the normal AWS credential chain: a profile on a laptop, an IAM role in EKS.

Debug AI agents wherever they run, from Slack bots to code review with Sentry's Agent Tracing

Agent Tracing shows the full execution path of an AI agent: the model call, every tool invocation and its arguments, token counts, cost, and the span where it broke. Same traces and spans you already use, with agent-specific attributes on top. Serge walks through three apps — a Next.js e-commerce agent using the AI SDK with a failing tool call, a Slack bot built with Eve that orders lunch, and a code review agent built with Flue over MCP.

Your Framework Doesn't Have to Be on Our List: How MCP Server Deployment Changes Everything

To deploy an application we haven't seen before, we need two things out of its repository. One is a Dockerfile that builds it. The other is a service definition saying what runs, which ports it listens on, which databases it needs, and what environment variables it expects. Customers arrive with a git URL, and we figure out the rest. We even do the tricky task of generating a Dockerfile if it doesn't already exist in the codebase. We've built a solution for this twice already.

Workspace now reads your tickets and automates the fix

IT teams don’t need another place to look for problems. They need a faster way to understand what is happening, decide what to do next, and act before disruption spreads. That has always been the promise of Workspace. It gives IT teams a conversational way to investigate issues, surface insights from Nexthink data, and understand what needs attention across the digital workplace. Now, Workspace is entering its next phase.

Advancing Semiconductor Manufacturing Through Intelligent Equipment Communication

In semiconductor manufacturing, reliable communication between production equipment and host systems is essential for maintaining efficiency, automation, and process consistency. As manufacturing environments become increasingly complex, standardised communication technologies have become critical in ensuring that equipment from different suppliers can operate together effectively. If you're looking to improve equipment connectivity and automation, explore solutions from SECS/GEM software providers to support reliable communication between manufacturing equipment and host systems.

12 Top SD-WAN Solutions for Growing Enterprises (2026)

Adding branches, cloud applications, contractors, and connected equipment changes the WAN problem. The network must steer traffic intelligently, preserve application quality during poor link conditions, and apply consistent controls without creating a separate operational stack at every location.

Backspaces, Retypes, and Idle Time: The Small Signals That Make a Draft Look Genuinely Written

A backspace that fixes a typo. A five-second pause before a hard sentence. A word typed, deleted, and replaced with a better one. A cursor that sits idle for two minutes while the writer stares at the screen. None of these moments feel significant while they are happening. They are the ordinary texture of writing, so automatic that most writers never notice them. But together, they are what separates a document that reads as genuinely drafted from one that reads as simply deposited.

How modern web development helps businesses scale without technical debt

A product that works today can quietly become a liability tomorrow. Teams ship fast, deadlines get met, and customers seem happy, but underneath, shortcuts pile up unnoticed. Then growth arrives, and the same codebase that once felt fast to build on starts fighting back. Suddenly, features take longer, bugs multiply, and every new hire needs weeks just to understand what is already there.

The EU Is Starting to Put Labels on the Synthetic Internet

It's getting harder and harder to distinguish between content produced by people and content produced by machines on the internet. AI can now create convincing articles, images, audio and video that may not be immediately recognized as being AI-generated. Europe has decided that this uncertainty cannot be left to users to deal with on their own. The EU AI Act introduces new transparency obligations, which are beginning to establish a more structured framework for identifying synthetic content.