Why your team isn't getting faster with AI
Hitting your PR count feels productive, but maybe it's not. Sometimes you have to slow down to 10x.
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Business metrics in Grafana Cloud: Get an AI assist to help securely analyze your data
For today's modern businesses, the data landscape demands security and flexibility. You need to connect your observability platform to rich, proprietary datasets that often reside in private networks without compromising security or managing complex network infrastructure. You may also face an extra layer of complexity in order to effectively query and visualize that data. Luckily, modern artificial intelligence tools have made these previously complicated processes much simpler.
The Atlassian Rovo MCP Server now supports Bitbucket Cloud
The Atlassian Rovo Model Context Protocol MCP Server now supports Bitbucket Cloud. AI clients like Claude, ChatGPT, Cursor, and VS Code can now browse repositories, create commits, open pull requests, and check pipeline results, all through the same secure MCP connection that already works with Jira and Confluence.
Closing the Mobile Visibility Gap: Extending DEX to Mobile
In 2026, I think it’s safe to say that most mobile devices in enterprise organizations aren’t purchased just for their ability to make calls. And for millions of employees, especially frontline workers, their primary device isn’t even a laptop anymore - it’s a smartphone or tablet. Yet, mobile device insights have largely remained a blind spot for IT.
Not All Agents Are Created Equal: Getting Agentic AI Right for IT
Three months ago, a CIO told me her organization had “already deployed agents.” Her endpoint team assumed she meant the telemetry clients on every managed laptop. Her service desk thought she meant AI chatbots. Meanwhile, her security architect heard “autonomous decision-making.” They were all right and all talking past each other. This is the agent confusion problem.
Where Most Operational Waste Comes From-and How AI Automation Cuts It
Most operational waste comes from fragmented workflows rather than individual performance constraints. An incident begins long before any fix is applied. Alerts trigger, tickets open, and engineers start reconstructing context across systems that were never designed to operate as one. Logs, metrics, past incidents, and runbooks sit in separate tools, each requiring manual lookup, interpretation, and validation before any decision can be made.
Episode 9 - AI, Enterprises, and the Law
In this episode of The Intelligent Enterprise, host Tom Stoneman takes us inside the different ways that AI is being utilized in the practice of law. In this episode, Tom is joined by Vintee Mishra, an attorney who’s currently part of the Commercial Contracting Organization at Navy Federal Credit Union, and has previously occupied supporting roles at Tata Consultancy Services, Cisco, First Technology Credit Union, and Moody’s Analytics.
What Native Audio in AI Video Actually Means for the Future of Content
In 2026, the arrival of native audio has officially ended the silent film era of generative AI. For years, creators had to hunt for sound effects and manually align voiceovers in post-production, but the new standard is simultaneous generation. Native audio means the AI no longer simply adds sound to a finished clip. Instead, models like Seedance 2.0 on the Higgsfield platform generate audio and video together in a single mathematical pass. This shift from fragmented tools to a unified multimodal architecture is fundamentally changing how content is produced.
Why Face Swap Is the Smartest Way to A/B Test Visual Creatives Without a Reshoot
A/B testing has always been a cornerstone of performance marketing. Marketers test headlines, tweak CTAs, adjust layouts, and refine copy continuously. These changes are easy to implement and quick to evaluate. Over time, even small improvements compound into measurable gains. But visual creatives have always been different. They are harder to test, slower to produce, and significantly more expensive to iterate. As a result, one of the most influential elements in a campaign often goes under-tested.
Responsible AI Writing: How Teams Use AI Tools Without Losing Authenticity
AI writing tools have made content creation significantly faster. Drafts that once required hours can now be produced in minutes, helping teams scale documentation, communication, and content production. However, speed alone does not guarantee quality. As AI-generated content becomes more common, many teams are finding that raw output often lacks clarity, consistency, or the tone required for professional use.