Microsoft introduced a new granular policy-based approach in Windows 11 25H2 that allows administrators to selectively remove pre-installed Microsoft Store apps through Group Policy and mobile device management (MDM) solutions like Microsoft Intune, rather than only disabling the Store globally as earlier policies did. This feature addresses long-standing demands from IT professionals for a supported method to eliminate unwanted applications from Windows deployments.

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MPA Tools, created by Veles Software, is an endpoint management and troubleshooting solution for Windows environments that addresses gaps in Microsoft's existing system administration tools. The endpoint solution offers real-time visibility and workflow automation for Intune, Microsoft Configuration Manager (ConfigMgr), and Active Directory environments. A key feature is its ability to manage endpoints without agents.

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Microsoft's Intune August 2025 service release (2508) delivers major endpoint management enhancements, including granular app control targeting, Windows Autopilot OOBE patch integration, and Apple Declarative Device Management reporting capabilities. The update introduces multi-administrator approval workflows for critical operations and expands Linux support to Ubuntu 22.04/24.04 LTS while addressing enterprise security and governance requirements. However, administrators should be aware of reported performance issues with app control policies and several critical bugs affecting Win32 app filtering, iPad Air 2 management, and Linux device enrollment that may impact deployment strategies.

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Windows 11 25H2 has entered the Release Preview Channel as Microsoft's latest annual feature update. It marks a departure from traditional major releases by prioritizing stability over extensive new functionality. The update shares a servicing branch with Windows 11 24H2, meaning that no new features have been added. This approach represents Microsoft's focus on reliability following previous update challenges.

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Windows Backup for Organizations is Microsoft's new cloud-based solution that helps enterprises preserve user settings and Microsoft Store app lists, enabling rapid restoration during device transitions, resets, and migrations to new Windows environments. This article examines the technical requirements for backup and restore operations, including supported Windows versions and device configurations. The coverage includes three deployment methods through Group Policy, Microsoft Intune, and Configuration Service Provider (CSP) settings, along with their installation requirements. Operational aspects include the automated eight-day backup schedule, Out-of-Box Experience integration, and Conditional Access considerations that affect authentication during restore processes. The article also addresses limitations, regional availability restrictions, and critical user feedback.

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The Model Context Protocol (MCP) makes building intelligent integrations between large language models (LLMs) and cloud services easier. By combining MCP with Azure Functions, developers can expose serverless tools that LLMs can securely call in real time. This article describes how to set up Azure Functions as a custom MCP server, extend it with custom tools, and connect it to clients such as VS Code in Agent Mode.

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Microsoft has released Windows Terminal version 1.23 as a stable update, and version 1.24 as the latest preview, both bringing major improvements to the popular command-line tool. These versions introduce a completely new windowing architecture, expanded settings in the user interface, and other powerful enhancements for productivity and customization. In this article, we’ll explore what’s new in these updates and to how to install the latest stable and preview builds through Microsoft Store, winget, choco, and scoop.

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The Chorus app is built to send prompts to multiple AI models from different providers simultaneously. You can also query several search engines with each prompt. Both methods significantly reduce the risk of hallucinations. Update: I don't recommend getting a Chorus subscription. You'll have a hard time unsubscribing, and you won't receive any support.

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In my last post, I discussed Perplexity's aim to transform the familiar blinking web we've known for decades. It brings to mind the early days of Google, when many questioned the need for another search engine since AltaVista already did a good job. Although Comet appears to be just another Chromium-based web browser, the AI powering the browser under the hood has the same disruptive potential as Google's PageRank algorithm once did.

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Perplexity's new AI-powered Comet web browser, initially exclusive to Max subscribers at $200 monthly, is now accessible to Pro subscribers for $20. I tested it and am impressed—both by Perplexity's hypocrisy and Comet's truly innovative browsing experience. This post shares my rant against Perplexity, while my next post will praise Comet, the first browser on the battlefield in the new browser war.

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In my previous Ollama series post, I explained how to access self-hosted AI models in Ollama via HTTP. While this method provides convenient connectivity from different apps, it's only secure for on-premises Ollama hosts. For remote internet access, you can set up an SSH tunnel. Alternatively, you can securely connect from GitHub Copilot to your self-hosted AI models by using Microsoft's VS Code extension Remote - SSH.

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In my previous post in the Ollama series with OpenAI OSS models, I explained how to install Ollama on an Ubuntu EC2 instance. If you followed my guide, you now have everything set up to remotely access gpt-oss-20b on your self-hosted Ollama installation via HTTP. I will also showcase how to connect to remote AI models in VS Code using popular coding assistants like Cline and Roo Code, as well as through AI apps such as the local Ollama client, BoltAI, and Anything LLM.

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In my previous post, I covered the new features in Proxmox Backup Server 4.0. Released simultaneously, Proxmox Virtual Environment (VE) 9.0 also merits attention. It runs on Debian 13 Trixie with Kernel 6.14 and includes updated QEMU, LXC, ZFS, and Ceph versions. More significantly, it introduces modifications affecting storage management, networking, and high availability within your virtual setup. This article examines these updates more closely, providing commands and examples you can test on your own system.

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In my previous post, I explained why you might want to run OpenAI gpt-oss-20b or gpt-oss-120b on your own virtual machine and how to select an appropriate EC2 instance type. Today, I will show you how to install Ollama via script or snap on Ubuntu within an EC2 instance. Most steps can be adapted for other cloud providers, on-premises setups, or Linux distributions with minor modifications. I will also briefly discuss the benefits of running open-weight models on an EC2 instance with Ollama compared to Bedrock, SageMaker, vLLM, or Hugging Face Transformers.

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OpenAI recently released its first open-weight models, gpt-oss-20b and gpt‑oss-120b, which you can download and run with Ollama. If security and privacy are essential when using AI models, you might not want to use the vendor's chat UI or API. The most powerful AI models require significant computing power and memory, and many desktop devices cannot run these models. Although Ollama was not designed with remote connections in mind, it is still possible. In this series, I will explain how to install OpenAI's open-weight models using Ollama and connect to them remotely from various applications, including VS Code GitHub Copilot. In this first post, I will outline how to choose the right size for your virtual machine, using EC2 instance types in AWS as an example.

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Proxmox Backup Server (PBS) 4.0 is here with a new Debian 13 base, updated kernel, native S3-compatible storage, and useful improvements for managing backups. This release gives you more choices for where to store data and simplifies tasks like using removable drives or syncing to off-site locations. In this post, I will walk you through crucial new features, show the commands you can run, and provide a short upgrade checklist.

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The key new feature in the just-released AI Shell Preview 6 is run_command_in_terminal, among several new built-in tools that allow the AI model to run commands and review outputs directly in your PowerShell terminal. Additionally, AI Shell now supports local and remote MCP servers, transforming it into a versatile AI assistant across Windows, Mac, and Linux.

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The ChatGPT Gmail connector was first released in June 2025 for Plus, Pro, Team, Enterprise, and Edu users. However, because of alleged data protection rules, users in the European Economic Area, Switzerland, and the UK were excluded. OpenAI is now deploying connectors for Gmail, Google Calendar, Google Drive, and GitHub across Europe for all plans—notably after Anthropic released their MCP connectors weeks ago in Europe without such concerns, suggesting OpenAI's initial data protection claims were merely pretextual or that MCP has no priority status for the AI company. The announcement mentions Google Contacts, but this connector isn't yet accessible in my ChatGPT with a Plus plan. I tested the Gmail Connector, and following GPT-5's disastrous launch, it appears OpenAI released another flop immediately afterward.

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If you are working with PowerShell, you will often face the question: "Under which user is my script running?" In other words, you want to know who is logged in. Many admins use the whoami command on the Command Prompt (cmd). However, PowerShell provides native alternatives to whoami that give you the username and domain.

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