Microsoft’s POML offers a declarative way to manage complex instructions by using XML-like tags and CSS-style rules for prompt design. By separating content from stylistic parameters like tone and token limits, the system promotes modularity, reusability, and improved maintainability compared to manual string concatenation.
- Requires Python 3.10 or higher
- Facilitates cleaner version control through structured diffs in pull requests
- Enables non-engineers like product managers to contribute using familiar syntax styles
- Allows for model-agnostic structures that separate intent from specific API formatting quirks
- Requires Python 3.10 or higher
- Facilitates cleaner version control through structured diffs in pull requests
- Enables non-engineers like product managers to contribute using familiar syntax styles
- Allows for model-agnostic structures that separate intent from specific API formatting quirks
Yuge Zhang writes about Prompt Orchestration Markup Language (POML), a framework designed to manage complex prompt structures and diverse data types for Large Language Models. It uses component-based markup and specialized tags to integrate documents, tables, and images while employing a CSS-like styling system to decouple content from its presentation format. This approach aims to reduce formatting sensitivity and improve the reliability of prompts when interacting with models.
- Validated through PomLink application integration and TableQA accuracy tests.
- Includes templating for dynamic prompt generation and an SDK/IDE toolkit.
- Designed to enhance version control and collaboration in development workflows.
- Validated through PomLink application integration and TableQA accuracy tests.
- Includes templating for dynamic prompt generation and an SDK/IDE toolkit.
- Designed to enhance version control and collaboration in development workflows.
Yuge Zhang et al. write about Prompt Orchestration Markup Language (POML), a markup language designed to bring structure, maintainability, and versatility to prompt engineering for Large Language Models. By employing an HTML-like syntax, POML modularizes components such as roles and tasks while decoupling content from presentation via a CSS-inspired styling system.
- Includes built-in templating with support for variables, loops, and conditionals
- Provides SDKs for Python and Node.js integration into application workflows
- Offers a Visual Studio Code extension featuring syntax highlighting and real-time previews
- Supports seamless embedding of external data sources like images and spreadsheets via specialized components
- Includes built-in templating with support for variables, loops, and conditionals
- Provides SDKs for Python and Node.js integration into application workflows
- Offers a Visual Studio Code extension featuring syntax highlighting and real-time previews
- Supports seamless embedding of external data sources like images and spreadsheets via specialized components
Security startup XBOW discovered critical flaws in Bing Image Search that allow specially crafted SVG files to execute commands with high privileges, including NT AUTHORITYSYSTEM on Windows and root on Linux. These vulnerabilities, identified as CVE-2026-32194 and CVE-2026-32191 (both rated 9.8 CVSS), exploit the way image processing workers utilize ImageMagick delegates to handle file conversion processes.
* The flaws allow for remote code execution via both direct SVG uploads and by providing a URL of a malicious SVG fetched by Bingbot.
* Microsoft has already implemented server-side fixes, meaning no user action is required to resolve the issue.
* The exploit works by using an image reference within the SVG that triggers shell commands when processed through enabled delegates.
* Experts recommend disabling ImageMagick delegates and restricting supported file formats like SVG or EPS to mitigate this class of vulnerability.
* The flaws allow for remote code execution via both direct SVG uploads and by providing a URL of a malicious SVG fetched by Bingbot.
* Microsoft has already implemented server-side fixes, meaning no user action is required to resolve the issue.
* The exploit works by using an image reference within the SVG that triggers shell commands when processed through enabled delegates.
* Experts recommend disabling ImageMagick delegates and restricting supported file formats like SVG or EPS to mitigate this class of vulnerability.
The expiration of Microsoft’s 2011 Secure Boot certificates in 2026 presents potential challenges for Linux users on consumer hardware. While existing installations are unlikely to fail immediately when dates roll over, new distributions or updates may face boot issues unless firmware is updated with the newer 2023 keys. To maintain security and compatibility, users should update their system BIOS/UEFI via vendor tools or fwupd and verify readiness by testing current distribution ISOs on live USB sticks. Disabling Secure Boot entirely to avoid these hurdles is discouraged as it increases vulnerability to rootkits.
>"On many systems, you can use Linux's firmware update stack, fwupd, to handle this from within your distro. To take this step, run the following commands as the root user:"
>
>`fwupdmgr refresh && fwupdmgr get-updates && fwupdmgr update`
>"On many systems, you can use Linux's firmware update stack, fwupd, to handle this from within your distro. To take this step, run the following commands as the root user:"
>
>`fwupdmgr refresh && fwupdmgr get-updates && fwupdmgr update`
This article explores the critical architectural decision of where to store conversation history when building AI agents. It examines how different storage strategies impact user experience, privacy, cost, and portability. The author compares service-managed versus client-managed storage models and details how modern APIs support both linear threads and forking/branching capabilities.
Key topics include:
* Service-Managed vs. Client-Managed storage tradeoffs
* Linear (single-threaded) vs. Forking-capable conversation models
* Strategies for context window management and compaction such as truncation, summarization, and sliding windows
* How Microsoft Agent Framework abstracts these patterns using AgentSession and ChatHistoryProvider to ensure provider-agnostic code
* Practical implementation examples for the Responses API in different modes
Key topics include:
* Service-Managed vs. Client-Managed storage tradeoffs
* Linear (single-threaded) vs. Forking-capable conversation models
* Strategies for context window management and compaction such as truncation, summarization, and sliding windows
* How Microsoft Agent Framework abstracts these patterns using AgentSession and ChatHistoryProvider to ensure provider-agnostic code
* Practical implementation examples for the Responses API in different modes
Jason Donenfeld, the creator of the popular open-source WireGuard VPN software, has been locked out of his Microsoft developer account. This unexpected suspension prevents him from signing drivers and shipping critical software updates to Windows users. The issue stems from a mandatory account verification process within Microsoft's Windows Hardware Program, which has suspended accounts that failed to complete verification by a specific deadline, often without prior notification to the developers. This situation mirrors recent troubles faced by other prominent open-source projects like VeraCrypt and Windscribe, highlighting a growing tension between Microsoft's security verification requirements and the operational needs of independent software maintainers.
This article examines the development of Microsoft’s Azure SRE Agent, designed to mitigate operational toil in mission-critical environments. By utilizing an "agentic workflow" of specialized AI agents, Microsoft has integrated automation across the entire software development lifecycle. This human-AI partnership has autonomously resolved over 35,000 incidents and saved more than 50,000 developer hours, accelerating root cause analysis and mitigation while maintaining rigorous governance and human oversight.
WebMCP is a new technology that allows AI agents to interact with web pages more directly. It works by turning web pages into MCP (Model Context Protocol) servers via a Chrome extension. This enables agents to understand and manipulate web content in a structured way, potentially improving efficiency and user experience.
The technology, backed by Google and Microsoft, is designed to work alongside human users, allowing them to ask agents questions about the page they are viewing. WebMCP uses a Declarative API for standard actions and an Imperative API for more complex tasks. Early experiments demonstrate the ability to query web pages and receive structured data back.
The technology, backed by Google and Microsoft, is designed to work alongside human users, allowing them to ask agents questions about the page they are viewing. WebMCP uses a Declarative API for standard actions and an Imperative API for more complex tasks. Early experiments demonstrate the ability to query web pages and receive structured data back.
Microsoft's Phi-4-Reasoning-Vision-15B model challenges the trend of ever-larger AI models by demonstrating strong reasoning capabilities with a comparatively compact size. Trained on curated reasoning data, it aims to achieve performance without the massive compute costs associated with frontier models. The model supports multimodal tasks, combining text and image understanding, and offers flexible reasoning modes for different workloads. This research highlights the importance of data quality and training strategy, suggesting that smarter training techniques can be as impactful as simply increasing model size, particularly for AI agents and practical deployments.
