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GitHub MCP Registry: The fastest way to discover AI tools

GitHub rolled out theMCP Registry—a hub for findingModel Context Protocol (MCP) serverswithout hunting through scattered corners of the internet. No more siloed lists or mystery URLs. It's all in one place now. The goal? Cleaner access to AI agent tools, plus a path towardself-publishing, thanks to .. read more  

GitHub MCP Registry: The fastest way to discover AI tools
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Nine HTTP Edge Cases Every API Developer Should Understand

Last February, CVE-2024-26141 punched a nasty hole inRack's Range header parsing. All versions since 1.3.0 are exposed. The bug let attackers blow up memory usage and responses—classic denial-of-service—just by crafting bloated Range headers. The trick? Custom file download handlers. They skip the u.. read more  

Nine HTTP Edge Cases Every API Developer Should Understand
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A stateful browser agent using self-healing DOM maps

A stateful browser agent using self-healing DOM maps is now available. Users describe tasks, Agent4 performs them, creates reusable workflows from interactions, and executes instantly on subsequent requests. Under the hood, it checks for known maps in a vector DB, patches them if needed, and self-he.. read more  

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Supply Chain Risk in VSCode Extension Marketplaces

Wiz dug up 550+ leaked secrets buried in 500+ public VSCode extensions—including 130+ live access tokens forVSCode MarketplaceandOpenVSX. That’s a wide-open door to supply chain attacks through auto-updates. Microsoft reacted fast: dumped the breached tokens, rolled outpre-publish secret scanning, a.. read more  

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Foreign hackers breached a US nuclear weapons plant via SharePoint flaws

UnpatchedSharePoint flaws(CVE-2025-53770, CVE-2025-49704) cracked open theKansas City National Security Campusin July. IT systems tied to 80% of U.S. non-nuclear weapons parts got compromised. Attackers—likely state-backed, Russian or Chinese—moved fast, hitting the zero-day RCE and spoofing bugs ju.. read more  

Foreign hackers breached a US nuclear weapons plant via SharePoint flaws
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Python 3.14 Is Here. How Fast Is It?

Python 3.14 lands with a ~27% speed jump over 3.13, keeping the post-3.11 momentum alive. The big news: the newfree-threading interpreter—no GIL—now hits up to3.1x fasterthan regular CPython in multi-threaded, CPU-heavy benchmarks. That’s up from 2.2x in 3.13. Less shiny: theJIT interpreterstill can.. read more  

Python 3.14 Is Here. How Fast Is It?
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Sora 2 in Azure AI Foundry: Create videos with responsible AI

OpenAI’sSora 2just dropped intopublic previewvia theAzure AI FoundryAPI. It’s a multimodal video model aimed at serious use—enterprise safety, API-ready, built for scale. Azure didn’t stop there. It bundled inGPT-image-1,Flux 1.1, andKontext Pro, pulling together a full-gen stack under one roof... read more  

Sora 2 in Azure AI Foundry: Create videos with responsible AI
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How Microsoft Evaluates LLMs in Azure AI Foundry: A Practical, End-to-End Playbook

Microsoft’s Azure AI Foundry just released a proper workflow for putting LLMs through their paces. Thinkoffline/online tests,human-in-the-loop checks,automated scoring, and evencustom evaluators—all wired into one system. At the heart of it: the newAzure AI Evaluation SDK. You can run it locally whi.. read more  

How Microsoft Evaluates LLMs in Azure AI Foundry: A Practical, End-to-End Playbook
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Structured Vibe Coding: A Smarter Way to Build AI Agents with GitHub Copilot

A fresh approach calledstructured vibe codingblends human-style team habits with AI workflows. Specs, GitHub Issues, and Copilot now pull agents into the loop like actual teammates. Powered byGitHub Copilot Coding AgentsandAzure AI Foundry, devs can run full AI-driven sprints—spec to PR—right inside.. read more  

Structured Vibe Coding: A Smarter Way to Build AI Agents with GitHub Copilot
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OpenAI Needs $400 Billion In The Next 12 Months

OpenAI, Broadcom, NVIDIA, and AMD say they’ll deploy10GWof AI compute by end of 2026. That includes custom chips and slews of 1GW data centers. What they didn’t say: where, when, or how. No sites named. No shovels in dirt. OpenAI alone aims for250GW by 2033—a moonshot that needs$400Bin the next 12 m.. read more  

OpenAI Needs $400 Billion In The Next 12 Months
Flask is an open-source web framework written in Python and created by Armin Ronacher in 2010. It is known as a microframework, not because it is weak or incomplete, but because it provides only the essential building blocks for developing web applications. Its core focuses on handling HTTP requests, defining routes, and rendering templates, while leaving decisions about databases, authentication, form handling, and other components to the developer. This minimalistic design makes Flask lightweight, flexible, and easy to learn, but also powerful enough to support complex systems when extended with the right tools.

At the heart of Flask are two libraries: Werkzeug, which is a WSGI utility library that handles the low-level details of communication between web servers and applications, and Jinja2, a templating engine that allows developers to write dynamic HTML pages with embedded Python logic. By combining these two, Flask provides a clean and pythonic way to create web applications without imposing strict architectural patterns.

One of the defining characteristics of Flask is its explicitness. Unlike larger frameworks such as Django, Flask does not try to hide complexity behind layers of abstraction or dictate how a project should be structured. Instead, it gives developers complete control over how they organize their code and which tools they integrate. This explicit nature makes applications easier to reason about and gives teams the freedom to design solutions that match their exact needs. At the same time, Flask benefits from a vast ecosystem of extensions contributed by the community. These extensions cover areas such as database integration through SQLAlchemy, user session and authentication management, form validation with CSRF protection, and database migration handling. This modular approach means a developer can start with a very simple application and gradually add only the pieces they require, avoiding the overhead of unused components.

Flask is also widely appreciated for its simplicity and approachability. Many developers write their first web application in Flask because the learning curve is gentle, the documentation is clear, and the framework itself avoids unnecessary complexity. It is particularly well suited for building prototypes, REST APIs, microservices, or small to medium-sized web applications. At the same time, production-grade deployments are supported by running Flask applications on WSGI servers such as Gunicorn or uWSGI, since the development server included with Flask is intended only for testing and debugging.

The strengths of Flask lie in its minimalism, flexibility, and extensibility. It gives developers the freedom to assemble their application architecture, choose their own libraries, and maintain tight control over how things work under the hood. This is attractive to experienced engineers who dislike being boxed in by heavy frameworks. However, the same freedom can become a limitation. Flask does not include features like an ORM, admin interface, or built-in authentication system, which means teams working on very large applications must take on more responsibility for enforcing patterns and maintaining consistency. In situations where a project requires an opinionated, all-in-one solution, Django or another full-stack framework may be a better fit.

In practice, Flask has grown far beyond its initial positioning as a lightweight tool. It has been used by startups for rapid prototypes and by large companies for production systems. Its design philosophy—keep the core simple, make extensions easy, and let developers decide—continues to attract both beginners and professionals. This balance between simplicity and power has made Flask one of the most enduring and widely used Python web frameworks.