Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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MSNBC’s website is now MS.NOW

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A few months after announcing its big name change, MSNBC is getting a new domain featuring its new name: ms.now. It features essentially the same layout as the old MSNBC website, but with a fresh coat of paint, including the new MS NOW flag logo — the old MSNBC peacock is gone.

The new website is launching as part of MS NOW’s independent newsroom, which began separating from NBC News in October. The split is the result of Comcast’s decision to spin off its cable channels, including MSNBC. With the new domain name and website refresh, MS NOW is leaving behind one of its clearest ties to NBC.

MS NOW seems to have missed its opportunity to get msnow.com, which is currently occupied by a mostly empty page referencing “Motorized Snow vehicles.” Fortunately for them, domains with the .now extension went on sale about a year ago.

It’s somewhat ironic that MS NOW is keeping the “MS” part of its name, though, considering Microsoft sold its stake in the brand over 10 years ago. Of course, it no longer stands for Microsoft — now it’s “My Source for News, Opinion, and the World.”

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alvinashcraft
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What IT Pros Can Expect at Microsoft Ignite 2025

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Another year has passed and it’s time again for Microsoft Ignite. In this article, I’ll cover what IT Pros can expect to be announced.

It shouldn’t come as a surprise that Microsoft will be focusing on AI this year at Ignite. Windows is getting more attention but only because Microsoft sees its OS as the platform for local AI processing.

Let’s look at each area in more detail.

Artificial intelligence

AI is no longer a sidekick, it’s becoming the backbone of enterprise workflows. Microsoft is doubling down on agentic AI with several key updates:

  • Azure AI Foundry Agent Service reaches general availability: IT teams can now design, deploy, and scale enterprise-grade AI agents to automate business processes. Multi-agent orchestration and open protocols, like Agent2Agent (A2A) and Model Context Protocol (MCP), ensure interoperability across ecosystems.
  • Copilot Studio enhancements: Users and developers gain new pro-code and low-code features, including the ability to bring their own models (BYOM) from Azure AI Foundry, integrate Dynamics 365 data, and leverage Dataverse search for unified organizational knowledge.
  • Observability and monitoring: Azure AI Foundry introduces built-in observability for performance, safety, and cost, giving IT Pros a single pane of glass for monitoring AI workloads.
  • GitHub Copilot evolution: Copilot is moving into “agent mode,” acting as a peer programmer capable of refactoring code, running tests, and collaborating across the dev lifecycle.

For IT Pros, this means AI agents are shifting from experimental pilots to production-ready digital assistants.

Windows

This year, Windows is getting more attention than it has in recent years. Microsoft now sees Windows as the platform for enterprise AI:

  • Azure AI Foundry Local: Available on Windows 11 and macOS, this feature brings model inferencing and agent services directly to client devices. IT Pros can run AI workloads locally, saving bandwidth, improving privacy, and reducing costs.
  • Cross-silicon performance: Leveraging ONNX Runtime, Foundry Local ensures optimized AI performance across millions of Windows devices, making it easier to deploy industry-specific AI solutions without constant cloud connectivity.

This marks a significant step in bringing AI closer to the endpoint, as processing data in the cloud is not something every organization can or wants to do. And with these new features, Microsoft is addressing that need.

Security

Security remains a top priority, and Microsoft is embedding protections across its AI stack:

  • Prompt Shields (GA): Integrated into Azure AI Content Safety, these shields intercept jailbreaks and injection attacks before they compromise model behavior.
  • Spotlighting (in preview): Detects adversarial prompts hidden in external data sources, reducing cross-domain injection risks.
  • Task Adherence Controls (in preview): Ensures agents stay aligned with approved workflows, preventing unintended actions.
  • Microsoft Defender for Cloud integration: Real-time security recommendations and runtime alert monitoring are now part of the AI development workflow.
  • PII detection filters: Azure AI Foundry Models now include automatic redaction of sensitive data, supporting compliance and privacy.

For IT Pros, Microsoft hopes that these updates mean AI deployments can be scaled with confidence, backed by enterprise-grade safeguards.

Power Apps and Copilot Pages

Microsoft is reimagining how IT Pros and business users collaborate with agents inside business applications:

  • Power Apps: A unified development canvas now allows IT Pros to co-create with agentic AI, defining requirements, generating data models, and designing solution architectures. The new agent feed provides visibility into agent actions, keeping humans in the loop.
  • Copilot Pages: Pages now support mobile creation, Word export, and advanced outputs like interactive charts and code blocks. IT Pros can expect smoother workflows bridging Copilot responses into traditional document formats.
  • Dynamics 365 integration: Copilot now surfaces CRM insights across sales, service, supply chain, and marketing, helping IT teams deliver business value faster.

These updates position Microsoft’s business apps as hubs for human-agent collaboration, streamlining both IT and end-user productivity.

Scaling AI with confidence

At Ignite 2025, IT Pros can expect Microsoft to announce that AI agents will become mainstream, Windows to serve as a local AI processor, enterprise security to expand into AI-specific protections, and business applications to evolve into collaborative agent-driven platforms.

The message is clear: Microsoft is building an ecosystem where IT leaders can confidently deploy, secure, and scale AI across every layer of the enterprise.

Don’t miss out on Petri.com’s Microsoft Ignite 2025 coverage!

The post What IT Pros Can Expect at Microsoft Ignite 2025 appeared first on Petri IT Knowledgebase.

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alvinashcraft
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Countering a Brutal Job Market with AI

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Headlines surfaced by a simple “job market” search describe it as “a humiliation ritual” or “hell” and “an emerging crisis for entry-level workers.” The unemployment rate in the US for recent graduates is at an “unusually high” 5.8%—even Harvard Business School graduates have been taking months to find work. Inextricable from this conversation is the complication of AI’s potential to automate entry-level jobs, and as a tool for employers to evaluate applications. But the widespread availability of generative AI platforms begs an overlooked question: How are job seekers themselves using AI?

An interview study with upcoming master’s graduates at an elite UK university* sheds some light. In contrast to popular narratives about “laziness” or “shortcuts,” AI use comes from job seekers trying to strategically tackle the digitally saturated, competitive reality of today’s job market. Here are the main takeaways:

They Use AI to Play an Inevitable Numbers Game

Job seekers described feeling the need to apply to a high volume of jobs because of how rare it is to get a response amid the competition. They send out countless applications on online portals and rarely receive so much as an automated rejection email. As Franco, a 29-year-old communications student put it, particularly with “LinkedIn and job portals” saturating the market, his CV is just one “in a spreadsheet of 2,000 applicants.”

This context underlies how job seekers use AI, which allows them to spend less time on any given application by helping to cater résumés or write cover letters and thus put out more applications. Seoyeon, a 24-year-old communications student, describes how she faced repeated rejections no matter how carefully she crafted the application or how qualified she was.

[Employers] themselves are going to use AI to screen through those applications….And after a few rejections, it really frustrates you because you put in so much effort and time and passion for this one application to learn that it’s just filtered through by some AI….After that, it makes you lean towards, you know what, I’m just gonna put less effort into one application but apply for as many jobs as possible.

Seoyeon went on to say later that she even asks AI to tell her what “keywords” she should have in her application in light of AI in hiring systems.

Her reflection reveals that AI use is not a shortcut, but that it feels like a necessity to deal with the inevitable rejection and AI scanners, especially in light of companies themselves using AI to read applications—making her “passion” feel like a waste.

AI as a Savior to Emotional Labor

The labor of applying to jobs and dealing with constant rejection and little human interaction makes it a deeply emotional process that students describe as “draining” and “torturing,” which illuminates that AI is a way to reduce not just the time of labor but the emotional aspect of it.

Franco felt that having to portray himself as “passionate” for hundreds of jobs that he would not even hear back from was an “emotional toll” that AI helped him manage.

Repeating this process to a hundred job applications, a hundred job positions and having to rewrite a cover letter in a way that sounds like if it was your dream, well I don’t know if you can have a hundred dreams.…I would say that it does have an emotional toll….I think that AI actually helps a lot in terms of, okay, I’m going to help you do this cover letter so you don’t have to mentally feel you’re not going to get the shot.

Using AI thus acted as a buffer for the emotional difficulties of being a job seeker, allowing students to conserve mental energy in a grueling process while still applying to many jobs.

The More Passionate They Are, the Less AI They Use

AI use was not uniform by any means, even though the job application process often requires the same materials. Job seekers had “passion parameters” in place, where they dial down their use for a job that they were more passionate about.

Joseph, a 24-year-old psychology student, put this “human involvement” as “definitely more than 50%” for a role he truly desires, whereas for a less interesting role, it’s about “20%–30%.” He differentiates this by describing how, when passion is involved, he does deep research into the company as opposed to relying on AI’s “summarized, nuanced-lacking information,” and writes the cover letter from scratch—only using AI to be critical of it. In contrast, for less desirable jobs, AI plays a much more generative role in creating the initial draft that he then edits.

This points to the fact that while AI feels important for labor efficiency, students do not use it indiscriminately, especially when passion is involved and they want to put their best foot forward.

They Understand AI’s Flaws (and Work Around Them)

In their own words, students are not heedlessly “copying and pasting” AI-generated materials. They are critical of AI tools and navigate them with their concerns in mind.

Common flaws in AI-generated material include sounding “robotic” and “machine-like,” with some “AI” sounding words including “explore” and “delve into.” Joseph asserted that he can easily tell which one is written by a human, because AI-generated text lacks the “passion and zeal” of someone who is genuinely hungry for the job.

Nandita, a 23-year-old psychology student, shared how AI’s tendency to “put you on a pedestal” came through in misrepresenting facts. When she asked AI to tailor her résumé, it embellished her experience of “a week-long observation in a psychology clinic” into “community service,” which she strongly felt it wasn’t—she surmised this happened because community service was mentioned in the job description she fed AI, and she caught it and corrected it.

Consequently, using AI in the job hunt is not a passive endeavor but requires vigilance and a critical understanding to ensure its flaws do not hurt you as a job seeker.

They Grapple with AI’s Larger Implications

Using AI is not an unconditional endorsement of the technology; all the students were cognizant of (and worried about) its wider social implications.

John, a 24-year-old data science student, drew a distinction between using AI in impersonal processes versus human experiences. While he would use it for “a cover letter” for a job he suspects will be screened by AI anyway, he worries how it will be used in other parts of life.

I think it’s filling in parts of people’s lives that they don’t realize are very fundamental to who they are as humans. One example I’ve always thought of is, if you need it for things like cover letters, [that]s OK] just because it’s something where it’s not very personal.…But if you can’t write a birthday card without using ChatGPT, that’s a problem.

Nandita voiced a similar critique, drawing on her psychology background; while she could see AI helping tasks like “admin work,” she worries about how it would be used for therapy. She argues that an AI therapist would be “100% a Western…thing” and would fail to connect with someone “from the rural area in India.”

The understanding of AI shows that graduates differentiate using it for impersonal processes, like job searching in the digital age, from more human-to-human situations where it poses a threat.

Some Grads Are Opting Out of AI Use

Though most people interviewed were using AI, some rejected it entirely. They voiced similar qualms that AI users had, including sounding “robotic” and not “human.” Julia, a 23-year-old law student, specifically mentioned that her field requires “language and persuasiveness,” with “a human tone” that AI cannot replicate, and that not using it would “set you apart” in job applications.

Mark, a 24-year-old sociology student, acknowledged the same concerns as AI users about a saturated online arms race, but instead of using AI to send out as many applications as possible, had a different strategy in mind: “talking to people in real life.” He described how he once secured a research job through a connection in the smoking area of a pub.

Importantly, these job seekers had similar challenges with the job market as AI users, but they opted for different strategies to handle it that emphasize human connection and voice.

Conclusion

For graduate job seekers, AI use is a layered strategy that is a direct response to the difficulties of the job market. It is not about cutting corners but carefully adapting to current circumstances that require new forms of digital literacy.

Moving away from dialogue framing job seekers as lazy or unable to write their own materials forces us to look at how the system itself can be improved for applicants and companies alike. If employers don’t want AI use, how can they create a process that makes room for human authenticity as opposed to AI-generated materials that sustain the broken cycle of hiring?

*All participant names are pseudonyms.



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alvinashcraft
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How to Prepare for the Future of Programming

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Start a start-up? Scratch that. Call your mom. Go back to school? Don’t go back to school. Learn to code? Don’t learn to code. Forget coding. Only prompt engineering matters now. Actually, I heard it’s overrated. You think we’re gonna be prompting in 5 years? 2 years? Nonsense. All this hype is being blown so out of proportion. Have some healthy skepticism. Have a lot of healthy skepticism. Doubt. Believe. Move to the woods. Bury your laptop in the back yard. Get bored. Dig it up again. Coding is back, baby! Start another course, work on it for a few days. Lose motivation. Panic. Repeat.

You’re not alone. As a writer, I’m also panicking. Why read this when you could ask the same question to your LLM of choice and have a lively discussion perfectly tuned to be as broad or technical, long or short, playful or serious, as you want it to be? This thought has tormented me for days and this post remained a blank document. The only thing that saved me was remembering why I made this series in the first place.

How to learn to program in an AI World Part 4

I wanted to create a resource for learners to better understand programming within the context of our new AI world. I made a case for why it’s still worth learning to code, explored the psychology of beginner programmers, and discussed whether you should use AI at all. So, now what? 

We know that programming will change – that programming has changed. But how exactly? And how much? What knowledge can we be sure will remain fundamental? What should we learn to prepare for the worlds to come?

There are a variety of answers depending on where you as the answerer stand. Is your net worth positively correlated with AI hype? Is your job too complicated, social, or important for AI? How is your relationship with risk? How do you feel about change? What do you believe about what the future needs? 

These are not questions anyone can answer for you. Not me, not a tech CEO, not your mom, and certainly not a chatbot. We live in a world with platforms and educational institutions jumping to answer “What can I learn?” (a small reminder to check out our catalog of free courses), but there are very few resources that will give good answers to questions like “What should I learn?”, “Can you really justify why?”, and “Can you promise me it will remain useful?”.

I can’t guarantee that anything you learn will remain useful in the years to come, but I am certain that learning will. On that subject, here are a few short recommendations on how to prepare for the future of programming.

Understand the flaws of your education

Are you in a large institution that is slow to adapt? Is AI use being discussed openly or banned from the classroom? Are you self-studying at your own pace, but lack any network of peers or mentors? Is your education giving you a broad overview of a field (a Bachelor’s degree) or is it leading you toward specialization and a specific job (bootcamp/internship)? 

Both of these approaches are useful, they’re just working on different timelines. A broad overview can give you more options when the field changes, while a specialization can help you in the short term. Either way, try to compensate in the direction of your weaknesses so you’re not left either overqualified and underemployed, or unemployable when your only skill becomes redundant.

📚 An exercise: Take 10 to 20 minutes to reflect on your education from a zoomed-out perspective. Think about what it did or is doing well and what gaps you might be left with at the end of it. Below you’ll find a few recommendations on how to fill those gaps, but feel free to brainstorm your own as well.

How to broaden your knowledge

If you’ve got practical skills but worry about their shelf life, now is the time to foster curiosity about the wider scope of your field. This will feel different than learning a practical skill, since there are fewer concrete ways to assess your progress. Instead, pay attention to the moments when ideas from different domains click together. This is a sign that you’re starting to expand your general knowledge and get a clearer view of the big picture.

Here are some practical ways to do this:

  • 🧑‍🎓 Follow short courses in other domains. Our knowledge map can help you visualize what subjects you might find interesting to explore, or you can even consider departing from computing altogether. Bringing technical expertise to a writing course might lead to great science fiction, or an interesting exercise in applied philosophy.
  • 🧰 Work on projects that use a broad skillset but don’t require professional excellence. Make a silly app that needs a little bit of frontend, a little bit of backend, knowledge of APIs, and even graphic design. It might be ugly and inefficient, the point is that you did it.
    • Since motivation might be difficult to maintain on your own, find someone with a different skillset and swap roles.
  • 👯 If you consider yourself a “technical person”, focus especially on communication skills and critical thinking. These are particularly important in navigating the uncertain future we’re facing, since purely technical jobs are in many ways the easiest to automate away.

How to deepen your knowledge

Personally, I find it really hard to specialize. I jump between interests, rarely sticking with anything long enough to achieve mastery. This used to stress me out – how could I be good at my job if I couldn’t commit to one thing? But I’ve learned that the pressure to specialize is often about legibility, not capability. We like people who are easy to categorize. In practice, though, proficiency in one skill lends itself to an easier time with others.

Depth is what makes you adaptable. Surface-level knowledge can get outdated quickly. Understanding underlying principles like how systems actually work, not just how to use them, means you can transfer what you know to new tools and frameworks. When the landscape shifts, you’re not starting from scratch.

You’ll have to choose your approach depending on the specific skill you want to master. Here’s how to do this:

  • 🧑‍🏫 Get advice from someone who’s done it before, ideally someone who can personally mentor you. To get started, there are plenty of “Things I wish I’d known before becoming x” videos, which might help you wade through what’s necessary and what’s not. 
  • 💻 Regarding coding, our specializations courses provide very comprehensive and practical assignments in various domains.
  • 💯 If you, like me, quickly lose interest once the novelty wears off, I can recommend tailoring your media diet toward your target subject. Reading books and listening to stories of people talking about your subject on a high level helps you remember what sparked your interest in the first place. To start, you could check out our video essay on the history of Git!

Goodbye, AI world

You don’t need to understand tech to do things with it anymore. Now you can build apps, write code, or generate designs without understanding the underlying systems. There’s real value in that accessibility, but as a writer and coder, I worry about what we lose. If we go all-in on doing things, we might forget that developing deep knowledge and understanding can be fun and good for us. It might even be a requirement for our mental health and self-esteem. To not only be able to make an app, but to take pride in the fact that you learned how to.

This is the fourth and final post in our series How to Learn to Program in an AI World. If you missed it, check out the previous posts, Is It Still Worth Learning to Code?, Learning to Think in an AI World: 5 Lessons for Novice Programmers, and Should You use AI to Learn to Code?

Clara Maine is a technical content creator for JetBrains Academy. She has a formal background in Artificial Intelligence but finds herself most comfortable exploring its overlaps with education, philosophy, and creativity. She writes, produces, and performs videos about learning to code on the JetBrains Academy YouTube channel.

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Ignite your future with new security skills during Microsoft Ignite 2025

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Ignite your future with new security skills during Microsoft Ignite 2025

AI and cloud technologies are reshaping every industry. Organizations need professionals who can secure AI solutions, modernize infrastructure, and drive innovation responsibly. Ignite brings together experts, learning, and credentials to help you get skilled for the future.

Take on the Secure and Govern AI with Confidence Challenge

Start your journey with the Azure Skilling Microsoft Challenge. These curated challenges help you practice real-world scenarios and earn recognition for your skills. One of the challenges featured is the Secure and Govern AI with Confidence challenge. This challenge helps you:

  • Implement AI governance frameworks.
  • Configure responsible AI guardrails in Azure AI Foundry.
  • Apply security best practices for AI workloads.

Special Offer:
Be among the first 5,000 participants to complete this challenge and receive a discounted certification exam voucher—a perfect way to validate your skills and accelerate your career.

Completing this challenge earns you a badge and prepares you for advanced credentials—ideal for anyone looking to lead in AI security.

Join the challenge today!

Validate Your Expertise with this new Microsoft Applied Skill.

Applied Skills assessments are scenario-based, so you demonstrate practical expertise—not just theory. Earn the Secure AI Solutions in the Cloud credential—a job-ready validation of your ability to:

  • Configure security for AI services using Microsoft Defender for Cloud.
  • Implement governance and guardrails in Azure AI Foundry.
  • Protect sensitive data and ensure compliance across AI workloads.

This applied skill is designed for professionals who want to lead in AI security, accelerate career growth, and stand out in a competitive market. To learn how to prepare and take the applied skill, visit here.

Your Next Steps: Security Plans

Ignite isn’t just about live sessions—it’s about giving you on-demand digital content and curated learning paths so you can keep building skills long after the event ends. With 15 curated security plans that discuss topics such as controlling access with Microsoft Entra and securing your organization’s data, find what is relevant to you on Microsoft Ignite: Keep the momentum going page.

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Announcing Public Preview: Exchange Online Admin API

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Today, we are announcing the Public Preview of the Exchange Online Admin API – a REST based, cmdlet style administrative surface specifically designed to help organizations migrate away from EWS for specific Exchange admin scenarios and modernize automation workflows over HTTP.

Context

Exchange Web Services (EWS) is scheduled for deprecation in October 2026, yet many organizations still depend on EWS for specific Exchange administrative tasks due to unavailability of the alternate API for these scenarios. The Admin API provides a REST based, cmdlet style alternative for these scenarios, enabling modern automation while preserving familiar semantics for Exchange administrators.

Note: The Admin API is not a full REST replacement for Exchange Online management. It is designed only to cover the subset of Exchange Online Administrative capabilities that provide alternative for administrative scenarios currently available through EWS. For complete Exchange management, we recommend using Exchange Online PowerShell.

Capabilities available in Public Preview

The Admin API Public Preview includes 6 endpoints. The list of endpoints and supported functionalities are as follows:

  • OrganizationConfig — Read tenant wide MailTips related configuration.
  • AcceptedDomain — List accepted domains and core domain settings for the tenant.
  • Mailbox — Read mailbox properties and manage Send on behalf delegates (view/update).
  • MailboxFolderPermission — List, grant, modify, and remove folder level permissions (Inbox, Calendar, subfolders).
  • DistributionGroupMember — Retrieve membership for distribution groups.
  • DynamicDistributionGroupMember — Retrieve membership for dynamic distribution groups.

For detailed documentation, including request patterns, and endpoint details, visit:

For the most up to date guidance on EWS migration see https://aka.ms/ews1Page.

Availability and roadmap

  • Public Preview (Worldwide): Available starting November 17, 2025. Use this phase to evaluate functionality, plan migrations, and share feedback on any gaps between EWS admin scenarios and the Admin API.
  • General Availability (Worldwide): Yet to be announced
  • Sovereign environments (GCC, GCC High, DoD): Yet to be announced

Currently, API responses include extra properties, but only those listed in each endpoint's documentation will be available at GA. Please refer the individual endpoint documentation for the list of properties that will be available in GA. Any updates to the list of output properties will be announced during the GA release.

Share feedback

Your input during Public Preview is essential. Please use our feedback form to report issues, gaps, or suggestions. Your feedback will help us refine the API and documentation ahead of GA.

Exchange Online Administration and EWS Deprecation teams

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