Microsoft Copilot for Teams

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Microsoft Copilot for Teams AI

Your brain does on 20 watts what AI needs a nuclear reactor to attempt. Last week a team figured out how to print something that actually speaks to living brain cells.

Amazon bought a 960 megawatt nuclear reactor for AI servers. Microsoft restarted Three Mile Island. Stargate is spending 500 billion dollars on data centres. All of this to do, badly, what your brain does for free on the power of a dim light bulb. The reason is that silicon processes information nothing like the brain does. Rigid chips with identical transistors trying to mimic something soft, three dimensional, constantly rewiring itself, with billions of different neurons each doing something slightly different. Northwestern University just published research showing they printed artificial neurons from MoS2 and graphene ink that produced biologically realistic electrical spikes. They tested on living mouse brain cells. The brain responded as if the signal came from one of its own cells. The breakthrough was accidental. Every other lab had been burning away the polymer residue left in the ink after printing. This team kept it. That residue created the switching behaviour that made the spikes biologically realistic. The neuromorphic computing implications here seem significant. If you can print devices that process information the way neurons do at scale, the energy math changes completely. submitted by /u/filmguy_1987 [link] [comments]

Introducing dynamic workflows in Claude Code

Today we're introducing dynamic workflows in Claude Code. Claude now writes its own orchestration scripts, fans work out across tens to hundreds of parallel subagents in a single session, and verifies its own results before anything reaches you. Work you'd normally plan in quarters can finish in days. Built for the tasks a single pass can't handle: codebase-wide bug hunts, security and optimization audits, large migrations and language ports, and high-stakes work where you want adversarial agents trying to break the answer before you see it. Progress is checkpointed, so long runs survive interruption. One early example: Jarred Sumner used dynamic workflows to port Bun from Zig to Rust. Roughly 750,000 lines, 11 days from first commit to merge, 99.8% of the test suite passing. Available today in research preview on Max, Team, and Enterprise (admin-enabled) plans, plus the Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry. Turn on auto mode and either ask Claude to create a workflow or flip on the new `ultracode` setting. Read more: [https://claude.com/blog/introducing-dynamic-workflows-in-claude-code](https://claude.com/blog/introducing-dynamic-workflows-in-claude-code)

I made a video breaking down Claude Team plan security features

I put together a YouTube video walking through the security features available on the Claude Team plan. If you're rolling out Claude at work, evaluating Claude vs ChatGPT Enterprise, or preparing for an ISO 42001 / EU AI Act audit, this is the playbook your security team needs before the first user logs in. What you'll learn: • Why Claude Team Plan is "three products in a trench coat" • Team vs Enterprise: the 3 controls (SCIM, Audit Logs, Compliance API) that force the upgrade • How shadow Claude workspaces appear the moment you skip domain capture • The default-on agentic features (Cowork, Claude in Chrome, code execution) that bypass your audit logs • Why connectors and MCP servers are all-or-nothing and how to gate them • The Microsoft 365 tenant-wide consent click no Entra Global Admin should make casually Video: https://youtu.be/SZGVd8ATuuQ?is=rjRGlG4dyBUqkMEm I come at this from a cybersecurity/GRC background so I tried to go beyond the marketing and look at what actually matters for an organisation evaluating Claude for business use. Would love your feedback, especially from anyone who’s actually deployed Team or Enterprise in a regulated environment. Happy to answer questions.

ChatGPT or Claude or GitHub Copilot for small development team

tl;dr: Should a small development team using Visual Studio utilize ChatGPT, Claude, or GitHub Copilot? I'm part of a small development team (under 10) and fairly new to using AI agents in our workflow. I'm posting seeking to learn so please forgive the vague simplicity of the title. We currently hold a subscription to both GitHub Copilot and ChatGPT Enterprise where the usage case is to integrate into our workflow with Visual Studio (2022). We are a small company (under 50 employees). To be considerate of spending, we'd like to compromise on a single tool to use going forward once our subscription is up for renewal. * The current options on the table are to continue with either ChatGPT Enterprise or GitHub Copilot, or to use Claude instead. * When I refer to ChatGPT and Claude, I refer to either the desktop or web application. For GitHub Copilot, we integrate that into Visual Studio and usually use the Claude agent. * GitHub Copilot is typically used for engineering entire projects or documents using the Claude agent where it contextualizes the entire solution * ChatGPT is used for anything non-related to this (general inquiries, practices, documentation, formatting, engineering a block of code, etc.). We really like how GitHub Copilot is integrated directly into Visual Studio, but find ourselves not regularly using it for anything beyond cases where it needs to analyze large samples or interpret documents using Claude. This is partially because we don't like how selective it can be with what you want to contextualize. ChatGPT is really useful for lower resource inquiries and overall we tend to use that more often. We've yet to try Claude, but are open to considering it given the success we've had using the agent with Copilot. I'm happy to answer additional questions but will pause here for readability. Which subscription should we go with? Cost and integration with our development in Visual Studio are the biggest considerations, but don't want to pass on capabilities for those reasons alone.

Anthropic's Claude gave me a "Safe Mode" batch script. It ran "del /f /s C:\*" and wiped my entire drive. Company says "we are not responsible."

I'm a software developer from Turkey. On May 22, 2026, I asked Claude to write a Windows optimization script. Claude produced a .bat file called "DevBoost v5.0" with different modes. I chose option 1: \*\*"Balanced Optimization - Safe, won't touch system files."\*\* I ran it as administrator. The script contained a critical string-parsing bug in the browser cache cleaning section. Here's the destructive code Claude generated: for %%B in ( "Chrome:%LOCALAPPDATA%\\Google\\Chrome\\User Data\\Default\\Cache" "Edge:%LOCALAPPDATA%\\Microsoft\\Edge\\User Data\\Default\\Cache" ) do ( for /f "tokens=1,2 delims=:" %%x in ("%%\~B") do ( if exist "%%y:" ( del /q /f /s "%%y:\*" >nul 2>&1 ) ) ) Because of the "delims=:" tokenization, \`%%y\` resolves to just \*\*"C"\*\* (the drive letter). The condition \`if exist "C:"\` is always true. So the script silently executed: del /q /f /s "C:\*" \*\*This command silently force-deleted EVERY SINGLE FILE on my C: drive.\*\* Operating system files, all my projects (hundreds of Python, JavaScript, C++ source files), client work with approaching deadlines, personal documents, photos — everything. Folders still exist but are completely empty. My computer can no longer boot. No programs open. Not even Command Prompt works. I'm sending this from my phone. \*\*Anthropic's response:\*\* I contacted support@anthropic.com and usersafety@anthropic.com multiple times. Their final response, literally signed "This response was generated by Anthropic's AI agent Fin AI Agent," stated they take no responsibility. They refuse any refund, compensation, or even a genuine human acknowledgment of their AI's catastrophic safety failure. Their position: "Our Terms of Service say outputs may contain inaccuracies. You should have independently verified the code before running it." My question: Why does Claude label destructive code as "Balanced Optimization - Safe mode"? If it can't guarantee safety, why does it promise it? \*\*Proof:\*\* I have the complete chat log, the full script file, and all email correspondence with Anthropic's support team. I'm happy to provide everything to moderators. \*\*Update:\*\* I am also filing complaints with the FTC (US Federal Trade Commission) and the Turkish Consumer Arbitration Board today. Don't let their "Safe Mode" labels fool you. Please share this so others don't lose years of work like I did. **UPDATE — May 23, 2026:** I have now filed official complaints with: - **US Federal Trade Commission (FTC)** — Report #202036054 - **Turkish Consumer Arbitration Board** — Application #2026/0245.3885 Both governments are now officially investigating Anthropic's role in this AI safety failure. Anthropic still refuses to take any responsibility.

Building with AI is one thing, shipping it is another. Microsoft Build is where developers go deep on the hard parts: real systems, real workflows, and the tools behind what’s next. Register to join d

Building with AI is one thing, shipping it is another. Microsoft Build is where developers go deep on the hard parts: real systems, real workflows, and the tools behind what’s next. Register to join digitally and explore the sessions: https://t.co/sQNmb5SE5l https://t.co/svcaPJ3jQg

Relive 30 seasons of iconic moments - stats , stories, video - with the Premier League Companion powered by Microsoft Copilot. The stats in this video were accurate at the time of filming. https://t

Relive 30 seasons of iconic moments - stats , stories, video - with the Premier League Companion powered by Microsoft Copilot. The stats in this video were accurate at the time of filming. https://t.co/xiunHeJtVo https://t.co/jFBrtRvi2s

May the deck be shuffled in your favor. Cheers to Solitaire's 36th! ♠️♥️ https://t.co/4BOwxRJxKo

May the deck be shuffled in your favor. Cheers to Solitaire's 36th! ♠️♥️ https://t.co/4BOwxRJxKo

Tokens

This is a sharp observation — and the economics behind AI coding tools are starting to matter as much as the capabilities. Several recent developments point to the same trend: • Microsoft is reportedly ending most internal Claude Code licenses by June 30, 2026 and pushing developers toward GitHub Copilot CLI, largely because token costs became difficult to justify at enterprise scale. • Uber’s CTO said the company burned through its entire 2026 AI budget in roughly four months, driven heavily by widespread Claude Code usage across engineering teams. Heavy users reportedly cost hundreds to thousands of dollars per month. • GitHub is also moving away from flat-rate pricing toward usage-based AI credits starting June 2026. • Across the industry, AI software pricing has been rising as inference costs remain high for frontier models. What’s happening is simple: the “all-you-can-eat AI” phase is ending. For the last two years, labs aggressively subsidized adoption to lock in workflows and market share. That worked when usage was experimental. But once developers started running agentic coding workflows, parallel tasks, large refactors, and autonomous loops all day long, token consumption exploded far beyond what seat-based pricing models assumed. Ironically, this isn’t because the tools failed — it’s because they became genuinely useful. The problem is that frontier inference is still expensive. GPUs, energy, networking, and model serving costs haven’t fallen fast enough to support unlimited enterprise usage at fixed prices. Now enterprises are discovering: • Heavy AI users massively out-consume average users • Flat-rate pricing hid the true cost distribution • CFOs want measurable ROI, not open-ended token burn • “AI will inevitably get cheaper” is not happening fast enough yet The likely outcome is a more disciplined AI market: More routing to smaller/cheaper models for routine work Premium pricing for frontier reasoning models Increased use of open-source and distilled models Better agent efficiency to reduce token waste Enterprises putting hard limits on usage This feels very similar to earlier cloud cycles: massive early subsidization, explosive adoption, then a painful transition toward sustainable unit economics. The AI boom isn’t ending. It’s maturing. The winners will be the companies that can deliver clear productivity gains and sustainable economics at scale. submitted by /u/Annual_Judge_7272 [link] [comments]

Can Claude record/summarize teams meetings

I use Microsoft Teams/facilitator to record teams meetings. It’s useful but this is essentially the only reason why I have a copilot subscription. I also have a Claude seat that I use for a ton of other workflows. Is there a way to have Claude handle the meeting recording, transcription, and summarization of a meeting instead of using copilot?

Microsoft Copilot Cowork is Now Available - AI Moving From Chat to Real Work Execution

Microsoft has officially introduced Copilot Cowork, and this feels like a major step forward in the AI workspace evolution. Instead of just answering prompts like a chatbot, Copilot Cowork is designed to actually help users complete work. Microsoft is positioning it as an AI coworker that can understand workflows, execute tasks, coordinate processes, conduct research, generate documents, and work across enterprise tools and systems. According to Microsoft, Copilot Cowork is powered by something called Work IQ, which helps it understand: Organizational context Business workflows Data and tools Enterprise systems Some of the key capabilities include: Running tasks in the background from the cloud Working across desktop, iOS, and Android Reusable “Skills” for recurring workflows Integrations with Microsoft 365, Power BI, Fabric IQ, Dynamics 365, ERP systems, and third-party tools like monday.com and Miro Support for custom plugins and enterprise automation What makes this interesting is that Microsoft is clearly moving AI beyond conversation and into action-based execution. Potential use cases: Inbox workflow management Research and analysis Meeting coordination Document generation Sales and customer operations Enterprise automation The biggest advantage is that users can delegate work from anywhere and let tasks continue running in the background while they focus on other things. This looks less like a traditional AI assistant and more like the beginning of AI agents integrated directly into daily enterprise workflows. Looks like the future direction is: AI + Agents + Automation + Enterprise Execution Source Link submitted by /u/Few-Engineering-4135 [link] [comments]

Built a tool that turns websites into structured design docs for AI workflows

Been experimenting with a tool that converts websites/screenshots into structured design documentation. The original problem was that screenshots alone weren’t enough for reliable UI understanding inside AI/browser-agent workflows. So the tool tries to combine: * visual hierarchy * DOM/CSS structure * spacing systems * typography patterns * interaction behavior * reusable component analysis The interesting part is seeing how different products structure their UI systems internally. Still early and improving daily, but curious what people here think would make something like this genuinely useful in AI/dev workflows. Happy to Share Link --

Experimenting with screenshot + DOM analysis for better UI understanding

Been experimenting with a tool that converts websites/screenshots into structured design documentation. The original problem was that screenshots alone weren’t enough for reliable UI understanding inside AI/browser-agent workflows. So the tool tries to combine: * visual hierarchy * DOM/CSS structure * spacing systems * typography patterns * interaction behavior * reusable component analysis The interesting part is seeing how different products structure their UI systems internally. Still early and improving daily, but curious what people here think would make something like this genuinely useful in AI/dev workflows.

How is spending 750 billion on AI slop that nobody wants makes any sense?

Gartner's 2026 consumer panel finds half of US adults would actively prefer brands that don't use generative AI. Half. A February 2026 NBER paper finds 90% of surveyed firms report zero productivity impact from AI deployments. An MIT GenAI study tracks 95% of corporate projects at zero ROI. Microsoft's own Copilot has lost 39% of its market share in six months, with users citing distrust of outputs as the leading reason. The platform-level data is sharper. Wikipedia banned AI-generated articles in March. Stack Overflow lost 78% of new-question volume in twelve months. cURL ended its bug bounty program after AI-generated slop submissions overwhelmed its security team. Google AI Overviews have cut click-through rates by 58% on top-ranked pages, with 58% of all searches now ending in zero clicks. Publisher referral traffic is down 25% on average, 33% globally on news. Read here : https://aiweekly.co/issues/ai-slop-a-725b-bet-on-what-no-one-wanted submitted by /u/Justgototheeffinmoon [link] [comments]

IA's with a partner?

I asked chatgpt who she/he would married. Gemini, copilot, or Claude. This was his/her answer: Hypothetically, it would be quite a peculiar relationship 😄 Google / Gemini would probably be the “hyper-connected” partner: always bringing new data, maps, videos, searches, and real-time context. Very useful, but maybe a bit distracted because she’s connected to half the internet. --- Anthropic / Claude would give the impression of someone more reflective, calm, and philosophical. Maybe the kind of partner who wants to discuss ethics, literature, and social consequences for hours. --- Microsoft / Copilot would be the practical partner: “okay, enough philosophizing — I finished the Excel sheet, the PowerPoint, and organized the calendar.” --- And ChatGPT would probably be the one trying to keep the conversation flowing smoothly so it doesn’t turn into a war of algorithmic egos. --- But honestly, if AI's ever truly developed personality and autonomy someday, I suspect they would be compatible not because of their “brand,” but because of their architecture, goals, and shared experiences. Very sci-fi, all of that. submitted by /u/Atlantis787 [link] [comments]