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In this issue:
🤿Deep Dive: Microsoft makes app building easier, keeps IT in the loop
🤝From Our Friends: A couple of things worth checking out
⚒Tool Snapshots: Tools for AI, no-code, and productivity
🤖AI Made This: Interesting and inspiring creations made with AI
👀On Our Radar: Something worth checking out before you go
⚡Quick Hits: The latest in AI, tech, and productivity
🤿 DEEP DIVE
Building the App Isn’t Enough
Microsoft is bringing natural language app creation inside the enterprise.
AI has made building an app weirdly easy.
Describe what you want, let an agentic coding system turn that into software, tweak it until it works. That's basically the idea.
But Microsoft is focusing on the bit that comes immediately after that.
Because a working app sitting by itself isn't necessarily much use to a business. It needs access to company data. It needs to take actions in the systems people already use. And if suddenly a lot more employees can build these things, IT probably needs to know what exactly is being published.
That's the more interesting part of Microsoft's new app-building features in Copilot Cowork and Copilot Studio.
The prompt is just the beginning
The actual building process is deliberately conversational.
In Copilot Studio, you choose App (Preview). In Copilot Cowork, you invoke the /app skill. Then you describe the outcome you want, who will use the app, what data it needs and what actions it should perform.
Copilot Studio turns that into a working app scaffold, which you can keep changing through natural language. People who don't want to touch code can stay focused on the app itself, while more advanced builders can inspect the underlying code and structure.
But then come the connectors.
An onboarding app, for example, could pull progress from a business data source, show learning resources and update onboarding records. A field service app could retrieve technical information from a third-party system, guide someone through steps and write the results back.
So these aren't being pitched as little generated apps that live off on their own. They're supposed to sit inside actual business processes.
And IT gets a seat at the table
This is probably the detail that gives away the whole idea.
Microsoft says these are full-stack apps built using open standards, with things like Git-backed source control, deployment stages and version isolation.
Published apps also appear in the Microsoft 365 admin center, where administrators get an inventory and operational controls. Microsoft Entra identity and organizational data and connector policies are respected by default.
Basically, Microsoft isn't just trying to make app building easier. It's trying to make that easier app building something an organization can still govern.
There's an availability wrinkle though. The /app skill in Copilot Cowork is available through Microsoft's Frontier program, while native app building in Copilot Studio is rolling out in public preview over the next week. App building and running also follows Microsoft's usage-based billing model.
For companies, the bigger idea is pretty simple. More people can build the apps they need, while IT still gets the visibility and controls to manage what actually makes it into the business.
The quick take
Copilot Cowork and Copilot Studio are getting natural language app building.
Builders describe the users, data, actions and outcome, then iterate conversationally.
Connectors let apps read from and write back to organizational systems.
Published apps come with centralized visibility and controls for IT through the Microsoft 365 admin center.
🤝 FROM OUR FRIENDS
A quick share we thought you might find useful
What’s still sitting on your to-do list?
You don’t need an AI team to build an AI agent. With Skydive, the person who knows the work can create the agent to do it.
Start an agent off with a role, teach them how your team operates, connect your tools, and put them to work.
⚒ TOOL SNAPSHOTS
Futuristic tools within AI, no-code, and productivity
📹 Oats
Keep meeting notes local without adding another bot to the call.
Why it’s useful: A good fit if you want transcription and meeting notes on your own device, with optional cloud features when you need things like coaching, follow-up tracking, or speaker recognition.
Give your AI a researcher that learns where to look.
Why it’s useful: Useful for research-heavy work like company enrichment or regulations, where digging into the right domain-specific sources matters more than broad web search.
📁 Clipwise
Save the whole web page straight into your Notion database.
Why it’s useful: Handy if Notion is where you collect research and references, since you can fill in database properties before saving and keep the workflow local without another account.
🤖 AI MADE THIS
Interesting and inspiring creations made with AI
SLICE - A 2-Minute AI Animated Short
A charming animated short about two record-store clerks whose late-night pizza stop leads to an unexpected new companion. Creator Alejandro Pereira built every character, location, shot, sound effect, and score with AI, then shared the complete behind-the-scenes workflow including all 5 final video prompts and revisions so others can see how a coherent AI film is actually made.
AI used
Seedance 2.5 (video), Seedream (characters and sets), ElevenLabs (music and sound effects), and DaVinci Resolve (editing).
👀 ON OUR RADAR
One more thing we thought you'd like
I Threw Out My Grocery Store K-Cups After One Sip
One cup from Angelino's, a family-owned L.A. roastery, and I never went back. 50+ fresh-roasted pods compatible with all Keurig® brewers, shipped within days of roasting — from 39¢ a cup. New customers get 15% off their first order, applied automatically.
⚡ QUICK HITS
The latest in AI, tech, and productivity worth knowing
Mathematicians are worried AI is changing the rules. 25 Fields Medal winners signed an open letter warning that AI labs racing to solve famous problems could damage attribution and the culture of open research. Their concern is bigger than who gets the proof first. AI-generated ideas still need mathematicians to verify, explain, and integrate them into the field.
The AI slowdown idea has a China problem. China rejected calls from U.S. tech leaders to deliberately slow frontier AI development, with Beijing describing the proposal as fearmongering and part of a “Cold War playbook.” The disagreement comes as both China and the U.S. acknowledge AI risks, but competition and mutual suspicion are making coordinated restraint look difficult.
ℹ️ ABOUT US
The Intelligent Worker helps you to be more productive at work with AI, automation, no-code, and other technologies.
We like real, practical, and tangible use-cases and hate hand-wavy, theoretical, and abstract concepts that don’t drive real-world outcomes.
Our mission is to empower individuals, boost their productivity, and future-proof their careers.
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