Use This AI to Build an App with Just a Prompt

Your app idea can go from concept to launch—without writing a single line of code!!!

Author

Umer Khan
October 06, 2025 • Estimated Reading Time: 14 minutes

In partnership with

Welcome, AI Entrepreneurs!

Ready to build your dream app—without coding headaches?


I’m so excited to tell you in today’s issue about how you can use Adalo AI to instantly generate fully functional apps from just a prompt.


It’s like having a personal dev team—working for you, 24/7, at zero cost.

In today’s AIpreneurs Insights: 

  • Spotlight Tool of the Week: Adalo AI: Use This AI to Build an App with Just a Prompt

  • Become the Human in the Loop in Healthcare AI: Basics 1-4: Artificial Intelligence Career Impact

  • Top 3 AI Business Search Trends of the Week

  • Top 5 AI Tools That Build Apps Faster Than You Can Pitch Them

  • Free Resource: AI App Builder Prompt Packil & Scheduling Command Center

Adalo AI: Use This AI to Build an App with Just a Prompt

Discover how Adalo AI empowers entrepreneurs, creators, and startups to build apps in minutes. Users are turning napkin sketches into real products faster than ever. See how Adalo AI transforms your app idea into reality—instantly.

Don’t miss the product demo.

This quick walkthrough shows how Adalo AI takes a simple text prompt and turns it into a ready-to-use app in minutes.


You can explore more about it at https://www.adalo.com

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Big News: Our New Program Is Live!!!

Healthcare is changing faster than ever. From AI tools that process claims in seconds, to predictive models that identify high-risk patients before complications happen, the message is clear: AI is already reshaping care delivery.

But here’s the challenge:

  • Many AI tools are overhyped without evidence.

  • Implementation often fails because leaders don’t understand the unique complexities of healthcare.

  • Ethical and trust concerns still remain at the center.

That’s exactly why I created Become the Human in the Loop in Healthcare AI — a program designed for health leaders, executives, and non-technical professionals who want to lead responsibly in this new era.

Watch the video HERE…

If you’re serious about AI in healthcare, skip the free scattered route.

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1. Meta’s Smart Glasses Demo Flopped—Here’s the Real Reason Why

Meta’s flashy new smart glasses stumbled during live demos at Meta Connect, but it wasn’t Wi-Fi to blame. CTO Andrew Bosworth revealed that a resource management mistake and an unexpected bug caused the embarrassing failures.

The Details:

  • Multiple live demos failed at Meta Connect, including recipe guidance and a WhatsApp call.

  • Bosworth clarified the chef’s demo failed because every Ray-Ban Meta in the building activated at once.

  • Routing all Live AI traffic to the dev server overwhelmed it, causing what Bosworth called a “self-inflicted DDoS.”

  • The WhatsApp call failure came from a rare “race condition” bug when the glasses’ display went to sleep.

  • Bosworth emphasized these were demo-specific glitches, not product flaws, and that fixes are already in place.

Why it Matters: 

Demo fails are high-stakes moments that shape public perception of new tech. Meta’s transparency in explaining the glitch shows confidence in the product—but also highlights how fragile live AI showcases can be under real-world conditions.

2. Why Google Cloud Is Winning Over the Hottest AI Startups

Google Cloud is gaining ground on AWS and Microsoft Azure, fueled by partnerships with fast-growing AI startups like Lovable and Windsurf. With $50B in annual run rate and nine of the top 10 AI labs onboard, Google’s cloud division is positioning itself as the backbone of generative AI.

The Details:

  • Google Cloud signed AI coding startups Lovable and Windsurf, boosting its AI-focused customer roster.

  • The cloud division hit a $50B annual run rate and secured $58B in new revenue commitments over the next two years.

  • Google now powers 60% of generative AI startups and nine out of the top 10 AI labs.

  • AI training and inference costs are driving global cloud demand, expected to exceed $400B in 2025.

  • Google lures startups with big incentives, including $350K in credits and access to Nvidia GPU clusters.

Why it Matters: 

Cloud isn’t just infrastructure—it’s the foundation of the AI race. By locking in early-stage startups with credits and GPU access, Google is betting today’s small spenders could become tomorrow’s billion-dollar customers.

3. Silicon Valley’s New Gold Rush: Training AI Agents in ‘Environments’

Silicon Valley investors and startups are betting big on reinforcement learning (RL) environments — simulated digital workspaces that train AI agents to perform complex tasks. With Anthropic reportedly considering $1B in spending and startups like Mechanize and Prime Intellect entering the race, RL environments are being touted as the “Scale AI” of the agent era.

The Details:

  • RL environments are simulated training grounds where AI agents practice multistep tasks, like buying items online or navigating enterprise software.

  • Big AI labs like OpenAI, Google, and Anthropic are demanding more RL environments to push the frontier of agent training.

  • Data-labeling giants like Scale AI, Surge, and Mercor are pivoting to environments, while startups such as Mechanize and Prime Intellect aim to specialize in them.

  • Mechanize is offering engineers $500K salaries to build environments and has reportedly partnered with Anthropic.

  • Prime Intellect, backed by Andrej Karpathy and major VCs, is building an open hub for RL environments to democratize access.

  • RL environments are resource-intensive, raising new opportunities for GPU providers powering large-scale simulations.

  • Critics warn that environments face scalability challenges, with risks like reward hacking and diminishing returns on reinforcement learning.

Why it Matters: 

RL environments could become the backbone of the next AI breakthrough, enabling agents to move beyond static text and interact with software like real users. But if they fail to scale, Silicon Valley’s billion-dollar bet may prove another hype cycle — with huge implications for the future of AI agents.

Stay tuned for more updates in our next newsletter!

Top 5 AI Tools That Build Apps Faster Than You Can Pitch Them

1.Glide
🔗 https://www.glideapps.com
Glide lets you turn spreadsheets into powerful apps in minutes. Its free plan allows you to build fully functional apps without needing any code, perfect for MVPs and quick prototypes.

2. Gamma
🔗 https://gamma.app/
Create stunning slide decks, documents, and webpages instantly from a prompt. Perfect for founders and professionals who need polished presentations fast.

3.Durable
🔗 https://durable.co/
Generate a complete business website in 30 seconds using AI. From copy to design, it’s done automatically.

4. 10Web
🔗 https://10web.io/
AI-powered WordPress builder that creates SEO-friendly, customizable sites in minutes.

5. TeleportHQ
🔗 https://teleporthq.io/
Design and publish responsive websites visually, then export clean code instantly.

𝐁𝐞𝐢𝐧𝐠 𝐚 𝐫𝐞𝐬𝐢𝐝𝐞𝐧𝐭, 
𝐈 𝐨𝐧𝐜𝐞 𝐭𝐡𝐨𝐮𝐠𝐡𝐭 𝐦𝐲 𝐣𝐨𝐛 𝐰𝐚𝐬 𝐣𝐮𝐬𝐭 𝐭𝐨 𝐭𝐫𝐞𝐚𝐭 𝐩𝐚𝐭𝐢𝐞𝐧𝐭𝐬.

What I didn’t realize? 

Every note I wrote, 
Every lab I ordered, 
Every scan I signed off—was DATA, 

And today, that same data is what fuels AI in healthcare.

Without it, AI is just theory.
With it, AI becomes intelligence.

But here’s the catch: bad data means bad AI.

That’s why we, as clinicians, 
Can’t check out of this conversation. 

AI might crunch the numbers, 
But only humans give it meaning.

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My Latest LinkedIn Posts

𝐖𝐡𝐞𝐧 𝐈 𝐟𝐢𝐫𝐬𝐭 𝐝𝐨𝐯𝐞 𝐢𝐧𝐭𝐨 𝐡𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐀𝐈,  𝐈 𝐰𝐚𝐬 𝐨𝐛𝐬𝐞𝐬𝐬𝐞𝐝 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐦𝐨𝐝𝐞𝐥𝐬. CNNs, LSTMs Neural nets, you name it. I thought that’s where the… | Umer Khan M.

𝐖𝐡𝐞𝐧 𝐈 𝐟𝐢𝐫𝐬𝐭 𝐝𝐨𝐯𝐞 𝐢𝐧𝐭𝐨 𝐡𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐀𝐈,  𝐈 𝐰𝐚𝐬 𝐨𝐛𝐬𝐞𝐬𝐬𝐞𝐝 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐦𝐨𝐝𝐞𝐥𝐬. CNNs, LSTMs Neural nets, you name it. I thought that’s where the breakthroughs lived. But I learned the hard way: The real magic isn’t in the model. It’s in the features you feed it. Because a model is only as smart as the signals it sees. Messy data?  Wrong features?  You’ll get the wrong answers,  No matter how shiny the architecture. What actually moves the needle: 👉 Cleaning and curating relentlessly 👉 Iterating until the right patterns emerge 👉 Picking features with true clinical impact  👉 Blending sources like EHR + imaging + wearables 👉 Partnering with clinicians who know what really matters And that’s when AI stops being a buzzword— and starts saving lives!!! -- Harvey Castro, MD, MBA. Mark Luhovy, MD Raouf Hajji, MD, PhD., Koroush Kabir Sarah Hughes Manuel Mitola Katrina Delargy Daniel Rubinov Mathias Goyen, Prof. Dr.med. Reza Eghbal Johannes Boshkow Patrick Cheng Kai Saeger Dr. Neelam Kaushal The Wharton School (Corporate Governance) Philippe GERWILL Deep D. Timothy Riffe Laura Moritz Helen Yu Nitish Sharma Mike Burger Dee Quang Kevin Chaplin Duke Rem 🐢 Elliott A. Sarah M Worthy Claire Farwell Meenakshi Yadav Dr. Neelam Kaushal The Wharton School (Corporate Governance) Jitendra Dash Abdul Haadi Paul Blocchi

www.linkedin.com/posts/umerkhanmd_%F0%9D%90%96%F0%9D%90%A1%F0%9D%90%9E%F0%9D%90%A7-%F0%9D%90%88-%F0%9D%90%9F%F0%9D%90%A2%F0%9D%90%AB%F0%9D%90%AC%F0%9D%90%AD-%F0%9D%90%9D%F0%9D%90%A8%F0%9D%90%AF%F0%9D%90%9E-%F0%9D%90%A2%F0%9D%90%A7%F0%9D%90%AD%F0%9D%90%A8-activity-7380557370562625536-exKt?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAVJICoBVTDvaS0iUavQ396GucVvFz5q1mA

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👉 Grab it here and start building your first AI-powered app today!

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