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I built a full app with AI - frontend, backend, auth, everything. It ran clean. I almost deployed it. Then I discovered it was missing over half the core features I asked for. Quietly. Silently. No errors. AI agents only see what fits in their context window. They give...

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33,991 views • 1 year ago •via X (Twitter)

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You don’t need a dev team anymore. You need one prompt. Zoer takes your idea and turns it into a fully working app, not just code, but a real product you can use. Here’s what it handles for you: • Database (already structured) • Backend (logic + APIs) • Frontend (clean, production-ready UI) • Auth (Google + email login) • Deployment (live in one click) Most AI tools stop at “here’s your code.” Zoer goes further: It builds the entire system and puts it live. From: “build me a CRM / SaaS / tool” To: A real, working product you can open, test, and share. Try it → No setup. No configs. No extra tools. This is what building should feel like in 2026.
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This is insane Just built a fully working AI Room Designer in minutes, no coding, no API keys, just chatting with OnSpace AI. I use Nano Banana Pro for generation and handles UI, logic, and integration automatically. Not a demo. A real app: • No API setup required – Just told OnSpace to use Nano Banana Pro for content generation and it worked instantly • Full app, not a prototype – Complete UI, logic, and AI integration handled automatically • Actually works – Nails my tone every single time The whole thing came together through conversation. No design work. No wrestling with code. Just described the app and OnSpace made it real. This is what building with AI should feel like. Check my app link in the thread and try it yourself
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AI Frontliner

70,013 views • 8 months ago

I tested a new coding assistant on 34,568 lines of code. (Cursor could not achieve what this tool did.) AI models are improving every day: - Faster inference - Longer context lengths But are AI coding assistants advancing at the same rate? Can they truly understand your entire project? I tested Augment Code on my ai-engineering repo with ~35k lines of code. Augment Code is a powerful AI Assistant built for developers working with large, evolving codebases—needing an assistant that understands the full context of their projects. In the video demo below, I asked it to: - Merge two projects. - Answer a global context question. Here’s what happened: - It understood dependencies across both projects. - It merged them intelligently—without breaking anything. - It even created a README file for the merged project. - It answered my global query instantly, pulling from the full codebase. This is the difference between AI autocomplete and an AI engineer that truly understands your repo. Augment Code is powerful because it indexes your entire repo upfront. This way, it can answer questions instantly, no matter how large your project is. Lastly, Augment Code is fully compatible with VSCode, JetBrains, Vim, Slack, and more. Try them now, I have shared a link in the next tweet! Thanks to Augment Code for showing me their powerful AI coding assistant and working with me on this post.
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Akshay 🚀

30,856 views • 1 year ago

I built a mobile app to check Paddle revenue (because they don't have one): 👉 - Use your Paddle API key (read-only and scoped) - Live data with beautiful and useful graphs built with native Swift UI. - Multi-account supported, unified revenue metrics. - Data stay on device, no server (api requests are sent directly from your phone) - Home widgets - I made it free to download on App Store (once it's approved) - Buy the source code for $19 and customize it however you want (save 5hrs of prompting if you try to do it yourself). Some interesting facts about this side project: - I vibe coded with 100% claude code remotely on my Mac Mini (with my AI assistant setup) in less than 24 hours. - I have read 0 line of code in this project and never opened Xcode myself. - My AI assistant designed the app with GPT Image 2, built the app with Swift UI, test it on simulator (via screenshots), send the test build to TestFlight for me to test, and invited me to the app store connect account so I can test on my phone, then the AI submitted the app to App Store and currently waiting for approval. - For the website, I ask it to come up with a domain name, I bought it via manually and give it access via Cloudflare API, the AI design and create a static website with GitHub, test it with lighthouse CLI, deploy via GitHub pages, config the domain DNS, deploy the website. - Then I sign up an account with Polar payment, create an API key and ask the AI to setup a store, add payment, link with the account, and add the payment to the website. The entire process happened in the last 24 hours with me only talking to the AI via Telegram. This is such a fun side project not only to create an app that I wish exists, but also to push the limit of what I can use AI for, and so far I'm very impressed. I'll create so much more apps! It feels like I have unlocked a super power.
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Tony Dinh

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The Bugged Dev

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MotionViz

21,716 views • 7 months ago

I built the clipboard I always wanted for working with AI agents. It’s called Bluey and It’s 100% local-first. It lives under your mouse cursor. You can draw on your screen, speak to it, or type what you mean, and Bluey turns all of that into rich context for Claude Code or Codex. I’ve been using it to design websites and debug UI because I can finally say things like “move this here” or “make this section feel cleaner” while pointing at the actual screen. No more writing long explanations. No more manually describing screenshots. No more agents getting lost because they don’t know what “this” or "that" means. You can just point to it, speak or type and it will curate the best possible context for your agents Bluey captures the screenshot, annotation, transcript, app/window context, and the details your agent needs, then sends it directly into your coding session. I am giving it out for free for a while! Im building it with my buddy Omkar Satpute and we would love to hear what you think about it on Discord what context do you wish your agent could understand better?
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Well, it appears that turning a Gaussian Splat into a #3D mesh was not that hard after all 😅. I have recently tried an app called KIRI Engine - 3D Scanner App and it offers several nice features that for me made it stand out from many other scanning apps: - It supports both photos and videos - You can clean up the splat directly in the app - It works on both Android, iOS and web! - BUT MOST IMPORTANTLY you can export the mesh making gaussian splitting a much more usable format for various production pipelines. I will be interviewing Jack Wang, the CEO of Kiri for an upcoming episode of XR AI Spotlight: What questions should I ask him?

Gabriele Romagnoli

22,997 views • 1 year ago

Everyone's hyped about making money with Al apps. But here's the truth: It's not the code Al writes that makes money... It's the working, bug-free software that actually runs. Here's how even a complete beginner can ship a production-ready app in 3 steps: Step 1: Ask ChatGPT for a PRD (your blueprint). Step 2: Let Cursor (or any coding Al) generate the app. Step 3: Run it through TestSprite → it auto-tests every function, finds bugs, and hands you a fix report inside your IDE. After several test cycles, I had a polished, bug-free gym app live-no debugging required. That's the real Al game-changer: Not just auto-coding. But auto-testing + auto-fixing. TestSprite is already a top-10 Product Hunt tool and the most popular no-code dev tool of 2025. Try it here:
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Everyone's hyped about making money with Al apps. But here's the truth: It's not the code Al writes that makes money... It's the working, bug-free software that actually runs. Here's how even a complete beginner can ship a production-ready app in 3 steps: Step 1: Ask ChatGPT for a PRD (your blueprint). Step 2: Let Cursor (or any coding Al) generate the app. Step 3: Run it through TestSprite → it auto-tests every function, finds bugs, and hands you a fix report inside your IDE. After several test cycles, I had a polished, bug-free gym app live-no debugging required. That's the real Al game-changer: Not just auto-coding. But auto-testing + auto-fixing. TestSprite is already a top-10 Product Hunt tool and the most popular no-code dev tool of 2025. Try it here:

Tulsi Soni

31,968 views • 11 months ago

Most AI app builders can generate a prototype. The real question is: Can they generate something you can actually launch? I recently explored MeDo, an AI-powered full-stack app generation platform that goes beyond just creating a frontend. With a single prompt, it can generate the frontend UI, backend logic, database structure, and plugin integrations. All in one workflow, without requiring coding or deployment experience. What stood out to me is the focus on building real products rather than simple demos. Whether you're creating SaaS tools, internal dashboards, e-commerce applications, games, or business automation tools. the goal is to move from idea → working product as quickly as possible. A few notable features: ✅ Full-stack generation from a single prompt ✅ Plugin ecosystem with integrations like Stripe and AI tools ✅ Auto bug-fixing capabilities ✅ Website cloning from screenshots ✅ Built-in UI enhancement options ✅ Marketplace of ready-made apps you can customize The AI app builder space is becoming increasingly competitive, and platforms are starting to differentiate themselves based on how close they get to a production-ready result rather than just generating code. For builders, founders, and creators exploring no-code AI development, it's an interesting category worth watching. Try it today and launch your next project with just a prompt:
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Most AI app builders can generate a prototype. The real question is: Can they generate something you can actually launch? I recently explored MeDo, an AI-powered full-stack app generation platform that goes beyond just creating a frontend. With a single prompt, it can generate the frontend UI, backend logic, database structure, and plugin integrations. All in one workflow, without requiring coding or deployment experience. What stood out to me is the focus on building real products rather than simple demos. Whether you're creating SaaS tools, internal dashboards, e-commerce applications, games, or business automation tools. the goal is to move from idea → working product as quickly as possible. A few notable features: ✅ Full-stack generation from a single prompt ✅ Plugin ecosystem with integrations like Stripe and AI tools ✅ Auto bug-fixing capabilities ✅ Website cloning from screenshots ✅ Built-in UI enhancement options ✅ Marketplace of ready-made apps you can customize The AI app builder space is becoming increasingly competitive, and platforms are starting to differentiate themselves based on how close they get to a production-ready result rather than just generating code. For builders, founders, and creators exploring no-code AI development, it's an interesting category worth watching. Try it today and launch your next project with just a prompt:

Markandey Sharma

49,777 views • 2 months ago

Still relying on AI tools that can’t turn your ideas into real, working apps? Most can write code snippets but fall apart when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I simply asked it: “Build a responsive calculator app with a clean UI in light/dark mode.” Within minutes, it built the entire app with a beautiful UI, logic, light/dark mode, animations, and full responsiveness. Literally no setup. No debugging headache. Just vibe coding. Here’s why Replit stands out 👇 ✅ Build in Plain English: Just describe what you want and Replit turns it into a production-ready app. ✅ All-in-One Platform: Code, AI help, hosting, auth, and database, everything you need, already built in. ✅ Vibe Code Anywhere: Build on the go with the Replit mobile app for iOS & Android. ✅ Connected Ecosystem: Integrate with tools you already use like Notion, Slack, Google Drive, Dropbox, and more. ✅ Design to Live App: Import directly from Figma and bring your ideas to life in minutes. No micromanaging. No chaos. Just you, your idea, and Replit doing the heavy lifting. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my referral link. → #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore
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Still relying on AI tools that can’t turn your ideas into real, working apps? Most can write code snippets but fall apart when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I simply asked it: “Build a responsive calculator app with a clean UI in light/dark mode.” Within minutes, it built the entire app with a beautiful UI, logic, light/dark mode, animations, and full responsiveness. Literally no setup. No debugging headache. Just vibe coding. Here’s why Replit stands out 👇 ✅ Build in Plain English: Just describe what you want and Replit turns it into a production-ready app. ✅ All-in-One Platform: Code, AI help, hosting, auth, and database, everything you need, already built in. ✅ Vibe Code Anywhere: Build on the go with the Replit mobile app for iOS & Android. ✅ Connected Ecosystem: Integrate with tools you already use like Notion, Slack, Google Drive, Dropbox, and more. ✅ Design to Live App: Import directly from Figma and bring your ideas to life in minutes. No micromanaging. No chaos. Just you, your idea, and Replit doing the heavy lifting. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my referral link. → #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore

Manish Kumar Shah

52,314 views • 9 months ago

Everyone's talking about vibe coding without looking at code. I was skeptical. I decided to give it a shot on a challenging problem and was blown away by what I could accomplish in 8 hours. I'm not skeptical anymore, but I also do NOT think it kills SaaS Notes: - I tried to replicate some of my favorite features from the Solve-It platform as a jupyter extension - I've tried this many times before, and it didn't work. - I gave my agent specific testing tools that I packaged as skills. I used AI to write the skills. I found the right testing workflow for this Jupyter extension by having AI peruse lots of other extensions and the Jupyter source code. - I had the AI write and maintain a large suite of tests the whole time. I think this was important in keeping the AI on track. - I watched the diffs and the thinking traces as they streamed by. From time to time, I would see something very suspicious like " try ... except: pass" And would stop the AI and tell it to stop this behavior. Then trigger a comprehensive code review using AI. - Most importantly, I don't think this kills SasS at all. Even if I can create software that replicates some of my favorite features, there is an insanely long tail of paper cuts and features I don't want to manage. The models and capabilities are improving so fast that I don't want to constantly tune everything. So I would rather leave that up to people who are focused on that daily and have good taste, with the knowledge that it has been battle tested against many users.
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Everyone's talking about vibe coding without looking at code. I was skeptical. I decided to give it a shot on a challenging problem and was blown away by what I could accomplish in 8 hours. I'm not skeptical anymore, but I also do NOT think it kills SaaS Notes: - I tried to replicate some of my favorite features from the Solve-It platform as a jupyter extension - I've tried this many times before, and it didn't work. - I gave my agent specific testing tools that I packaged as skills. I used AI to write the skills. I found the right testing workflow for this Jupyter extension by having AI peruse lots of other extensions and the Jupyter source code. - I had the AI write and maintain a large suite of tests the whole time. I think this was important in keeping the AI on track. - I watched the diffs and the thinking traces as they streamed by. From time to time, I would see something very suspicious like " try ... except: pass" And would stop the AI and tell it to stop this behavior. Then trigger a comprehensive code review using AI. - Most importantly, I don't think this kills SasS at all. Even if I can create software that replicates some of my favorite features, there is an insanely long tail of paper cuts and features I don't want to manage. The models and capabilities are improving so fast that I don't want to constantly tune everything. So I would rather leave that up to people who are focused on that daily and have good taste, with the knowledge that it has been battle tested against many users.

Hamel Husain

48,930 views • 7 months ago

Shipping speed is up across the board, and AI tools like Gemini 3 Pro are helping us code and build faster than ever. But validation and quality assurance? Still the bottleneck. That’s why I’m integrating TestSprite into my workflow. It analyzes my code and PRD, automatically builds a comprehensive test layer, and keeps my development flow unbroken. No test writing. No last-minute QA chaos. What it covers: ➞ UI Flow Coverage: Verifies real-time updates and synchronization (e.g., confirming gradient sliders and angle controls work together). ➞ Edge Case Validation: Catches subtle logic bugs like inputs accepting out-of-range values that I'd typically miss. ➞ Functionality Check: Automatically runs videos to ensure core features (like "Randomize" and "Copy to Clipboard") are working. ➞ Repeatable Test Suite: Creates tests I can rerun anytime, giving me confidence that new code hasn't broken the old. My new Antigravity + Test Sprite Loop: ➞ AI Plan & Code: Use Antigravity's Planning Mode with Gemini 3 Pro to generate structured code. ➞ Browser Agent QA: Use Antigravity's Open Browser feature to let the AI visually analyze and control the live UI for quick verification. ➞ Validate & Test: Run the automated, reproducible test suite in Test Sprite. ➞ Ship. This loop feels clean, fast, and robust. Works beautifully alongside Gemini 3 Pro, Cloud Sonet, or any AI stack.
22:37

Shipping speed is up across the board, and AI tools like Gemini 3 Pro are helping us code and build faster than ever. But validation and quality assurance? Still the bottleneck. That’s why I’m integrating TestSprite into my workflow. It analyzes my code and PRD, automatically builds a comprehensive test layer, and keeps my development flow unbroken. No test writing. No last-minute QA chaos. What it covers: ➞ UI Flow Coverage: Verifies real-time updates and synchronization (e.g., confirming gradient sliders and angle controls work together). ➞ Edge Case Validation: Catches subtle logic bugs like inputs accepting out-of-range values that I'd typically miss. ➞ Functionality Check: Automatically runs videos to ensure core features (like "Randomize" and "Copy to Clipboard") are working. ➞ Repeatable Test Suite: Creates tests I can rerun anytime, giving me confidence that new code hasn't broken the old. My new Antigravity + Test Sprite Loop: ➞ AI Plan & Code: Use Antigravity's Planning Mode with Gemini 3 Pro to generate structured code. ➞ Browser Agent QA: Use Antigravity's Open Browser feature to let the AI visually analyze and control the live UI for quick verification. ➞ Validate & Test: Run the automated, reproducible test suite in Test Sprite. ➞ Ship. This loop feels clean, fast, and robust. Works beautifully alongside Gemini 3 Pro, Cloud Sonet, or any AI stack.

Dhaval Makwana

110,884 views • 8 months ago

This blew my mind: I just built a fully working end-to-end SaaS storefront in ~15 minutes with MeDo — not just a website, but an actual mini-Shopify stack. It generated the full frontend, backend, UI, auth system, product pages, shopping cart, payments flow, and even gave me a product management dashboard. Then I asked it to switch everything to dark mode… and it restyled the whole app in seconds. For $5 you basically get a SaaS factory: store builder, product manager, checkout system, user accounts, responsive design — all generated and wired together automatically. I never touched a line of code. MeDo feels like having a frontend dev, backend dev, designer, and SaaS architect working in sync, powered by Baidu’s enterprise-grade AI stack. Honestly, the generation quality beats what I’ve seen from Lovable at a much lower price point.
2:02

This blew my mind: I just built a fully working end-to-end SaaS storefront in ~15 minutes with MeDo — not just a website, but an actual mini-Shopify stack. It generated the full frontend, backend, UI, auth system, product pages, shopping cart, payments flow, and even gave me a product management dashboard. Then I asked it to switch everything to dark mode… and it restyled the whole app in seconds. For $5 you basically get a SaaS factory: store builder, product manager, checkout system, user accounts, responsive design — all generated and wired together automatically. I never touched a line of code. MeDo feels like having a frontend dev, backend dev, designer, and SaaS architect working in sync, powered by Baidu’s enterprise-grade AI stack. Honestly, the generation quality beats what I’ve seen from Lovable at a much lower price point.

Chubby♨️

63,919 views • 8 months ago

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base
1:47

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base

Malte Ubl

125,326 views • 7 months ago

This guy took a brand‑new app to #1 overall in the App Store and 1,000,000 downloads in under 3 days. For the FIRST TIME, he breaks down exactly how he did it, and we’re posting the full, RAW conversation right here on X To be clear, this is his first and only podcast on this playbook... And a little more context: this wasn’t luck. Jibran has taken 4 different apps to #1 in the App Store, including one that did $1.5M in 3 days and outranked ChatGPT He did it with a handful of creators, zero paid ads, and a product philosophy that blew my mind Here’s the core of what he taught me: > Your product and your marketing are not two separate things; they're the same thing. > What goes viral on TikTok is product validation. > What you learn from a hit video should change your UI, your App Store screenshots, your icon He ran that loop obsessively.. For his 2025 Wrapped app, he spent hundreds of hours in Figma asking one question: > “How does this look on TikTok?” Then he tracked: 1. What users screenshotted 2. What they shared to Snapchat 3. What slide they dropped off on The result was a #1 overall app in the App Store. Above EVERYTHING. Now he’s building because he realized he was spending hours every day doom‑scrolling TikTok looking for hooks and formats that worked So he built an AI to do it for him: > You tell it your app. > It tells you what to post, what’s trending in your niche, and what’s wrong with your existing videos. We go deep on all of it in this conversation. If you run a consumer app, this is the most useful 49 minutes you’ll spend this week
49:02

This guy took a brand‑new app to #1 overall in the App Store and 1,000,000 downloads in under 3 days. For the FIRST TIME, he breaks down exactly how he did it, and we’re posting the full, RAW conversation right here on X To be clear, this is his first and only podcast on this playbook... And a little more context: this wasn’t luck. Jibran has taken 4 different apps to #1 in the App Store, including one that did $1.5M in 3 days and outranked ChatGPT He did it with a handful of creators, zero paid ads, and a product philosophy that blew my mind Here’s the core of what he taught me: > Your product and your marketing are not two separate things; they're the same thing. > What goes viral on TikTok is product validation. > What you learn from a hit video should change your UI, your App Store screenshots, your icon He ran that loop obsessively.. For his 2025 Wrapped app, he spent hundreds of hours in Figma asking one question: > “How does this look on TikTok?” Then he tracked: 1. What users screenshotted 2. What they shared to Snapchat 3. What slide they dropped off on The result was a #1 overall app in the App Store. Above EVERYTHING. Now he’s building because he realized he was spending hours every day doom‑scrolling TikTok looking for hooks and formats that worked So he built an AI to do it for him: > You tell it your app. > It tells you what to post, what’s trending in your niche, and what’s wrong with your existing videos. We go deep on all of it in this conversation. If you run a consumer app, this is the most useful 49 minutes you’ll spend this week

Alex Olim

106,009 views • 4 months ago