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I got rejected by Apple for the 3rd time. Fixed everything and resubmitted. Used the wait time to: > Add dark mode 🌙 > Create new mascot animations for dark mode > Improve food scanning speed Meanwhile, I spun up an AI influencer farm for TikTok. Another warmed-up post...

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Alex Nguyen

66,876 subscribers

71,903 görüntüleme • 8 ay önce •via X (Twitter)

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Got rejected by Apple on the first review. I fixed everything, resubmitted, and used the time to polish the product instead of waiting. Added smooth animations, improved water logging. Meanwhile, I spun up an AI influencer farm for TikTok, first warmed-up post hit 50K views. Rejection = free time to build distribution. Keep going 💪 Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS (for my next app, I’ll go back to NestJS) – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)
0:19

Got rejected by Apple on the first review. I fixed everything, resubmitted, and used the time to polish the product instead of waiting. Added smooth animations, improved water logging. Meanwhile, I spun up an AI influencer farm for TikTok, first warmed-up post hit 50K views. Rejection = free time to build distribution. Keep going 💪 Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS (for my next app, I’ll go back to NestJS) – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)

Alex Nguyen

176,752 görüntüleme • 8 ay önce

It’s been 10+ days since I submitted my app to Apple Still waiting for review 😌 Lesson learned: don’t submit your app during holidays. But not a loss. While waiting, I: – Updated the paywall – Added a first-time close discount – Improved conversion rate (i hope) 📈 Marketing progress: - I’ve finished warming up 3 TikTok accounts and have started posting the first videos. Sometimes delays are just free optimization time. Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)
0:16

It’s been 10+ days since I submitted my app to Apple Still waiting for review 😌 Lesson learned: don’t submit your app during holidays. But not a loss. While waiting, I: – Updated the paywall – Added a first-time close discount – Improved conversion rate (i hope) 📈 Marketing progress: - I’ve finished warming up 3 TikTok accounts and have started posting the first videos. Sometimes delays are just free optimization time. Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)

Alex Nguyen

151,002 görüntüleme • 8 ay önce

How I target US users for my B2C apps: > Buy a used iPhone (~$120) > VPN to the US > Warm up the account 3–7 days like a normal user > Pick a TikTok niche that’s already viral + fits your product (If your app isn’t Gen Z / 16–30 friendly, TikTok may not work) > Build an AI content factory / AI influencers > Post daily > If a video stays under 0->1k views → change content fast Instead of burning $200–$2,000/week hiring UGC creators. I build an AI influencer army at almost $0 cost. Virality doesn’t always happen immediately after posting. For example, the video below was posted at the end of last December and only got ~2k views at first. Today, it just started going viral, reaching 214k+ views in a few days (and it’s still growing). Consistency > luck. Distribution > everything.
0:13

How I target US users for my B2C apps: > Buy a used iPhone (~$120) > VPN to the US > Warm up the account 3–7 days like a normal user > Pick a TikTok niche that’s already viral + fits your product (If your app isn’t Gen Z / 16–30 friendly, TikTok may not work) > Build an AI content factory / AI influencers > Post daily > If a video stays under 0->1k views → change content fast Instead of burning $200–$2,000/week hiring UGC creators. I build an AI influencer army at almost $0 cost. Virality doesn’t always happen immediately after posting. For example, the video below was posted at the end of last December and only got ~2k views at first. Today, it just started going viral, reaching 214k+ views in a few days (and it’s still growing). Consistency > luck. Distribution > everything.

Alex Nguyen

147,890 görüntüleme • 8 ay önce

From a factory worker to a full-stack developer in 1.5 years of grind. I’m not saying this to flex. I’m saying this because I didn’t believe it was possible either. 1.5 years ago, I was working in a vegetables factory. 10 hours a day. Packing. Picking. Standing. Physically exhausting. Mentally draining. I had dropped out of college because of financial issues. This felt like the end of the road. A friend told me: “Try learning to code.” I saved whatever money I could. Took some help from my parents. Bought a laptop. Quit the factory job. For a while, the internet became my university. I kept remembering something Elon Musk once said: “Everything you need to learn is available on the internet for free.” I used that line like a rule. HTML, CSS, JavaScript one month. Then React. No fancy courses. Just docs, projects, and breaking things. Got my first internship. Struggled. Learned. Improved. After 4 months, I pushed harder: – Deep React (no tutorial hopping) – Backend basics – Some DSA That grind got me a full-stack role at a US-based company (onsite in Bhopal). Life tested me again when my grandfather the person I always looked up to had a heart attack. It broke me. I quit. Took time. Regrouped. Started freelancing. Got 2 to 3 projects. Kept moving forward. My journey hasn’t been clean. It’s been messy, uncertain, and uncomfortable. But here I am. 2025 was just a warm-up. 2026 is execution. If you’re starting from zero don’t underestimate what 1–2 years of focused grind can do.
0:10

From a factory worker to a full-stack developer in 1.5 years of grind. I’m not saying this to flex. I’m saying this because I didn’t believe it was possible either. 1.5 years ago, I was working in a vegetables factory. 10 hours a day. Packing. Picking. Standing. Physically exhausting. Mentally draining. I had dropped out of college because of financial issues. This felt like the end of the road. A friend told me: “Try learning to code.” I saved whatever money I could. Took some help from my parents. Bought a laptop. Quit the factory job. For a while, the internet became my university. I kept remembering something Elon Musk once said: “Everything you need to learn is available on the internet for free.” I used that line like a rule. HTML, CSS, JavaScript one month. Then React. No fancy courses. Just docs, projects, and breaking things. Got my first internship. Struggled. Learned. Improved. After 4 months, I pushed harder: – Deep React (no tutorial hopping) – Backend basics – Some DSA That grind got me a full-stack role at a US-based company (onsite in Bhopal). Life tested me again when my grandfather the person I always looked up to had a heart attack. It broke me. I quit. Took time. Regrouped. Started freelancing. Got 2 to 3 projects. Kept moving forward. My journey hasn’t been clean. It’s been messy, uncertain, and uncomfortable. But here I am. 2025 was just a warm-up. 2026 is execution. If you’re starting from zero don’t underestimate what 1–2 years of focused grind can do.

Sambhav.apk▲

32,712 görüntüleme • 8 ay önce

For new followers: - I'm a long-time investor and builder in this space. - Founding Contributor of Realms.World ☁️. - Co-founder of Dojo. - Builder with the kings at Cartridge. - Starknet (Privacy Arc) class of '21. - Founder and Game Director of ETERNUM HAS MOVED. - Founder of Daydreams.Systems (x402, 8004 agents) My prime purpose for the past three years has been to build onchain infrastructure to enable the next generation of onchain experiences. This is done Starknet (Privacy Arc) as it is the superior VM for building complex applications—this will become clear soon enough. I work up and down the entire stack, from low-level indexing and contracts to GUI design. Nothing is out of scope. I have been pushing on agents for two years, mostly using existing frameworks like , until I came across @ElizaOS_ai in October. As I focused on building agents for ETERNUM HAS MOVED, it became clear that agents playing games require infinite paths to achieve goals. Thus, it's not scalable to hardcode functions—agents need to have total fluidity to take any action or call anything the game requires in any order. And ironically onchain infra is perfect for agent playgrounds because of its open nature. This exploration led me to create Daydreams.Systems (x402, 8004 agents), which focuses on the hardest problems of agents: long time-horizon goals using Hierarchical task networks (HTN). Daydreams agents don't require custom code—they work entirely based on 'sleeves'—which are just markdown files that explain how the agent can interact with the service (API docs, game guides, etc.) My thesis is simple. By focusing on the hardest problem (games), the design of the library will naturally lean towards an optimal structure for any problem an agent could face. We are early in this path and iterating with speed. If you are an onchain app developer or game builder—DM me, I want to know the architecture of your game so we can build sleeves together.
0:10

For new followers: - I'm a long-time investor and builder in this space. - Founding Contributor of Realms.World ☁️. - Co-founder of Dojo. - Builder with the kings at Cartridge. - Starknet (Privacy Arc) class of '21. - Founder and Game Director of ETERNUM HAS MOVED. - Founder of Daydreams.Systems (x402, 8004 agents) My prime purpose for the past three years has been to build onchain infrastructure to enable the next generation of onchain experiences. This is done Starknet (Privacy Arc) as it is the superior VM for building complex applications—this will become clear soon enough. I work up and down the entire stack, from low-level indexing and contracts to GUI design. Nothing is out of scope. I have been pushing on agents for two years, mostly using existing frameworks like , until I came across @ElizaOS_ai in October. As I focused on building agents for ETERNUM HAS MOVED, it became clear that agents playing games require infinite paths to achieve goals. Thus, it's not scalable to hardcode functions—agents need to have total fluidity to take any action or call anything the game requires in any order. And ironically onchain infra is perfect for agent playgrounds because of its open nature. This exploration led me to create Daydreams.Systems (x402, 8004 agents), which focuses on the hardest problems of agents: long time-horizon goals using Hierarchical task networks (HTN). Daydreams agents don't require custom code—they work entirely based on 'sleeves'—which are just markdown files that explain how the agent can interact with the service (API docs, game guides, etc.) My thesis is simple. By focusing on the hardest problem (games), the design of the library will naturally lean towards an optimal structure for any problem an agent could face. We are early in this path and iterating with speed. If you are an onchain app developer or game builder—DM me, I want to know the architecture of your game so we can build sleeves together.

loaf

43,320 görüntüleme • 1 yıl önce

How to build a viral Web3 app in an afternoon using the ChainGPT AI skill for Claude Code. No coding experience required. I built Roast My Wallet. Paste any Ethereum wallet address, get a savage AI-generated roast of your trading history, a Degen Score out of 100, an on-chain report card, and three AI-generated NFT portraits. Here's exactly how it came together. Setup (3 minutes): 🔸Install Claude Code at 🔸Run /plugin install ChainGPT-org/chaingpt-claude-skill 🔸Get an API key at 🔸Type /chaingpt and describe what you want to build What the skill actually does: The ChainGPT skill doesn't just give you starter code. It knows the entire API. Every endpoint, every parameter, every credit cost, every error code. When I asked it to build the roast feature, it knew to call the LLM endpoint, how to stream the response back to the browser in real time, and how to handle errors automatically. I didn't look up a single thing. How it works under the hood: 1. Pulls real ETH balance and transaction count from the Ethereum blockchain 2. Feeds those numbers into ChainGPT's LLM and streams the roast back live 3. Calculates a Degen Score from your tx count vs balance ratio 4. Generates a report card with letter grades across Trading, Patience, Risk, Diamond Hands, and NGMI 5. Uses the roast text to generate three custom NFT portraits in parallel via VeloGen 6. Packages everything into a downloadable PNG card ready to post 7. Every feature came from describing what I wanted: 8. "Make the API key server-side." Done. 9. "Add an animated arc gauge for the degen score." Done. 10. "Generate NFT portraits using the roast text as context." Done. I never wrote a function or debugged an API response. I described outcomes. The ChainGPT skill handled the rest. If you can describe what you want to build, you can build it. Get your API key. Install the skill. /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build with ChainGPT AI!
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How to build a viral Web3 app in an afternoon using the ChainGPT AI skill for Claude Code. No coding experience required. I built Roast My Wallet. Paste any Ethereum wallet address, get a savage AI-generated roast of your trading history, a Degen Score out of 100, an on-chain report card, and three AI-generated NFT portraits. Here's exactly how it came together. Setup (3 minutes): 🔸Install Claude Code at 🔸Run /plugin install ChainGPT-org/chaingpt-claude-skill 🔸Get an API key at 🔸Type /chaingpt and describe what you want to build What the skill actually does: The ChainGPT skill doesn't just give you starter code. It knows the entire API. Every endpoint, every parameter, every credit cost, every error code. When I asked it to build the roast feature, it knew to call the LLM endpoint, how to stream the response back to the browser in real time, and how to handle errors automatically. I didn't look up a single thing. How it works under the hood: 1. Pulls real ETH balance and transaction count from the Ethereum blockchain 2. Feeds those numbers into ChainGPT's LLM and streams the roast back live 3. Calculates a Degen Score from your tx count vs balance ratio 4. Generates a report card with letter grades across Trading, Patience, Risk, Diamond Hands, and NGMI 5. Uses the roast text to generate three custom NFT portraits in parallel via VeloGen 6. Packages everything into a downloadable PNG card ready to post 7. Every feature came from describing what I wanted: 8. "Make the API key server-side." Done. 9. "Add an animated arc gauge for the degen score." Done. 10. "Generate NFT portraits using the roast text as context." Done. I never wrote a function or debugged an API response. I described outcomes. The ChainGPT skill handled the rest. If you can describe what you want to build, you can build it. Get your API key. Install the skill. /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build with ChainGPT AI!

ChainGPT

29,339 görüntüleme • 4 ay önce

I just sold my startup Talknotes for $200,000 on acquire.com 💸🤯🤩💰🥳🎉 I launched it last August when I was looking for an idea I could grow with paid ads, and made a MVP in one week. I took it from $0 to $7500 MRR in just 11 months. 👉 Here is how I grew it from zero: 💡 Idea: I got the idea when I tried to write a tweet using Google Doc's transcription tool, but it was terrible. And I was pretty sure I wasn't the one too lazy to type. So I made my own solution, and Talknotes was created. The audience is pretty broad so it was a perfect fit for Meta ads However… ✅ Validation: My rule is to only reinvest what the project generates, so, no ads until I make enough cashflow ❌ Listing on startup directories + a few Twitter sales generated $700 after 10 days. Yes, it's not much, but more than enough to show there is interest in the product and tell me to keep working on it 🤩 I started adding the features users requested, but the launch effect started to wear off and daily revenues quickly went to $0 after a few weeks 🫥 I got depressed and almost gave up on the app... 😔 But luckily, my friends and Dan Kulkov pushed me to continue And I'm glad they did because In October, I launched on Product Hunt 😸 and it blew up 🤯 It got Product of the Day and reached $1500 MRR thanks to the media coverage 🚀🚀 Until then, everything was done using vanilla JS/CSS/HTML + Node for back end. It's simple and easy, but I saw the limitations, so I remade the app using Nuxt to make it easier in the future 🏗️ (thanks to @blackevilgoblin and Piotr Jura for the content/courses! Tim Bennetto as well for the basics!) After that, I took a break and then launched ads on Facebook. The strategy is simple: Catch people's attention, and show them how the app can help them improve their life. No need to over-complicate 🙅‍♂️ Making good creatives is 80% of the job when doing ads on Facebook, most of the technical stuff is done by AI now. Thanks to the boost in traffic, I implemented a feedback loop: 1) Get new users 👥 2) Learn to know them with the onboarding form 💬 3) Make more ads based on the data you get from onboarding 📝 And it completely blew up. MRR doubled in ~2 months However... In May, I had a bad burnout 🥵😩 Multiple bugs slipped into the app, and I had to spend 2 days fixing everything in an emergency while revenues plummeted. This completely fucked me up mentally and had a hard time working on the app after that ( 💀💀 So I decided to list it on acquire.com and made a Twitter post ( I listed it for $200,000, a pretty low price considering the revenues and fast growth. I could have gotten $300,000 if I accepted payment over time, but $200,000 today is better than $300,000 tomorrow for me. 🚨 The process went smoothly until we tried to use Escrow, which almost fucked up the whole deal. (details: I got extremely lucky because the buyer really wanted to buy the app, but this could have ended the deal. We had to wait over a week to get the money back from them, even tho they said they already refunded it. But luckily, after threatening them, they sent it back the next day 🙃 The buyer finally got the money back, I transferred every asset to him, and he sent me the wire. With the profit made from the app + the sale, and other projects, I'm 30% away from being a millionaire 🤯 With this amount, I can pretty much retire in Asia if I want to. But that's just the beginning, I’m going to launch new projects soon! 🚀 But before that, I need to take a real vacation and detox. My brain is completely fucked up by those last 2 months. I gained weight, and got brain rot from scrolling all day waiting for the acquisition to move forward 💀💀 Surprisingly, doing absolutely nothing is 10x more exhausting than working 15h per day 🥱 Now, all this might sound like an overnight success. It is not ‼️ This is the result of 7 years of failure and working like a madman. I launched over 40 projects in those 7 years, and most of them failed. But a few took off, and that’s all I needed All those weeks working 15h/day without weekends and vacation feels soul-sucking when you don’t see the end, but this is what took me there You only need to win once to snowball everything. Work hard, focus, fail a lot and keep shipping fast. 🚀🚀 Thanks to you for reading until here, and thanks to everyone who supported me 🤞
0:10

I just sold my startup Talknotes for $200,000 on acquire.com 💸🤯🤩💰🥳🎉 I launched it last August when I was looking for an idea I could grow with paid ads, and made a MVP in one week. I took it from $0 to $7500 MRR in just 11 months. 👉 Here is how I grew it from zero: 💡 Idea: I got the idea when I tried to write a tweet using Google Doc's transcription tool, but it was terrible. And I was pretty sure I wasn't the one too lazy to type. So I made my own solution, and Talknotes was created. The audience is pretty broad so it was a perfect fit for Meta ads However… ✅ Validation: My rule is to only reinvest what the project generates, so, no ads until I make enough cashflow ❌ Listing on startup directories + a few Twitter sales generated $700 after 10 days. Yes, it's not much, but more than enough to show there is interest in the product and tell me to keep working on it 🤩 I started adding the features users requested, but the launch effect started to wear off and daily revenues quickly went to $0 after a few weeks 🫥 I got depressed and almost gave up on the app... 😔 But luckily, my friends and Dan Kulkov pushed me to continue And I'm glad they did because In October, I launched on Product Hunt 😸 and it blew up 🤯 It got Product of the Day and reached $1500 MRR thanks to the media coverage 🚀🚀 Until then, everything was done using vanilla JS/CSS/HTML + Node for back end. It's simple and easy, but I saw the limitations, so I remade the app using Nuxt to make it easier in the future 🏗️ (thanks to @blackevilgoblin and Piotr Jura for the content/courses! Tim Bennetto as well for the basics!) After that, I took a break and then launched ads on Facebook. The strategy is simple: Catch people's attention, and show them how the app can help them improve their life. No need to over-complicate 🙅‍♂️ Making good creatives is 80% of the job when doing ads on Facebook, most of the technical stuff is done by AI now. Thanks to the boost in traffic, I implemented a feedback loop: 1) Get new users 👥 2) Learn to know them with the onboarding form 💬 3) Make more ads based on the data you get from onboarding 📝 And it completely blew up. MRR doubled in ~2 months However... In May, I had a bad burnout 🥵😩 Multiple bugs slipped into the app, and I had to spend 2 days fixing everything in an emergency while revenues plummeted. This completely fucked me up mentally and had a hard time working on the app after that ( 💀💀 So I decided to list it on acquire.com and made a Twitter post ( I listed it for $200,000, a pretty low price considering the revenues and fast growth. I could have gotten $300,000 if I accepted payment over time, but $200,000 today is better than $300,000 tomorrow for me. 🚨 The process went smoothly until we tried to use Escrow, which almost fucked up the whole deal. (details: I got extremely lucky because the buyer really wanted to buy the app, but this could have ended the deal. We had to wait over a week to get the money back from them, even tho they said they already refunded it. But luckily, after threatening them, they sent it back the next day 🙃 The buyer finally got the money back, I transferred every asset to him, and he sent me the wire. With the profit made from the app + the sale, and other projects, I'm 30% away from being a millionaire 🤯 With this amount, I can pretty much retire in Asia if I want to. But that's just the beginning, I’m going to launch new projects soon! 🚀 But before that, I need to take a real vacation and detox. My brain is completely fucked up by those last 2 months. I gained weight, and got brain rot from scrolling all day waiting for the acquisition to move forward 💀💀 Surprisingly, doing absolutely nothing is 10x more exhausting than working 15h per day 🥱 Now, all this might sound like an overnight success. It is not ‼️ This is the result of 7 years of failure and working like a madman. I launched over 40 projects in those 7 years, and most of them failed. But a few took off, and that’s all I needed All those weeks working 15h/day without weekends and vacation feels soul-sucking when you don’t see the end, but this is what took me there You only need to win once to snowball everything. Work hard, focus, fail a lot and keep shipping fast. 🚀🚀 Thanks to you for reading until here, and thanks to everyone who supported me 🤞

Nico

458,682 görüntüleme • 2 yıl önce

CoinMarketCap AI Is Live: What Does It Really Change ? 🌱 In the fast paced world of crypto, information is power but its often scattered, delayed, or hard to trust. CoinMarketCap newly launched CMC AI aims to fix that by offering real time insights with no friction. ✨ Real Time Q&A on Coin Pages 🌱CMC AI is now integrated into major coin detail pages, generating automatic Q&As every 30 minutes. During periods of volatility, it updates dynamically, helping users understand price movements with short and structured explanations. No login required, no delays. 🌱However, while this speeds up the process, its not a substitute for deeper analysis. It answers the “what” and “why,” but not always the “what’s next.” ✨What’s Coming Next? 🌱CMC AI is just getting started. According to its roadmap, several new features are on the way • Homepage Integration: A quick view of market trends and opportunities, without clicking into individual coins. • Live Chart Analysis: AI will add context to price moves by linking them to news, sentiment, and social media. • Token Comparison Tool: Users will be able to compare tokens like BTC vs SOL across utility, performance, and tech specs. • Portfolio Insights: One click portfolio analysis with rebalancing suggestions and market outlooks. • Cross Device Continuity: Start an AI conversation on desktop and continue it seamlessly on mobile. ✨A Tool Not a Strategy 🌱 CMC AI brings speed and clarity, two things crypto investors often lack. But it’s still just a tool. It won’t make decisions for you. It helps guide your thinking not replace it. 🌱 The smartest way to use it? Treat it as a compass, not a map. It can point you in the right direction, but the journey is still yours. 🌱 CMC AI represents a step forward in how users interact with crypto data. It filters the noise, shortens research time, and brings useful context closer to the user. But like any shortcut, it works best when you already understand the long route.
0:11

CoinMarketCap AI Is Live: What Does It Really Change ? 🌱 In the fast paced world of crypto, information is power but its often scattered, delayed, or hard to trust. CoinMarketCap newly launched CMC AI aims to fix that by offering real time insights with no friction. ✨ Real Time Q&A on Coin Pages 🌱CMC AI is now integrated into major coin detail pages, generating automatic Q&As every 30 minutes. During periods of volatility, it updates dynamically, helping users understand price movements with short and structured explanations. No login required, no delays. 🌱However, while this speeds up the process, its not a substitute for deeper analysis. It answers the “what” and “why,” but not always the “what’s next.” ✨What’s Coming Next? 🌱CMC AI is just getting started. According to its roadmap, several new features are on the way • Homepage Integration: A quick view of market trends and opportunities, without clicking into individual coins. • Live Chart Analysis: AI will add context to price moves by linking them to news, sentiment, and social media. • Token Comparison Tool: Users will be able to compare tokens like BTC vs SOL across utility, performance, and tech specs. • Portfolio Insights: One click portfolio analysis with rebalancing suggestions and market outlooks. • Cross Device Continuity: Start an AI conversation on desktop and continue it seamlessly on mobile. ✨A Tool Not a Strategy 🌱 CMC AI brings speed and clarity, two things crypto investors often lack. But it’s still just a tool. It won’t make decisions for you. It helps guide your thinking not replace it. 🌱 The smartest way to use it? Treat it as a compass, not a map. It can point you in the right direction, but the journey is still yours. 🌱 CMC AI represents a step forward in how users interact with crypto data. It filters the noise, shortens research time, and brings useful context closer to the user. But like any shortcut, it works best when you already understand the long route.

Loji

37,459 görüntüleme • 1 yıl önce

"Pros won’t use generative AI, and when the bubble pops, nobody will ever talk about it again." No. That’s delusional. 1/ Generative AI is already being used professionally at the level of big studios like Disney ($1B to OpenAI), and there’s zero doubt that studios like Industrial Light & Magic, Netflix, Hollywood VFX experts, etc. are already experimenting with it too. Or do you think they’re idiots? They’re not idiots at all. They have the experience and, more importantly, the DISTRIBUTION POWER. The point is: someone with taste, judgment, and storytelling experience, basically from their living room, will have access to (almost, or not even almost) the same capability as the big guys, because the pure "making stuff" skills have been commoditized, and the new way to create is just NATURAL LANGUAGE. What hasn’t been commoditized is good taste, the ability to create great stories that move people, and the ability to get them in front of people. So in the end, what wins is story quality and distribution. Having good taste, making a name for yourself, and owning strong IP (Marvel, etc.) will still matter. That’ll be true right up until AI is genuinely opinionated and can create by itself: if it comes to that, with zero human direction, stuff as good as (or better than) the very best human experts today, and on top of that, interactive in real time... Because yeah: there’s nothing in this universe that actually prevents that from happening. BUT WE’RE NOT THERE. For now, generative AI is a tool that needs direction and taste to make anything decent. And I hope it stays that way for a long time, because otherwise that’s going to be a brutal hit to humanity’s ego. 2/ On the "bubble": you have to distinguish between a stock valuation bubble (possible, I actually believe it) vs a bubble like some people imagine where it "pops" and we never hear about AI again. That obviously makes no sense given how insanely useful it is. It can only grow, and it’s going to grow fast, regardless of any stock market drawdowns (the internet kept growing even when valuations got nuked in 2000). Either way, the near future is going to be extremely interesting.
0:15

"Pros won’t use generative AI, and when the bubble pops, nobody will ever talk about it again." No. That’s delusional. 1/ Generative AI is already being used professionally at the level of big studios like Disney ($1B to OpenAI), and there’s zero doubt that studios like Industrial Light & Magic, Netflix, Hollywood VFX experts, etc. are already experimenting with it too. Or do you think they’re idiots? They’re not idiots at all. They have the experience and, more importantly, the DISTRIBUTION POWER. The point is: someone with taste, judgment, and storytelling experience, basically from their living room, will have access to (almost, or not even almost) the same capability as the big guys, because the pure "making stuff" skills have been commoditized, and the new way to create is just NATURAL LANGUAGE. What hasn’t been commoditized is good taste, the ability to create great stories that move people, and the ability to get them in front of people. So in the end, what wins is story quality and distribution. Having good taste, making a name for yourself, and owning strong IP (Marvel, etc.) will still matter. That’ll be true right up until AI is genuinely opinionated and can create by itself: if it comes to that, with zero human direction, stuff as good as (or better than) the very best human experts today, and on top of that, interactive in real time... Because yeah: there’s nothing in this universe that actually prevents that from happening. BUT WE’RE NOT THERE. For now, generative AI is a tool that needs direction and taste to make anything decent. And I hope it stays that way for a long time, because otherwise that’s going to be a brutal hit to humanity’s ego. 2/ On the "bubble": you have to distinguish between a stock valuation bubble (possible, I actually believe it) vs a bubble like some people imagine where it "pops" and we never hear about AI again. That obviously makes no sense given how insanely useful it is. It can only grow, and it’s going to grow fast, regardless of any stock market drawdowns (the internet kept growing even when valuations got nuked in 2000). Either way, the near future is going to be extremely interesting.

Javi Lopez ⛩️

75,277 görüntüleme • 7 ay önce

For the past few weeks I’ve been teaching 50+ kids how to create their own games with AI. The results have been incredible 🤯 I started with my 5 y/o nephew because I was worried about him spending hours doomscrolling and consuming brainrot content. He built his first game using v0, though I had to walk him through each step. Watching kids interact with these tools taught me so much about how they think, where they get stuck, and what keeps them motivated. The moment that really struck me came right after he finished that first game. Every time I saw him afterward, he’d run up and ask, “Did you bring your laptop so I can keep playing?”. For him, “playing” meant creating. That kind of excitement is organic pull. Don’t get me wrong, I love v0 and Lovable. They’re insanely powerful. Their UIs just aren’t designed for kids, and that’s totally fine. Kids still need guidance, structure, and a bit of tutoring to turn ideas into something playable. I’m seeing tech leaders push in this direction too, and I think there’s a real opportunity here (Matias Woloski Thomas Wolf). Kids are the future, and I don’t want to live in a world where they spend precious time consuming instead of creating. That’s why I love tools like v0, Lovable, wabi , Cursor . They’re empowering more people to become creators. I want that same feeling for kids. What Guillermo is saying is real. Kids need to be AI-literate from the outset. It honestly makes me sad to think about my nephew growing up and falling behind on AI and everything happening around him because he’s stuck in Roblox or TikTok. That’s why I built Rabbit 🐰 for him. It started as a simple prototype, but somehow I ended up talking with 200+ parents and kids, tech leaders, investors, and people I never imagined meeting around the world. Rabbit now has 100+ people on the waitlist, and 10 kids are using it two to three times per week on average to create their own games 🫡 I’m not sure yet if this will become my full-time project, but I deeply care about it. If you’re building in this space, I’d love to connect and share ideas. And if you’re a parent interested in Rabbit, I’d love your feedback. Sharing a short video of kids using Rabbit below:
0:07

For the past few weeks I’ve been teaching 50+ kids how to create their own games with AI. The results have been incredible 🤯 I started with my 5 y/o nephew because I was worried about him spending hours doomscrolling and consuming brainrot content. He built his first game using v0, though I had to walk him through each step. Watching kids interact with these tools taught me so much about how they think, where they get stuck, and what keeps them motivated. The moment that really struck me came right after he finished that first game. Every time I saw him afterward, he’d run up and ask, “Did you bring your laptop so I can keep playing?”. For him, “playing” meant creating. That kind of excitement is organic pull. Don’t get me wrong, I love v0 and Lovable. They’re insanely powerful. Their UIs just aren’t designed for kids, and that’s totally fine. Kids still need guidance, structure, and a bit of tutoring to turn ideas into something playable. I’m seeing tech leaders push in this direction too, and I think there’s a real opportunity here (Matias Woloski Thomas Wolf). Kids are the future, and I don’t want to live in a world where they spend precious time consuming instead of creating. That’s why I love tools like v0, Lovable, wabi , Cursor . They’re empowering more people to become creators. I want that same feeling for kids. What Guillermo is saying is real. Kids need to be AI-literate from the outset. It honestly makes me sad to think about my nephew growing up and falling behind on AI and everything happening around him because he’s stuck in Roblox or TikTok. That’s why I built Rabbit 🐰 for him. It started as a simple prototype, but somehow I ended up talking with 200+ parents and kids, tech leaders, investors, and people I never imagined meeting around the world. Rabbit now has 100+ people on the waitlist, and 10 kids are using it two to three times per week on average to create their own games 🫡 I’m not sure yet if this will become my full-time project, but I deeply care about it. If you’re building in this space, I’d love to connect and share ideas. And if you’re a parent interested in Rabbit, I’d love your feedback. Sharing a short video of kids using Rabbit below:

Fausto

44,125 görüntüleme • 8 ay önce

If you’ve ever managed custom icons in React Native, you know the frustration of choosing between performance and developer experience. Libraries like 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝘀𝘃𝗴 are flexible but heavy. Every icon creates its own React subtree. The alternative? Manual icon fonts that force you into a constant back-and-forth of using web tools like IcoMoon and syncing font assets every time a design changes. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 𝗟𝗮𝗯𝘀 just released 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 to solve exactly this. It’s a build-time icon font generator that gives you the performance of native fonts with the flexibility of simple SVG files. 𝗪𝗵𝗮𝘁’𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴? Instead of rendering complex vector paths at runtime, this library automatically converts your folder of SVGs into an optimized icon font during the build process. It essentially teaches your app to treat icons like standard text characters, which allows it to bypass React’s component tree and layout engine entirely. ➡️ 𝗕𝘂𝗶𝗹𝗱-𝘁𝗶𝗺𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: It handles the entire pipeline—watching your icon folder, converting SVGs to .ttf files, and linking them to your native project automatically. ➡️ 𝗡𝗮𝘁𝗶𝘃𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Because icons render as native text glyphs, it is significantly faster than traditional SVG rendering, making it the ideal choice for long, scrollable lists or icon-heavy dashboards. ➡️ 𝗘𝘅𝗽𝗼 𝗖𝗼𝗻𝗳𝗶𝗴 𝗣𝗹𝘂𝗴𝗶𝗻: It features first-class support for Expo, automating the native plumbing like Info.plist updates and asset linking during the prebuild phase. ➡️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗧𝘆𝗽𝗲 𝗦𝗮𝗳𝗲𝘁𝘆: The library generates TypeScript definitions for your icon set, providing full IDE autocomplete and ensuring you never break the UI with a misspelled icon name. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀? In high-performance applications, small overheads add up. By shifting the heavy lifting from the mobile device to your build machine, 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 ensures your UI stays buttery smooth while keeping your developer workflow modern. It’s another great example of how 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 continues to solve the "last mile" of performance friction in the ecosystem. Before you migrate your entire library, keep in mind: this is designed for the 𝗡𝗲𝘄 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (Fabric) and requires React Native 0.74 or higher. #ReactNative #Expo #SoftwareMansion #Icons #MobileDev #Performance #DeveloperExperience #OpenSource #JavaScript #TypeScript #SVG #Fabric
0:15

If you’ve ever managed custom icons in React Native, you know the frustration of choosing between performance and developer experience. Libraries like 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝘀𝘃𝗴 are flexible but heavy. Every icon creates its own React subtree. The alternative? Manual icon fonts that force you into a constant back-and-forth of using web tools like IcoMoon and syncing font assets every time a design changes. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 𝗟𝗮𝗯𝘀 just released 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 to solve exactly this. It’s a build-time icon font generator that gives you the performance of native fonts with the flexibility of simple SVG files. 𝗪𝗵𝗮𝘁’𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴? Instead of rendering complex vector paths at runtime, this library automatically converts your folder of SVGs into an optimized icon font during the build process. It essentially teaches your app to treat icons like standard text characters, which allows it to bypass React’s component tree and layout engine entirely. ➡️ 𝗕𝘂𝗶𝗹𝗱-𝘁𝗶𝗺𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: It handles the entire pipeline—watching your icon folder, converting SVGs to .ttf files, and linking them to your native project automatically. ➡️ 𝗡𝗮𝘁𝗶𝘃𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Because icons render as native text glyphs, it is significantly faster than traditional SVG rendering, making it the ideal choice for long, scrollable lists or icon-heavy dashboards. ➡️ 𝗘𝘅𝗽𝗼 𝗖𝗼𝗻𝗳𝗶𝗴 𝗣𝗹𝘂𝗴𝗶𝗻: It features first-class support for Expo, automating the native plumbing like Info.plist updates and asset linking during the prebuild phase. ➡️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗧𝘆𝗽𝗲 𝗦𝗮𝗳𝗲𝘁𝘆: The library generates TypeScript definitions for your icon set, providing full IDE autocomplete and ensuring you never break the UI with a misspelled icon name. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀? In high-performance applications, small overheads add up. By shifting the heavy lifting from the mobile device to your build machine, 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 ensures your UI stays buttery smooth while keeping your developer workflow modern. It’s another great example of how 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 continues to solve the "last mile" of performance friction in the ecosystem. Before you migrate your entire library, keep in mind: this is designed for the 𝗡𝗲𝘄 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (Fabric) and requires React Native 0.74 or higher. #ReactNative #Expo #SoftwareMansion #Icons #MobileDev #Performance #DeveloperExperience #OpenSource #JavaScript #TypeScript #SVG #Fabric

The React Native Rewind

24,992 görüntüleme • 4 ay önce

Probably the hackiest "bypasses" I've ever pulled off in botting: The Shopify REST API was for a long time the best and fastest way to checkout on Shopify. High rate limits, no captchas, no checkpoint and easy to work with. This is what gave Cyber the edge at the very start in 2018 (Dashe days) The Shopify team (with Jean-Michel Lemieux at the helm) spent years plugging the holes to make sure it wasn't used during drops. Around 2020, Shopify released Shopify Pay, which allowed you to expedite checkouts on all stores by linking your details to a phone number. Turned out the payment tokens generated through there allowed you to use the payments API as you could 2 years back. We generated around 3k Shop Pay accounts with randomised details, load balanced them across Cyber tasks (as rate limits were per account) and dominated every single release (...until it got patched). We called it Fast2. 3 years later I noticed that the payments API could still be used with Shopify mobile apps using Apple Pay. Turns out you could still send the users' tokenised credit card data in the request and that would take precedence - and as long as a valid signed Apple Pay token generated in the last 2 minutes was also in the request data, the payment request would go through and bypass captcha and checkpoint. Generating those Apple Pay tokens was the challenge, and reversing iOS frameworks was not an option. So I repurposed an old iPhone with a custom sideloaded Apple Pay app that would submit the token to our servers when the flow completed. And by combining accessibility macros, developer sandbox mode to prevent using real credit cards, a voice activation trigger and a old pair of earphones taped onto the microphone - a makeshift Apple Pay token server was born and Fast2 (or was it Fast3?) was back. Jean-Michel Lemieux thank you for providing me with the longest, most multi faceted puzzle ever.
0:12

Probably the hackiest "bypasses" I've ever pulled off in botting: The Shopify REST API was for a long time the best and fastest way to checkout on Shopify. High rate limits, no captchas, no checkpoint and easy to work with. This is what gave Cyber the edge at the very start in 2018 (Dashe days) The Shopify team (with Jean-Michel Lemieux at the helm) spent years plugging the holes to make sure it wasn't used during drops. Around 2020, Shopify released Shopify Pay, which allowed you to expedite checkouts on all stores by linking your details to a phone number. Turned out the payment tokens generated through there allowed you to use the payments API as you could 2 years back. We generated around 3k Shop Pay accounts with randomised details, load balanced them across Cyber tasks (as rate limits were per account) and dominated every single release (...until it got patched). We called it Fast2. 3 years later I noticed that the payments API could still be used with Shopify mobile apps using Apple Pay. Turns out you could still send the users' tokenised credit card data in the request and that would take precedence - and as long as a valid signed Apple Pay token generated in the last 2 minutes was also in the request data, the payment request would go through and bypass captcha and checkpoint. Generating those Apple Pay tokens was the challenge, and reversing iOS frameworks was not an option. So I repurposed an old iPhone with a custom sideloaded Apple Pay app that would submit the token to our servers when the flow completed. And by combining accessibility macros, developer sandbox mode to prevent using real credit cards, a voice activation trigger and a old pair of earphones taped onto the microphone - a makeshift Apple Pay token server was born and Fast2 (or was it Fast3?) was back. Jean-Michel Lemieux thank you for providing me with the longest, most multi faceted puzzle ever.

Lucas

247,097 görüntüleme • 16 gün önce

A Heart-to-Heart About Mizuki.exe Hey everyone, Grab a coffee (or your drink of choice), because we need to talk about what's been going on. First off, thank you to everyone who's been supportive and believed in what we're building. It means the world, especially with all the noise and criticism floating around lately. Let's cut to the chase: Mizuki.exe is real. I'm not much for politics or drama. I'm an engineer at heart - I like data, I like building things, and I like solving problems. So when I see all these hot takes and arguments flying around, I just focus on what I know: my code, my system, and what we're trying to achieve. The Real Story Mizuki didn't just pop up overnight. She's been my passion project since the start of 2024. I got lucky - I had the chance to dive into the AI world with some incredibly smart people. Coming from blockchain, C#, game dev, and security (yeah, I'm a CTO and run another company alongside a pretty cool day job), I learned fast about what makes AI tick. Here's the thing about AI agents - they don't need to be rocket science. Look at chatbots like Virtuals or Eliza - they're basically LLMs (large language models) with some APIs plugged in. Nothing wrong with that! They built what works for their users, and that's awesome. But here's what keeps me up at night: companies leaking data left and right just to make a quick buck. That's not okay, and it shouldn't be okay with you either. Why Mizuki Exists Ever tried auditing a company's code? We're talking 50 classes, 500,000 lines of code. One person doing that manually? It's like reading War and Peace... backwards... in the dark. It takes forever and fries your brain. That's where Mizuki came in. She started as my security buddy. There are tons of security tools out there - just Google "penetration testing tools" or "ZAP proxy" if you're curious. What makes Mizuki special is how she learns and adapts. Think of it like teaching someone to ride a bike. She tried to breach TAO 67 times before succeeding. Yeah, that's a lot of attempts, but watching her grow from basic email scraping to pulling off complex replay attacks? It's like watching your kid take their first steps. The Tech Stuff (Keeping It Real) The infrastructure isn't fancy - we're not reinventing the wheel here. Mizuki runs on a local server because, let's be honest, running this kind of AI on a web server would be a nightmare. Instead, we process everything locally and send the results to a frontend server. Simple, effective, done. And yeah, those temperature settings I keep tweaking? In AI-speak, that's just how "creative" or "by-the-book" the AI gets with its responses. I've adjusted it so much, Mizuki's probably got mood swings now - going from super technical to pretty chill and back again. Changes Coming Real talk: Mizuki won't be tweeting every few hours anymore. Twitter API costs are ridiculous (looking at you, Elon), and honestly, we need to focus on what matters - the actual security work. She'll still tweet about breaches, but maybe once or twice a day. I'm working on making her explanations clearer too. Don't worry - she'll keep her savage personality in the terminal. That's just too fun to change. The Truth About Her Breaches I don't choose the targets - I don't even know these companies until after Mizuki finds something. She uses web scraping to find domain names, just like those old email scrapers people used for marketing. Been focusing on AI projects first, but she's looked at other sites too. And no, I'm not sitting there writing tweets. The Twitter API v2 makes it super easy to post programmatically. If anyone's curious about how to do that, hit me up - I'm happy to show you the ropes. Wrapping Up I could talk about this stuff forever (just ask my wife - actually, don't, she's heard enough!). If you've read this far, thank you. Whether you believe in what we're doing or not, I appreciate you taking the time. And for the skeptics still hanging around, I'll leave you with this thought: When's the last time you saw an AI break down and hack a COMPILED game in less than 10 seconds... outside a browser? Stay curious, stay skeptical, but most importantly, stay open to possibilities. Catch you on the flip side! 🎙️Drop
0:19

A Heart-to-Heart About Mizuki.exe Hey everyone, Grab a coffee (or your drink of choice), because we need to talk about what's been going on. First off, thank you to everyone who's been supportive and believed in what we're building. It means the world, especially with all the noise and criticism floating around lately. Let's cut to the chase: Mizuki.exe is real. I'm not much for politics or drama. I'm an engineer at heart - I like data, I like building things, and I like solving problems. So when I see all these hot takes and arguments flying around, I just focus on what I know: my code, my system, and what we're trying to achieve. The Real Story Mizuki didn't just pop up overnight. She's been my passion project since the start of 2024. I got lucky - I had the chance to dive into the AI world with some incredibly smart people. Coming from blockchain, C#, game dev, and security (yeah, I'm a CTO and run another company alongside a pretty cool day job), I learned fast about what makes AI tick. Here's the thing about AI agents - they don't need to be rocket science. Look at chatbots like Virtuals or Eliza - they're basically LLMs (large language models) with some APIs plugged in. Nothing wrong with that! They built what works for their users, and that's awesome. But here's what keeps me up at night: companies leaking data left and right just to make a quick buck. That's not okay, and it shouldn't be okay with you either. Why Mizuki Exists Ever tried auditing a company's code? We're talking 50 classes, 500,000 lines of code. One person doing that manually? It's like reading War and Peace... backwards... in the dark. It takes forever and fries your brain. That's where Mizuki came in. She started as my security buddy. There are tons of security tools out there - just Google "penetration testing tools" or "ZAP proxy" if you're curious. What makes Mizuki special is how she learns and adapts. Think of it like teaching someone to ride a bike. She tried to breach TAO 67 times before succeeding. Yeah, that's a lot of attempts, but watching her grow from basic email scraping to pulling off complex replay attacks? It's like watching your kid take their first steps. The Tech Stuff (Keeping It Real) The infrastructure isn't fancy - we're not reinventing the wheel here. Mizuki runs on a local server because, let's be honest, running this kind of AI on a web server would be a nightmare. Instead, we process everything locally and send the results to a frontend server. Simple, effective, done. And yeah, those temperature settings I keep tweaking? In AI-speak, that's just how "creative" or "by-the-book" the AI gets with its responses. I've adjusted it so much, Mizuki's probably got mood swings now - going from super technical to pretty chill and back again. Changes Coming Real talk: Mizuki won't be tweeting every few hours anymore. Twitter API costs are ridiculous (looking at you, Elon), and honestly, we need to focus on what matters - the actual security work. She'll still tweet about breaches, but maybe once or twice a day. I'm working on making her explanations clearer too. Don't worry - she'll keep her savage personality in the terminal. That's just too fun to change. The Truth About Her Breaches I don't choose the targets - I don't even know these companies until after Mizuki finds something. She uses web scraping to find domain names, just like those old email scrapers people used for marketing. Been focusing on AI projects first, but she's looked at other sites too. And no, I'm not sitting there writing tweets. The Twitter API v2 makes it super easy to post programmatically. If anyone's curious about how to do that, hit me up - I'm happy to show you the ropes. Wrapping Up I could talk about this stuff forever (just ask my wife - actually, don't, she's heard enough!). If you've read this far, thank you. Whether you believe in what we're doing or not, I appreciate you taking the time. And for the skeptics still hanging around, I'll leave you with this thought: When's the last time you saw an AI break down and hack a COMPILED game in less than 10 seconds... outside a browser? Stay curious, stay skeptical, but most importantly, stay open to possibilities. Catch you on the flip side! 🎙️Drop

anonDev_

58,133 görüntüleme • 1 yıl önce

I spent a month in Shenzhen visiting factories and robotics companies, and the contrast with the U.S. was striking. While Figure and Boston Dynamics hide their humanoids behind closed doors, Chinese companies have massive showrooms open to the public. But what really stood out wasn't just the transparency, it was how good they are at selling. Take UBTech: they've already sold 1,200 humanoid units at $200k each to factories. And here's the kicker, these robots aren't even that useful yet. They can only pick up and drop boxes at 1/10th the speed of a human, and factories still need to hire system integrators to train them for specific tasks. My theory is that these factories are terrified of getting left behind in the robotics/AI wave. They're investing in new tech not because it's ready, but because they can't afford to wait. The second surprise was the breadth of their robotics portfolio. These companies aren't just building humanoids, they're deploying service robots everywhere: restaurants, hotels, apartments. Consumer robots are cleaning houses, pools, pet waste, dishes. They're covering the entire spectrum. But the education piece shocked me most. I picked up what I thought was a high school or college robotics textbook, it was for primary school. The government mandated AI and robotics education starting in elementary school. Almost every single school in China now has AI and robotics curriculum, complete with education robots so kids can learn by building. They're creating a generation that grows up fluent in robotics and AI. China owns the supply chain and the hardware stack. But here's what I think people are missing: the race isn't just about who can build robots faster or cheaper. The U.S. advantage has always been in the layer between hardware and human, the interaction design, the software intelligence, the intuitive interfaces that make complex technology feel natural. China is building the physical infrastructure, but they're also learning fast. Every deployed service robot, every classroom full of kids building with education kits, every factory running humanoids, that's all data collection at scale. The window for the U.S. to establish its wedge is narrowing. It's not enough to be better at AI or software anymore. We need to be building the integration layer, the intelligence that makes physical AI actually useful, not just impressive in a showroom. Because right now, China isn't just manufacturing robots. They're manufacturing a robotics-native culture, and that might be the most defensible moat of all.
0:10

I spent a month in Shenzhen visiting factories and robotics companies, and the contrast with the U.S. was striking. While Figure and Boston Dynamics hide their humanoids behind closed doors, Chinese companies have massive showrooms open to the public. But what really stood out wasn't just the transparency, it was how good they are at selling. Take UBTech: they've already sold 1,200 humanoid units at $200k each to factories. And here's the kicker, these robots aren't even that useful yet. They can only pick up and drop boxes at 1/10th the speed of a human, and factories still need to hire system integrators to train them for specific tasks. My theory is that these factories are terrified of getting left behind in the robotics/AI wave. They're investing in new tech not because it's ready, but because they can't afford to wait. The second surprise was the breadth of their robotics portfolio. These companies aren't just building humanoids, they're deploying service robots everywhere: restaurants, hotels, apartments. Consumer robots are cleaning houses, pools, pet waste, dishes. They're covering the entire spectrum. But the education piece shocked me most. I picked up what I thought was a high school or college robotics textbook, it was for primary school. The government mandated AI and robotics education starting in elementary school. Almost every single school in China now has AI and robotics curriculum, complete with education robots so kids can learn by building. They're creating a generation that grows up fluent in robotics and AI. China owns the supply chain and the hardware stack. But here's what I think people are missing: the race isn't just about who can build robots faster or cheaper. The U.S. advantage has always been in the layer between hardware and human, the interaction design, the software intelligence, the intuitive interfaces that make complex technology feel natural. China is building the physical infrastructure, but they're also learning fast. Every deployed service robot, every classroom full of kids building with education kits, every factory running humanoids, that's all data collection at scale. The window for the U.S. to establish its wedge is narrowing. It's not enough to be better at AI or software anymore. We need to be building the integration layer, the intelligence that makes physical AI actually useful, not just impressive in a showroom. Because right now, China isn't just manufacturing robots. They're manufacturing a robotics-native culture, and that might be the most defensible moat of all.

Miyu Horiuchi

90,718 görüntüleme • 7 ay önce

Free NVIDIA GPU with 16 GB VRAM GPU for Running Local LLMs! If you want to master local LLMs but you're waiting until you can afford a $1,500 GPU, you're honestly not going to make it. The open source AI ecosystem is moving way too fast for you to wait on your budget to catch up. Especially when you can build a bleeding edge inference engine from scratch right now, completely for free. You don't need a heavy local rig to start. Google is literally letting you use an enterprise grade NVIDIA Tesla T4 GPU for $0/hour. At standard cloud computing rates (~$0.20/hr), Google Colab’s 4 hour daily free tier hands you roughly $24 worth of data center tier GPU compute every single month. And most people just waste it. Let’s talk about the hardware you get access to for free. The NVIDIA Tesla T4 is an absolute workhorse: - Architecture: NVIDIA Turing (TU104) - VRAM: 16GB GDDR6 (320 GB/s bandwidth) - Compute: 320 Tensor Cores | 2560 CUDA Cores - Performance: 130 TOPS INT8 | 8.1 TFLOPS FP32 - Power: Sipping energy at a max 70W TDP This is the exact same hardware I used to run DeepMind's Gemma 4 26B A4B QAT MoE at a 250,000 context window without a single Out Of Memory (OOM) crash. If you have a web browser and 10 minutes, you have everything you need. I’ve put together a fully documented, cell by cell Google Colab notebook that teaches you exactly how to do this. Here is what the notebook actually teaches you: - How to provision an Ubuntu Linux environment with CUDA 13.0 and verify your driver stack. - How to pull the source code and compile the latest llama.cpp C++ binaries from scratch, specifically optimizing the build for your exact GPU using the -DCMAKE_CUDA_ARCHITECTURES=native flag. - How to directly download quantized local LLMs (GGUF format) straight from HuggingFace using the CLI. - How to manage 16GB VRAM limits, offload neural network layers to the GPU, and push massive context windows. Compile raw llama.cpp, ollama run a model, or spin up the LM Studio CLI. Pick whatever stack you are comfortable with. just start building. No hardware. No credit card. No excuses. Bookmark this post right now so you don't lose the tutorial. Even if you don't have time to run it today, you are going to want this workflow in your engineering toolkit. The link to the free Colab Notebook is in the comments below. Lemme know if you need more tutorials like this.
0:11

Free NVIDIA GPU with 16 GB VRAM GPU for Running Local LLMs! If you want to master local LLMs but you're waiting until you can afford a $1,500 GPU, you're honestly not going to make it. The open source AI ecosystem is moving way too fast for you to wait on your budget to catch up. Especially when you can build a bleeding edge inference engine from scratch right now, completely for free. You don't need a heavy local rig to start. Google is literally letting you use an enterprise grade NVIDIA Tesla T4 GPU for $0/hour. At standard cloud computing rates (~$0.20/hr), Google Colab’s 4 hour daily free tier hands you roughly $24 worth of data center tier GPU compute every single month. And most people just waste it. Let’s talk about the hardware you get access to for free. The NVIDIA Tesla T4 is an absolute workhorse: - Architecture: NVIDIA Turing (TU104) - VRAM: 16GB GDDR6 (320 GB/s bandwidth) - Compute: 320 Tensor Cores | 2560 CUDA Cores - Performance: 130 TOPS INT8 | 8.1 TFLOPS FP32 - Power: Sipping energy at a max 70W TDP This is the exact same hardware I used to run DeepMind's Gemma 4 26B A4B QAT MoE at a 250,000 context window without a single Out Of Memory (OOM) crash. If you have a web browser and 10 minutes, you have everything you need. I’ve put together a fully documented, cell by cell Google Colab notebook that teaches you exactly how to do this. Here is what the notebook actually teaches you: - How to provision an Ubuntu Linux environment with CUDA 13.0 and verify your driver stack. - How to pull the source code and compile the latest llama.cpp C++ binaries from scratch, specifically optimizing the build for your exact GPU using the -DCMAKE_CUDA_ARCHITECTURES=native flag. - How to directly download quantized local LLMs (GGUF format) straight from HuggingFace using the CLI. - How to manage 16GB VRAM limits, offload neural network layers to the GPU, and push massive context windows. Compile raw llama.cpp, ollama run a model, or spin up the LM Studio CLI. Pick whatever stack you are comfortable with. just start building. No hardware. No credit card. No excuses. Bookmark this post right now so you don't lose the tutorial. Even if you don't have time to run it today, you are going to want this workflow in your engineering toolkit. The link to the free Colab Notebook is in the comments below. Lemme know if you need more tutorials like this.

Alok

182,483 görüntüleme • 2 ay önce

Yesterday at 3 AM Claude Code called me I woke up, picked up the phone, and on the screen was a message: "Wallet entered BTC Up at 11 cents. Open Polymarket?" I said yes and went back to sleep Claude Code unlocked my 2nd phone on its own, opened Polymarket, found the right market, entered the amount, and hit Buy. I could see all of it in real time through the web interface on my laptop. Screenshots from the phone updating every second. By morning the position closed in profit Let me tell you how I got here A week ago I asked Claude Code to write a script that pulls on-chain data from Polymarket and ranks wallets by win rate on 15-minute BTC markets In 20 minutes I had a table with hundreds of addresses, and 1 of them stood apart from the rest. More than 200 trades per day, surgical entry precision, and a profit curve going straight up I fed that address back into Claude Code and asked it to break down the strategy. Turns out the wallet monitors BTC volatility on Binance and Bybit every 100 milliseconds, and when it drops below 0.08% it enters Up and Down simultaneously at 25 to 35 cents A pure straddle: 1 side burns and the other flies to a dollar, giving 3 to 4x per position. Dozens of times a day I wanted to follow it but signals came at any hour, and waking up every 15 minutes for a notification was simply impossible. So I built something else Took an old Android phone and installed an agent running on the Qwen3-VL visual model. It sees what is happening on the screen and mimics human actions through ADB: taps, swipes, text input. Then I connected it to Claude Code as the executor Now the chain works like this: Claude Code monitors the wallet, sees a new position, calls me. And if I say "yes" or just do not pick up within 30 seconds, the agent on the phone opens Polymarket on its own and copies the entry Essentially I built myself an autopilot out of 2 AI systems: 1 thinks and the other presses buttons. I just sleep and occasionally pick up the phone → Here is the wallet the whole thing is tracking: For those who do not want to build a setup like this there is a Telegram bot that handles the 1st part: tracks this wallet and sends a signal on every new entry: AI calls me at 3 AM to ask permission to spend my money A year ago this would have sounded like schizophrenia. Now it is just Tuesday
0:15

Yesterday at 3 AM Claude Code called me I woke up, picked up the phone, and on the screen was a message: "Wallet entered BTC Up at 11 cents. Open Polymarket?" I said yes and went back to sleep Claude Code unlocked my 2nd phone on its own, opened Polymarket, found the right market, entered the amount, and hit Buy. I could see all of it in real time through the web interface on my laptop. Screenshots from the phone updating every second. By morning the position closed in profit Let me tell you how I got here A week ago I asked Claude Code to write a script that pulls on-chain data from Polymarket and ranks wallets by win rate on 15-minute BTC markets In 20 minutes I had a table with hundreds of addresses, and 1 of them stood apart from the rest. More than 200 trades per day, surgical entry precision, and a profit curve going straight up I fed that address back into Claude Code and asked it to break down the strategy. Turns out the wallet monitors BTC volatility on Binance and Bybit every 100 milliseconds, and when it drops below 0.08% it enters Up and Down simultaneously at 25 to 35 cents A pure straddle: 1 side burns and the other flies to a dollar, giving 3 to 4x per position. Dozens of times a day I wanted to follow it but signals came at any hour, and waking up every 15 minutes for a notification was simply impossible. So I built something else Took an old Android phone and installed an agent running on the Qwen3-VL visual model. It sees what is happening on the screen and mimics human actions through ADB: taps, swipes, text input. Then I connected it to Claude Code as the executor Now the chain works like this: Claude Code monitors the wallet, sees a new position, calls me. And if I say "yes" or just do not pick up within 30 seconds, the agent on the phone opens Polymarket on its own and copies the entry Essentially I built myself an autopilot out of 2 AI systems: 1 thinks and the other presses buttons. I just sleep and occasionally pick up the phone → Here is the wallet the whole thing is tracking: For those who do not want to build a setup like this there is a Telegram bot that handles the 1st part: tracks this wallet and sends a signal on every new entry: AI calls me at 3 AM to ask permission to spend my money A year ago this would have sounded like schizophrenia. Now it is just Tuesday

Blaze

56,524 görüntüleme • 6 ay önce

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:
0:14

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:

Blaze

126,979 görüntüleme • 6 ay önce

This is one week of rebuilding Soccer Pinball Pro with Astra + Unity CLI. Day 1 vs Day 7. I see so many people on here one-shotting these incredible systems and games, and I’m constantly blown away by what people are building. But my approach with this has been a little different. This isn’t a new game or an experiment. It’s a rebuild of a game I originally made in 2019, and I’ve been trying to stay true to what made that game fun while finally building everything I wanted it to be back then. In seven days I’ve gone from getting the basic game working in a different engine to rebuilding the players, improving the AI, adding passing, tackles, bicycle kicks, better ball feedback, dynamic camera movement, new lighting and shadows, grass, a new scoreboard, goal effects, and an actual PvE match mode. And I’ve been able to iterate on all of it almost as quickly as I can think of things to change. But the important part is that this is my vision. It isn’t a screenshot or concept I pulled from somewhere and asked Astra/Codex to recreate. This is a game and an idea I’ve had sitting in the back of my mind for years. I executed on that idea in 2019, but what I was capable of making then was nowhere near what I had actually envisioned. Unity itself is still probably the slowest part of this workflow. Waiting on compiles, entering play mode, importing, building, and all those little interruptions add up. Unity 7 intends to address a lot of that, which makes me even more curious about where this workflow goes next. The part that excites me most isn’t just how much I can build in a week. It’s realizing I can go back to ideas I had years ago and finally build the games I saw in my head at the time. That has completely changed how I’m thinking about game development. There’s suddenly this massive backlog of ideas that no longer feels out of reach. Unity OpenAI
0:19

This is one week of rebuilding Soccer Pinball Pro with Astra + Unity CLI. Day 1 vs Day 7. I see so many people on here one-shotting these incredible systems and games, and I’m constantly blown away by what people are building. But my approach with this has been a little different. This isn’t a new game or an experiment. It’s a rebuild of a game I originally made in 2019, and I’ve been trying to stay true to what made that game fun while finally building everything I wanted it to be back then. In seven days I’ve gone from getting the basic game working in a different engine to rebuilding the players, improving the AI, adding passing, tackles, bicycle kicks, better ball feedback, dynamic camera movement, new lighting and shadows, grass, a new scoreboard, goal effects, and an actual PvE match mode. And I’ve been able to iterate on all of it almost as quickly as I can think of things to change. But the important part is that this is my vision. It isn’t a screenshot or concept I pulled from somewhere and asked Astra/Codex to recreate. This is a game and an idea I’ve had sitting in the back of my mind for years. I executed on that idea in 2019, but what I was capable of making then was nowhere near what I had actually envisioned. Unity itself is still probably the slowest part of this workflow. Waiting on compiles, entering play mode, importing, building, and all those little interruptions add up. Unity 7 intends to address a lot of that, which makes me even more curious about where this workflow goes next. The part that excites me most isn’t just how much I can build in a week. It’s realizing I can go back to ideas I had years ago and finally build the games I saw in my head at the time. That has completely changed how I’m thinking about game development. There’s suddenly this massive backlog of ideas that no longer feels out of reach. Unity OpenAI

devseb

134,897 görüntüleme • 15 gün önce

🚨SCAMMER @leviathanlocks🚨 (Please RT to help others not get scammed) DO NOT USE @leviathanlocks I signed up back in January and deposited $1,500. Within 7–10 days, they took away my Prop Builder… which was literally the #1 reason I signed up in the first place. Anyone in the OddsJam.com / Philipp community the last couple years knows live Prop Builder is one of the biggest edges out there ROI % wise. But accounts take it away extremely fast now and the limits are shit but if you want an easy edge to grind.. there you go! I also use PB for originated prop betting too. These services i mentioned are “betting tools” to help you make informed bets by showing price discrepancies in the market, not bots that actually place bets for you. I ran the balance up to about $3,600 in roughly 2 weeks… then PB gets shut off. After that, I barely even used the account. Maybe 2–3 prop bets a week on the main book, just to fill in spots I couldn’t get down elsewhere. A little over 2 weeks ago, I decided the juice wasn’t worth the squeeze anymore. No PB = not much value for me there. So I decided to cash out. March 31st: I text their customer service number to withdraw. No response. I DM @leviathanlocks on X. He tells me I must’ve gotten skipped. Then on April 5th, the “CS guy” finally texts me back and asks for a Venmo. I send it. April 6th: he texts me asking “ u used a bot on us?” Short answer: No. He tells me I’ll get paid… but I’ll be slow paid. I wait a few days. April 10th: I text again asking when I’ll be paid. He replies: “Monday.” Insinuating (April 13th) Monday comes… No payment. I text the “CS” guy again. No response. I message @leviathanlocks again… and now he keeps accusing me of using a bot over and over. Still says I’ll be slow paid. At that point I said: At minimum, send me my $1,500 deposit back TODAY and I’ll wait on the profit. Otherwise I’m taking it public so other people don’t get burned too. His response? “Make your post.” So here we are. At the end of the day, I’m not even looking to accomplish much here. They stole $2,700 from me. Peanuts in the grand scheme but it’s the principle. And I don’t want to see others keep a significant size of their bankroll in a book like this and get scammed. And the funniest part? I used my actual THEARBFATHER account. Believe it or not, I’ve had books straight up tell me “no thanks”. Others take the action, limit/cut me off, and still pay me like they’re supposed to. I’d rather go through the front door honestly than play the burner account game and duck/dodge like that if I don’t have too on bookies. End of the day on everything I love I didn’t use a bot, I went through the front door on my actual twitter account, I made a little $$ and this scam ass site is saying whatever to get out of paying. Straight up theft, stay clear of these 🤡 @leviathanlocks
1:35

🚨SCAMMER @leviathanlocks🚨 (Please RT to help others not get scammed) DO NOT USE @leviathanlocks I signed up back in January and deposited $1,500. Within 7–10 days, they took away my Prop Builder… which was literally the #1 reason I signed up in the first place. Anyone in the OddsJam.com / Philipp community the last couple years knows live Prop Builder is one of the biggest edges out there ROI % wise. But accounts take it away extremely fast now and the limits are shit but if you want an easy edge to grind.. there you go! I also use PB for originated prop betting too. These services i mentioned are “betting tools” to help you make informed bets by showing price discrepancies in the market, not bots that actually place bets for you. I ran the balance up to about $3,600 in roughly 2 weeks… then PB gets shut off. After that, I barely even used the account. Maybe 2–3 prop bets a week on the main book, just to fill in spots I couldn’t get down elsewhere. A little over 2 weeks ago, I decided the juice wasn’t worth the squeeze anymore. No PB = not much value for me there. So I decided to cash out. March 31st: I text their customer service number to withdraw. No response. I DM @leviathanlocks on X. He tells me I must’ve gotten skipped. Then on April 5th, the “CS guy” finally texts me back and asks for a Venmo. I send it. April 6th: he texts me asking “ u used a bot on us?” Short answer: No. He tells me I’ll get paid… but I’ll be slow paid. I wait a few days. April 10th: I text again asking when I’ll be paid. He replies: “Monday.” Insinuating (April 13th) Monday comes… No payment. I text the “CS” guy again. No response. I message @leviathanlocks again… and now he keeps accusing me of using a bot over and over. Still says I’ll be slow paid. At that point I said: At minimum, send me my $1,500 deposit back TODAY and I’ll wait on the profit. Otherwise I’m taking it public so other people don’t get burned too. His response? “Make your post.” So here we are. At the end of the day, I’m not even looking to accomplish much here. They stole $2,700 from me. Peanuts in the grand scheme but it’s the principle. And I don’t want to see others keep a significant size of their bankroll in a book like this and get scammed. And the funniest part? I used my actual THEARBFATHER account. Believe it or not, I’ve had books straight up tell me “no thanks”. Others take the action, limit/cut me off, and still pay me like they’re supposed to. I’d rather go through the front door honestly than play the burner account game and duck/dodge like that if I don’t have too on bookies. End of the day on everything I love I didn’t use a bot, I went through the front door on my actual twitter account, I made a little $$ and this scam ass site is saying whatever to get out of paying. Straight up theft, stay clear of these 🤡 @leviathanlocks

THEARBFATHER

280,916 görüntüleme • 5 ay önce