Harry Tech (@Harry_TechAi) header
Harry Tech (@Harry_TechAi) profile picture

➤ Exploring AI & New Tech ➤ Sharing Useful Content ➤ Open for Paid Collabs & Partnerships ➤ 📧[email protected]

New York, USA 🇺🇸
Joined August 2013
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🚀 Meet Your AI Dream Team! 12 AI Tools to Supercharge Your Workflow! 🤯 🔹 ChatGPT → chatgpt.com 🔹 Perplexity → perplexity.ai 🔹 Gamma → gamma.app 🔹 Nano Banana → gemini.google.com 🔹 Kling AI → kling.ai 🔹 n8n → n8n.io 🔹 Claude Code → claude.com 🔹 Lovable → lovable.dev 🔹 Retell AI → retellai.com 🔹 Later → later.com 🔥 Work Smarter. Create Faster. Save Time! ❤️ Like | 🔁 Repost | 🔖 Bookmark Follow @harry_techai for more AI tools!
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Harry Tech retweeted
🚀 Meet Your AI Dream Team! 12 AI Tools to Supercharge Your Workflow! 🤯 🔹 ChatGPT → chatgpt.com 🔹 Perplexity → perplexity.ai 🔹 Gamma → gamma.app 🔹 Nano Banana → gemini.google.com 🔹 Kling AI → kling.ai 🔹 n8n → n8n.io 🔹 Claude Code → claude.com 🔹 Lovable → lovable.dev 🔹 Retell AI → retellai.com 🔹 Later → later.com 🔥 Work Smarter. Create Faster. Save Time! ❤️ Like | 🔁 Repost | 🔖 Bookmark Follow @harry_techai for more AI tools!
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AI teams overpay for inference twice: once for models bigger than they need, and again for idle capacity they don’t use. @useRouterPlus is the extended inference team for fast-growing AI companies. We test models and providers on your traffic and get providers to compete for your work. Make your inference better. Go to routerplus.com
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🚨 BREAKING: ChatGPT can now teach you BUILD PASSIVE INCOME from zero. For free. Here are 6 prompts to earn Money While You Sleep:
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15 AI Research Voices on X @amaarora= AI papers explained through code. @cwolferesearch= Clear, in-depth LLM research breakdowns. @sedielem =Diffusion models explained deeply. @MaartenGr= Complex AI made visual. @seb_ruder =NLP and multilingual AI insights. @Tim_Dettmers= Quantization and efficient LLMs demystified. @arankomatsuzaki= Research papers distilled into takeaways. @srush_nlp= Transformers explained with hands-on code. @ai_explorer25= New AI tools, peoples and ai commentary @rasbt= LLM research translated into practical code. @natolambert= RLHF and post-training unpacked. @eugeneyan= AI research meets real-world systems. @sh_reya= AI evaluation beyond benchmark scores. @HamelHusain= Practical, no-nonsense AI evaluation. @ch402= Neural networks decoded from within
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A model topping the leaderboard doesn't automatically make it the right choice for your product. Your prompts are different. Your users are different. Your workloads are different. Test against reality, not assumptions. That's the approach behind RouterPlus.
🤝 Paid partnership
AI teams overpay for inference twice: once for models bigger than they need, and again for idle capacity they don’t use. @useRouterPlus is the extended inference team for fast-growing AI companies. We test models and providers on your traffic and get providers to compete for your work. Make your inference better. Go to routerplus.com
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WALL STREET spends millions on quant teams. I spent $20 on Claude. Yesterday: fired. rent late. $25 left in my bank account. I opened Claude and typed: “Analyze profitable Polymarket wallets from the last 90 days and build me an edge.” Then went to sleep. Woke up to: +$4,237. While I was asleep, the agent: • scanned 10,000 wallets • filtered fake alpha from real edge • tracked sizing, timing, and conviction • found traders consistently beating the market Then it built a fully automated strategy: → monitors breaking news → maps narratives to active markets → detects mispriced odds → executes arbitrage → sizes positions dynamically Started at PM. By morning: 94 trades executed. Zero manual input. No fear. No greed. No second-guessing. Just data reacting faster than humans can. People keep asking if AI will replace jobs. Wrong question. The real question is: what happens when one person gets access to tools that used to belong only to Wall Street? You only need Claude + laptop + 1 hour/day. Giving This Free for 24 hours. To get it:
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ELEVENLABS IS F*CKED. i'm not exaggerating. GitHub just ended the paid voice AI business. 2 devs dropped VoiceStudio. 100% free. runs on YOUR machine. and in 6 months it hit 94,000 stars and #1 Repository Of The Day. look at what you get for $0: → clone a voice from ONE clean clip → dub any video in 646 languages → type "middle-aged british narrator, low pitch" → it builds the voice → full audiobooks, dictation, transcription → mac, windows, linux, android, iphone no cloud. no credits. no monthly bill. no GPU. you are paying a subscription for something a free repo does on your laptop. read that again. every creator still paying for voice AI in 2026 is getting milked. bookmark this NOW. send it to the one friend who keeps paying link in the comments 👇
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Don't date: - Nurses - Coworkers - Your best friend's ex - Someone who still talks to their ex - Someone who thrives on drama DATE:
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The RouterPlus demo is basically an eval loop: look at real traffic, choose the model, measure the cost. Same results as frntier setups, at up to 80% lower cost.
AI teams overpay for inference twice: once for models bigger than they need, and again for idle capacity they don’t use. @useRouterPlus is the extended inference team for fast-growing AI companies. We test models and providers on your traffic and get providers to compete for your work. Make your inference better. Go to routerplus.com
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Elon Musk follows a simple but powerful 5-step framework to solve complex problems: Question everything. Challenge every requirement and assumption. Remove anything unnecessary or incorrect. Delete relentlessly. Eliminate as much as possible. If you don't add back at least 10% of what you removed, you probably haven't deleted enough. Simplify and optimize. Improve what actually needs to exist. Accelerate. Make the refined process faster and more efficient. Automate. Only automate once everything else has been perfected. But here's the part most people get wrong: They jump straight to optimization and automation without questioning whether the process should exist in the first place. As Musk emphasizes, there's no point making something faster if it shouldn't have been built at all. Don't optimize a bad process. Eliminate it first. Watch the full video to see how this first-principles approach works in practice.
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A couple has paid $325 a year for the American Express Gold card for 3 years. which comes to $975, and they chose it because a coworker told them it was the best card for people who love food. They cook at home most nights, they eat out about twice a week, and they were sure the card was quietly paying them back. Then last month the husband sat down to do the family budget and counted what the card had actually given them. It was a few thousand points they had never redeemed and a monthly statement that looked exactly like every other one. He turned to his wife and said they were paying $325 a year for a piece of gold-colored metal. His college roommate, who spent 7 years on a rewards team at a major card issuer, happened to be visiting that weekend and glanced at the statement over his shoulder. He asked one question. Why is your grocery spending at Costco and Target if you have a card that pays 4 points a dollar at supermarkets? The husband said they buy everything at Costco and Target because it is cheaper, and the roommate put down his coffee. You have never enrolled in the dining credit. You have never used the Uber Cash that has been loading onto the card every month. You have never claimed the Dunkin credit, never touched the Resy credit and never redeemed a single point for anything worth more than a penny. Costco and Target do not count as supermarkets on this card, so your biggest grocery bills have been earning almost nothing. You have been paying a premium for a food card and using it like a basic one. You are not paying $325 for a card. You are paying $325 for a menu, and you have never ordered anything off it. The husband opened the Amex app for the first time in months, found the Benefits tab and saw more than $400 in credits waiting to be claimed. His roommate wrote down 10 things on the back of a receipt. Some take 30 seconds and some take 10 minutes, and every one of them was already included in the fee they had been paying for 3 years. Here is every single thing he wrote down 🧵
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🚨 BREAKING: Claude can now BUILD a YouTube channel from scratch and hit monetization in just 90 days. 100% free. Here are 7 prompts to make it happen:
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The client cuts the budget in half. Your AI team invents a cheaper quote to make it fit. Would you catch it? 👀 I tested Teamily AI @Teamily_AI with a real-world project scenario: 📌 One landing page, 3 social posts, and a project plan. 💰 Budget: $2,000 ⏳ Deadline: 10 days Four specialist AI agents collaborated in one chat through a saved Loop. 🔍 Research flagged a critical issue: the enquiry form had no submission destination. 📋 Planning used that finding to scope the work. ⚠️ Review caught a scheduling conflict between Day 8 publishing and Day 9 approval. 💻 Webpage Developer turned the plan into a live project dashboard using Teamily Website Builder. Then I changed one requirement: “The budget is now $1,000. Day 10 stays.” I reran the saved Loop. The updated brief flowed through the team without repeatedly prompting every agent. But there was a problem. The team proposed a $750 “trimmed” page. Our fixed estimate was $900. That lower price had never been approved. I challenged it. The Review agent rejected the unsupported quote and sent the correction back to the developer. The final dashboard exposed the real situation: $1,600 in core work $1,000 available $600 budget gap Instead of pretending everything could fit, the workflow made the trade-offs visible. And I took it further. Inside Open Studio, I used a comment to ask the developer to make the budget gap and available options clearer at the top of the page. The developer refined the dashboard, and I could review the before-and-after result in the same workflow. That’s the difference between generating AI outputs and coordinating AI agents around a shared project. ✅ Multiple agents collaborating in one chat ✅ Saved workflows that adapt when requirements change ✅ Review that challenges unsupported assumptions ✅ Website editing through Open Studio ✅ Clearer decisions without rebuilding everything from scratch The real value of AI isn't making every answer look perfect. It's making problems, costs, and decisions impossible to ignore. The finished dashboard was built with Teamily Website Builder. 🔗 Explore the dashboard and compare the budget options: teamily.ai/link/Wk-BaNlHnj4 🚀 Put your next project through the same test: teamily.ai/i/DQQ2VR #Ad #AI #AIAgents #AITools #WebsiteBuilder #Automation
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Stop wasting AI credits on prompts that don’t get the job done. These 16 practical tips can help you write better prompts, reduce unnecessary back-and-forth, and get more useful results from Claude. Small changes in how you prompt can make your workflow much more efficient. Save this infographic for your next AI session. #ClaudeAI #AITips #PromptEngineering #ArtificialIntelligence #AIProductivity
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🚨 Anime studios might not exist in 2026 !! I just found a FREE AI tool called Charakuru.... And it can 👉 Create 3d Models in Blender 👉 And Animate them using AI You no longer need to learn BLENDER !! People with ZERO-EXPERIENCE are just uploading an image & a prompt in Charakuru to create creative 3d VFX Videos like these 👇 1️⃣ Tripo 2.0 Converts the image into a 3d model 2️⃣ ChatGPT 6 Astra Uses Blender to animate (or) rig the 3d model.... It adjusts the camera angles & lighting to match the footage This used to be a full VFX pipeline. Now ONE person can do it 🔥 Charakuru is FREE & open-source github.com/nanocle/Charakuru Try Tripo Studio AI 👇 studio.tripo3d.ai/?utm_sourc… 🎁 Get 300 FREE credits with my Coupon Code: "7YGPR8"
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I generated $7625 overnight using an automated Claude setup. I’ve documented the exact, step-by-step process behind this timezone arbitrage strategy. What you need👇 • Claude • A Mobile • 24 hours to test it ( no cost ) How to access the guide👇 1. Comment “ SetUp ” 2. Like & RT 3. Follow @Shubhambais05 (so I can send it via DM) The system runs continuously, scanning global news across Japanese, European, Australian, and Middle Eastern markets. It identifies pricing inefficiencies situations where outcomes are already reflected overseas, but U.S. markets have yet to adjust. After 9 days of running this setup, the results have been consistent and eye opening. Most traders focus on EST. Markets don’t. While one region sleeps, another resolves events in real time. That timing gap is the opportunity. Follow @Shubhambais05 to receive the full breakdown. ( First 1500 people will get it! Like, comment, and follow quickly )
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I lost my job yesterday. Rent was due. No backup plan. Then I remembered I still had Claude. Asked it: “Analyze every top Polymarket wallet from the last 90 days and build me something” $25 → $4,237 in one night. It scanned 10,000 wallets. Cross-referenced win rates, sizing, timing. Found 7 traders whose edge wasn’t luck. Then built an autonomous agent. Not a script. Not an if-then bot. An agent that reads live news, maps it to markets, detects mispricing, and exploits arbitrage across outcomes. Sizes every position using Kelly. I deployed it at 11:47PM. Closed the laptop. Woke up to: $25 → $4,237 94 trades while I slept. No input. No hesitation. No second-guessing. That’s the game. Information asymmetry at machine speed. Wall Street pays millions for this. I pay $20/month. You only need Claude + laptop + 1 hour/day. Giving This Free for 24 hours. To get it: 1. Comment the word 'AutoPilot' 2. Like and Retweet this post 3. Follow me @Tec_with_Lui(so i can DM you)
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Ever wondered what happens after you click “Checkout”? Let me try to explain the core building blocks of an E-Commerce Architecture. Here’s a breakdown of the journey of an online order using a microservices-based architecture - where each step, from cart to shipping, is handled by an independent service. The process kicks off when a customer places an order, which is managed by the Shopping Cart microservice via a REST API. The order then flows into the Order Placement service, which records and broadcasts the order details through an event stream. Next, the Inventory service checks stock levels and interacts with the Supplier backorder system if needed. The Payment microservice integrates with third-party providers (via SOAP or REST) to process payments securely. Once payment is confirmed, the Shipping service prepares the consignment, updates order status, and notifies the Operations team for dispatch. Meanwhile, reporting tools consume order and inventory events and store them in an OLAP database for analytics and dashboards. Don’t forget to save this for later ! P.S. Preparing for a software engineering role? Check out my book, System Design and Behavioral Intelligence. It will help you: •⁠  ⁠Build strong System Design foundations and approach design problems with confidence •⁠  ⁠Develop practical frameworks to navigate complex behavioral and leadership challenges Get Your Copy anywhere internationally:  US: lnkd.in/eVy2ACxQ UK: lnkd.in/evzmHKm4 India : lnkd.in/e25PthqU
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Most people use ChatGPT at 15% of its power. They write one prompt, get one answer, and stop. The real trick: stop writing prompts yourself. Let the AI write them for you. I built a simple system where ChatGPT asks me questions, then builds the perfect prompt on its own. My results got 10x better. Here's the exact guide 👇
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