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Users state the goal. xBubble handles the building path. With Bubble Code, xBubble helps users create different kinds of Code AI Agents & AI roducts. The key is not just generating a prototype. Bubble Code is built to turn user goals into ready-to-use products with real interfaces, logic, integrations,... show more

DAPPOS

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97,785 görüntüleme • 3 ay önce •via X (Twitter)

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Users define the experience. Bubble Code brings the AI host live. Through xBubble, you can build and deploy an interactive avatar livestream room with real-time video, audience chat, live responses, and session controls. Not a prerecorded digital human, a ready-to-use AI livestream product built for real interaction.

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Teams are cooking some code. 🧑‍💻 Smart Contracts, APIs, frontend, AI agents. It is possible to develop products on chain under 24 hours. Complete products. Especially with the age of AI, everything is faster, and anyone with some prompting skills and an idea can start building. The night will be long. Time to build more!

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Everyone should learn to code with AI! At AI Fund, everyone - not just engineers - can vibe code or use AI assistance to code. This has been great for our creativity and productivity. I hope more teams will empower everyone to build with AI. Please watch the video for details.

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😎Just created My website using DAPPOS xBubble Ai 💥Update on xBubble 🆕Code option went live recently 🤔Other AI agents give u code to build website as per prompt 🤷Writing the code is no longer the hard part, Launching it is 🫠But getting that app live need u to hosting, deploying, API integration etc.. 💡But xBubble changes it ✅Just give prompt, it will deploy & give u ready website ❌No developer required 👇Steps 🔗 ✅Sign up with wallet ✅U need credits to use AI ✅Describe what kind of website u want to build ✅Select "code" from drop down ✅Sent ✅It will take sometime & give a ready website 😁It created my website in just 21min 😃Team gave me link to claim free credits for our community members 🔗 ✅Enter same wallet & ur x id ✅Complete quick quiz ✅Claim free 500 credits ✅Go back to xBubble ✅Start using it 🤏Each link has limited credit, claim before it's gone 🔗 😉2nd link for more credits 💥Done 📸Post ur xBubble work screenshots below 💙Like 🔁RT

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CryptoTelugu

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this is insane… I JUST built a full Spotify clone with nothing but text prompts. no code. no design. Emergent AI did everything.. UI, logic, backend APIs, database setup, and full server deployment. this should not be possible: 👇

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Today we’re launching Decawork (YC S26) backed by Y Combinator : one place for IT to deploy, govern, and maintain the internal AI agents running across a company. Every team is building AI tools/agents now. They go live with real access, no standard way to ship, nobody watching. With Decawork, every agent - built in Claude Code, Codex, or anywhere else - ships with its own identity and scoped credentials. IT signs off before it's live, sensitive actions wait for approval, and every run is watched from first to last. I built AI at NVIDIA, deployed at OpenAI and Meta. Aman (aman) built Barclays' AI compliance platform used by internal teams, then shipped agents to 100K+ monthly users. We lived this and quit to solve it. Internal AI agents/tools piling up at your company? Chat with us founders[at]decawork[dot]ai or

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sarthak 🇮🇳

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The best way to learn about AI is to build an AI app yourself. With tools like Bubble and OpenAI, you can create apps like an AI chatbot without writing code 🤯 Stay ahead on AI and start learning today:

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Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon Aish and Kiriti Badam have built 50+ enterprise AI products across companies like OpenAI, Google, Amazon, and Databricks. Based on these experiences, they’ve developed a small set of best practices for building and scaling successful AI products. Our goal with this conversation is to save you and your team a lot of pain and suffering while building your AI products. We discuss: 🔸 Two key ways AI products differ from traditional software 🔸 Common patterns and anti-patterns when building successful AI products 🔸 Their framework for iteratively building AI products 🔸 Why evals aren’t a cure-all 🔸 Why obsessing about customer trust and reliability is an underrated driver of successful AI products 🔸 The skills that matter most for builders in the AI era Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Merge — The fastest way to ship 220+ integrations: 🏆 Strella — The AI-powered customer research platform: 🏆 Brex — The banking solution for startups:

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Claude Code cracked something open for us Every 🧱. Now I ship to codebases I barely know, every feature we ship makes the next one easier, and non-technical members of the team use the terminal. I’m genuinely grateful. So I brought its creators, Cat Wu (cat) and Boris Cherny (Boris Cherny) from Anthropic, on AI & I to say thank you—and to talk about everything they’ve learned from building Claude Code. We get into: • The workflows Anthropic’s smartest engineers use to push Claude Code to its limits. Why they pit subagents against each other to get cleaner results, how they turn past code into leverage, and the slash commands and MCPs they rely on most. • The product lessons behind one of the most loved AI agents in the world. How the team balances simplicity and power—building a tool that anyone can use, but that experts can bend to their will—and their philosophy of “unshipping,” or cutting back whenever there’s a simpler, more intuitive path to user intent. • A peek into the future of coding with AI. The new form factors they’re experimenting with to make Claude Code more autonomous, more reliable, and more accessible to non-technical users This is a must-watch for anyone—both technical and non-technical—who wants to learn how to use Claude Code like the people who built it. Watch below! Timestamps: Introduction: 00:01:26 Claude Code’s origin story: 00:02:25 How Anthropic dogfoods Claude Code: 00:07:03 Boris and Cat’s favorite slash commands: 00:14:06 How Boris uses Claude Code to plan feature development: 00:15:49 Everything Anthropic has learned about using sub-agents well: 00:21:53 Use Claude Code to turn past code into leverage: 00:26:16 The product decisions for building an agent that’s simple and powerful: 00:33:14 Making Claude Code accessible to the non-technical user: 00:36:38 The next form factor for coding with AI: 00:45:12

Dan Shipper 📧

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We’re on a mission to revolutionize AI-powered products with limitless potential By seamlessly answering questions & executing tasks, the future of AI is within reach. Our aims is to empower users with actionable intelligence, including the tokenization of AI Agents! 🧠🤖

We’re on a mission to revolutionize AI-powered products with limitless potential By seamlessly answering questions & executing tasks, the future of AI is within reach. Our aims is to empower users with actionable intelligence, including the tokenization of AI Agents! 🧠🤖

PAAL AI 🧠🤖

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Excited to be featured on the latest episode of Design Better Portfolio Club with Aarron Walter and Elijah Woolery! 🧡 We dive into building AI-native products with Claude Code, the shift happening in product development and the best practices for creating with AI. Check it out!

Excited to be featured on the latest episode of Design Better Portfolio Club with Aarron Walter and Elijah Woolery! 🧡 We dive into building AI-native products with Claude Code, the shift happening in product development and the best practices for creating with AI. Check it out!

Joey Primiani

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prompting tip: How to write hybrid english & code prompts while building custom GPTs -Turn on code interpreter -"write code to ..." -Regenerate a few times until you get one you like -Copy paste it back into your prompt -tweak it to improve Now your ai can write consistent code Plus, you can add & combine with all sorts of english rules on top. Essentially adding english code logic "If the user asks for ..., then run this code" "If the user needs help with ..., use this code snippet and ask the user for all required information" Guess what thats a working if statement in english! if userAsksFor { // run this code } Prompts are code! English is a coding language Prompt-gramming is abstract coding

prompting tip: How to write hybrid english & code prompts while building custom GPTs -Turn on code interpreter -"write code to ..." -Regenerate a few times until you get one you like -Copy paste it back into your prompt -tweak it to improve Now your ai can write consistent code Plus, you can add & combine with all sorts of english rules on top. Essentially adding english code logic "If the user asks for ..., then run this code" "If the user needs help with ..., use this code snippet and ask the user for all required information" Guess what thats a working if statement in english! if userAsksFor { // run this code } Prompts are code! English is a coding language Prompt-gramming is abstract coding

Nick Dobos

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nader dabit

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