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💥 Introducing Vibe, an AI powered app builder similar to Lovable, Replit and v0. No, this isn't my SaaS announcement, this is a product that you will learn how to build in my newest FREE course! 🚀 🚀 Next.js 15 + React 19 🎨 Tailwind v4 + shadcn UI... 📡 tRPC.io 🧙‍♂️ for full-stack type safety 🔁 Inngest background jobs 🧠 Inngest agent toolkit 🔐 authentication 💳 billing 🧱 Component and app generation from AI prompts 🗂️ Live project preview with URL access 🖥️ E2B cloud sandboxes for runtime execution 🐳 Docker -based sandbox templating 🧠 AI model support (OpenAI, Anthropic, Grok) 📦 Prisma + Neon for database integration 🤖 CodeRabbit AI-powered PR reviews 🧾 Built-in credit system with usage tracking 🧪 Preview + code explorer toggleshow more

Code With Antonio

24,856 subscribers

93,079 Aufrufe • vor 1 Jahr •via X (Twitter)

Wissenschaft & Technologie Bildung Comedy

Anya Rossi• Live Now

Private livecam show

10 Kommentare

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Code With Antoniovor 1 Jahr

Watch on YouTube:

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Code With Antoniovor 1 Jahr

Watch on my platform:

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@trpcio .@theo can i submit this as late t3 clone? jk, but i definitely would've participated if i wasn't working on this!

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Josh tried codingvor 1 Jahr

@shadcn @trpcio he has done it again, incredible work man

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Code With Antoniovor 1 Jahr

@shadcn @trpcio Thank you Josh!!

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Vasek Mlejnskyvor 1 Jahr

@shadcn @trpcio Hey @YTCodeAntonio, I'm the ceo of @e2b. This is awesome tutorial! Thanks for creating this

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Code With Antoniovor 1 Jahr

@shadcn @trpcio @e2b Hi Vasek! Nice to meet you! So happy you like the tutorial, I had a great time using E2B!

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Sahajvor 1 Jahr

@shadcn @trpcio thanks for featuring tweakcn :) The video looks amazing. Will check it out for sure

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Code With Antoniovor 1 Jahr

@shadcn @trpcio 🫶

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Coding in Flowvor 1 Jahr

@shadcn @trpcio Bro are you UPS because you just delivered

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Here’s the most compelling benchmark of AI progress: A task that took 60 minutes a year ago now takes 60 seconds. In January 2024, Geoffrey Litt and I spent an hour coaxing @ChatGPTapp and Replit ⠕ to build an app live on my podcast. 12 months later, Steve Krouse and I built the same app with one prompt in less than a minute. Steve is the cofounder and CEO of Val Town, a cloud-based platform for developers to write, share, and deploy code directly in the browser. We used Townie, Val Town’s AI assistant, to build an app to keep track of time on the podcast, take notes, and generate questions for the guest. Townie generated the app even before Steve could finish describing it on the show. As we demo Townie, we get into: - Why Steve believes programming can rewire the way you think - The rise of the non-technical AI developer and what that means for the future of coding - How Townie works under the hood, including the details of the system prompt - How Steve is evolving Val Town’s strategy as AI progress continues to unfold - The power of small, dense engineering teams This is a must-watch for founders building AI-powered developer tools, and anyone interested in the future of programming. Watch below!

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15,222 Aufrufe • vor 1 Jahr

New short course: Vibe Coding 101 with Replit! Learn to build and host applications with an AI agent in this course, built in partnership with Replit ⠕ and taught by its President Michele Catasta and Head of Developer Relations . Coding agents are changing how we write code. "Vibe coding" refers to a growing practice where you might barely look at the generated code, and instead focus on the architecture and features of your application. However, contrary to popular belief, effectively coding this way isn't done by just prompting, accepting all recommendations, and hoping for the best. It requires structuring your work, refining your prompts, and having a systematic process that lead to a more efficient and effective workflow. I code frequently using LLMs, and asking an LLM to do everything in one shot usually does not work. I'll typically take a problem, partition it into manageable modules, spend time creating prompts to specify each module, and use the model to produce the code one module at a time, and test/debug each module before moving on. A process like this is making me and many other developers faster and more efficient. In this video-only course, you’ll learn how to use Replit’s cloud environment--with an integrated code editor, package manager, and deployment tools--to build and deploy web applications. Along the way, you’ll learn strategies for working effectively with agents and improve your development skills. In detail, you’ll: - Understand principles of agentic code development such as being precise, giving agents one task at a time, making prompts specific, keeping projects tidy, starting with fresh sessions for each new feature, and how to approach debugging. - Learn how to get started with Replit, and key skills for vibe coding: Thinking, using frameworks, checkpoints, debugging, and providing context. - Create a product requirement document (PRD) and wireframe for your agent to build a prototype of a website performance analyzer. - See how to use an agent to make your prototype more visually appealing, and deploy it application others to access . - Learn to build a head-to-head national park ranking app, from a sample dataset, with voting capabilities and persistent data storage, and refine further ask the assistant to recap and explain what it built to find room for improvement and reinforce your learning. By the end of this course, you’ll have a solid foundation in building with coding agents, and a process you can use to keep vibe coding effectively. Please sign up here:

New short course: Vibe Coding 101 with Replit! Learn to build and host applications with an AI agent in this course, built in partnership with Replit ⠕ and taught by its President Michele Catasta and Head of Developer Relations . Coding agents are changing how we write code. "Vibe coding" refers to a growing practice where you might barely look at the generated code, and instead focus on the architecture and features of your application. However, contrary to popular belief, effectively coding this way isn't done by just prompting, accepting all recommendations, and hoping for the best. It requires structuring your work, refining your prompts, and having a systematic process that lead to a more efficient and effective workflow. I code frequently using LLMs, and asking an LLM to do everything in one shot usually does not work. I'll typically take a problem, partition it into manageable modules, spend time creating prompts to specify each module, and use the model to produce the code one module at a time, and test/debug each module before moving on. A process like this is making me and many other developers faster and more efficient. In this video-only course, you’ll learn how to use Replit’s cloud environment--with an integrated code editor, package manager, and deployment tools--to build and deploy web applications. Along the way, you’ll learn strategies for working effectively with agents and improve your development skills. In detail, you’ll: - Understand principles of agentic code development such as being precise, giving agents one task at a time, making prompts specific, keeping projects tidy, starting with fresh sessions for each new feature, and how to approach debugging. - Learn how to get started with Replit, and key skills for vibe coding: Thinking, using frameworks, checkpoints, debugging, and providing context. - Create a product requirement document (PRD) and wireframe for your agent to build a prototype of a website performance analyzer. - See how to use an agent to make your prototype more visually appealing, and deploy it application others to access . - Learn to build a head-to-head national park ranking app, from a sample dataset, with voting capabilities and persistent data storage, and refine further ask the assistant to recap and explain what it built to find room for improvement and reinforce your learning. By the end of this course, you’ll have a solid foundation in building with coding agents, and a process you can use to keep vibe coding effectively. Please sign up here:

Andrew Ng

753,686 Aufrufe • vor 1 Jahr

"If everyone can build, it's your unique expertise, judgement, distribution, and more that people will pay for." Here’s my new episode with Amol Jain, Replit ⠕'s head of product engineering, about what it takes to turn a vibe-coded product into a real business. Amol shared: → 3 examples of apps built by non-coders that reached six figures → 4 steps to take an AI-built app from prototype to production (security!) → How to find your competitive advantage when code is free Some quotes from Amol: “He built the whole thing end to end in three days. Within the first two months, he was already at $180K+ in revenue.” “At Replit, this internal tool saves us six figures in SaaS costs. More importantly, anytime we want to add a feature, we just do it. We’re not at the mercy of someone else’s roadmap.” “The businesses that survive go beyond code to offer expertise, trust, infrastructure, networks, systems of record, data, physical goods, or services.” 📌 Watch now: Thanks to our sponsors: Riverside: The all-in-one AI studio I use to record and edit my podcast Linear: The AI agent platform for modern teams

"If everyone can build, it's your unique expertise, judgement, distribution, and more that people will pay for." Here’s my new episode with Amol Jain, Replit ⠕'s head of product engineering, about what it takes to turn a vibe-coded product into a real business. Amol shared: → 3 examples of apps built by non-coders that reached six figures → 4 steps to take an AI-built app from prototype to production (security!) → How to find your competitive advantage when code is free Some quotes from Amol: “He built the whole thing end to end in three days. Within the first two months, he was already at $180K+ in revenue.” “At Replit, this internal tool saves us six figures in SaaS costs. More importantly, anytime we want to add a feature, we just do it. We’re not at the mercy of someone else’s roadmap.” “The businesses that survive go beyond code to offer expertise, trust, infrastructure, networks, systems of record, data, physical goods, or services.” 📌 Watch now: Thanks to our sponsors: Riverside: The all-in-one AI studio I use to record and edit my podcast Linear: The AI agent platform for modern teams

Peter Yang

104,352 Aufrufe • vor 1 Monat

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

142,256 Aufrufe • vor 1 Jahr

Everyone's talking, reading, or writing about how much is changing in how we build products in the future, but very few people have actually experienced what the most cutting edge tools are capable of. In a new series on my podcast, I'm going to sit down with the founders of the most advanced product development tools to live demo what these tools can do, and then talk about the implications of this on product people's careers and lives. To kick things off, I sat down with Amjad Masad (Amjad Masad), co-founder and CEO of Replit ⠕, a browser-based coding environment that allows anyone to write and deploy code. Replit has 34 million users globally and is one of the fastest-growing developer communities in the world. In our conversation, Amjad shares: 🔸 A live demo of Replit building a full-stack web app from a text prompt 🔸 The implications of AI-powered development for product managers, designers, and engineers 🔸 What skills will matter more, and less, in the future 🔸 How this might reshape companies and careers 🔸 Why being “generative” will become an increasingly valuable skill 🔸 “Amjad’s law” and how learning to debug AI-generated code is becoming ever more valuable 🔸 Much more Listen now 👇 - YouTube: - Spotify: - Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 WorkOS — Modern identity platform for B2B SaaS, free up to 1 million MAUs: 🏆 — A global leader in digital identity verification: 🏆 @LinkedInMktg — Reach professionals and drive results for your business:

Everyone's talking, reading, or writing about how much is changing in how we build products in the future, but very few people have actually experienced what the most cutting edge tools are capable of. In a new series on my podcast, I'm going to sit down with the founders of the most advanced product development tools to live demo what these tools can do, and then talk about the implications of this on product people's careers and lives. To kick things off, I sat down with Amjad Masad (Amjad Masad), co-founder and CEO of Replit ⠕, a browser-based coding environment that allows anyone to write and deploy code. Replit has 34 million users globally and is one of the fastest-growing developer communities in the world. In our conversation, Amjad shares: 🔸 A live demo of Replit building a full-stack web app from a text prompt 🔸 The implications of AI-powered development for product managers, designers, and engineers 🔸 What skills will matter more, and less, in the future 🔸 How this might reshape companies and careers 🔸 Why being “generative” will become an increasingly valuable skill 🔸 “Amjad’s law” and how learning to debug AI-generated code is becoming ever more valuable 🔸 Much more Listen now 👇 - YouTube: - Spotify: - Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 WorkOS — Modern identity platform for B2B SaaS, free up to 1 million MAUs: 🏆 — A global leader in digital identity verification: 🏆 @LinkedInMktg — Reach professionals and drive results for your business:

Lenny Rachitsky

81,990 Aufrufe • vor 1 Jahr