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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 Postgres for database integration 🤖 CodeRabbit AI-powered PR reviews 🧾 Built-in credit system with usage tracking 🧪 Preview + code explorer toggleshow more

Code With Antonio

24,925 subscribers

92,964 Aufrufe • vor 1 Jahr •via X (Twitter)

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10 Kommentare

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Watch on YouTube:

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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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@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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@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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Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!

Workshop AI

29,022 Aufrufe • vor 5 Monaten

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

81,955 Aufrufe • vor 1 Jahr

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

228,497 Aufrufe • vor 4 Monaten

We're excited to launch 🚀Airtable AI Assistant 🚀 today, along with AI document analysis and AI web research capabilities! Airtable was founded 12 years ago with the mission of democratizing software creation. Our pioneering innovation was to distill app-building concepts (data, logic, interface) into intuitive visual components, like a no-code lego kit for app building. At the time, we speculated that someday, maybe AI would get good enough to enable conversational app building–talking to an expert AI app builder–and be a huge unlock, making app building even more accessible. We’re now at that point. While surprisingly impressive text generation and manipulation by LLMs was the breakthrough of the 2022 ChatGPT moment, the emergence of surprisingly impressive reasoning capability from LLMs is the breakthrough of 2025. This is unlocking more autonomous agentic experiences, and generating apps and code is the first killer use case (Cursor, @windsurf, Devin, v0, bolt.new, Replit ⠕ Agent to name a few). But for the large class of non-technical builders, a different approach is needed. When AI generates apps with code, rather than no-code building blocks, it requires a developer to fully understand how they work – and to verify them for hidden mistakes that would be tricky/impossible to debug by interface inspection alone (it may look right, but what is the data model business logic is flawed in non-obvious ways?). Airtable Assistant is an agent that can build and modify Airtable apps through conversation, changing schemas, adding automations, and designing interfaces. You can ask it to do things like: –“Research every conference attendee in this base” to have the Assistant immediately spin up an army of researchers that pull in background information for your attendees –“Analyze each contract to identify key risks they pose to my business” to have the Assistant add an AI field that runs an analysis at scale for each contract you’ve signed. Airtable Assistant can also answer questions about the data in your apps, like prompts as advanced as: –“I'm about to meet Jane Smith at Zelos, read all of their recent sales call transcripts and tell me how far along they are in their implementation and if they’re dealing with any issues” –“What are the most common risk factors in our contracts? Are there any changes to our default posture we might consider?” Credit to Mike Krieger for introducing us to the concept of low floor and high ceiling in HCI many years ago, which has become part of our internal lexicon for thinking about product improvements. Assistant dramatically lowers the floor to building apps, including more sophisticated ones, by helping human builders translate their business requirements into the schema design, logic, and interfaces required to deliver on the use case. In addition to launching Airtable Assistant today, we’re also releasing the capability to deploy thousands of AI web researchers, and AI document analysts, to continuously work on the data in Airtable apps. You can do things like: –Pull strategy and value stories from every product requirement doc to draft launch and release messaging –Monitor all brand mentions across digital channels to measure campaign impact –Create an automatically updating competitive intelligence dossier with the latest news and messaging from every competitor in your industry Check it out 👇

Howie Liu

2,313,379 Aufrufe • vor 1 Jahr

🧠 Aigentrun × XRPfi Analytics Is Live We’re proud to announce the launch of our XRPfi Analytics dashboard, powered by our agents This marks a major step forward for XRPfi transparency and analytics on the XRPL, giving traders and builders the clearest view yet of the ecosystem’s top protocols. 🚀 What’s New 🗂️ New XRPfi Tab → Real-time analytics with daily-refreshed data + AI agent integration 📊 XRPfi Analytics Table → Compare protocols, explore yields, and visualize XRP's expanding yield-bearing landscape 💬 Chat with the AI Assistant → Bottom-right pop-up where you can ask anything from “How safe are my funds in x protocol?” to “Where does the yield on x protocol come from?” or even “Analyze and rank the active XRPfi protocols by long-term yield sustainability.” 💻 Terminal & Traders Analysis Overhaul → Complete UI/UX redesign for the entire app including the Aigent Terminal, with faster performance and better flow 💡 Why It Matters The new dashboard is the first AI-powered analytics and hub for the XRPfi ecosystem. Turning complex yield data into clear, actionable insights that users can now explore and compare performance, safety, and yield data directly through our dashboard while assisted by specialized AI agents. 🔍 We’re Tracking Analytics from some of the XRPL’s leading XRPfi platforms such as Doppler Finance, Midas / Axelar Network, Kinetic.Market☀️, MoreMarkets, Strobe Finance, Ēnosys, and Soil 🌐 🔗 Try It Now: XRPfi Dashboard (Link in comments below) 👇

🧠 Aigentrun × XRPfi Analytics Is Live We’re proud to announce the launch of our XRPfi Analytics dashboard, powered by our agents This marks a major step forward for XRPfi transparency and analytics on the XRPL, giving traders and builders the clearest view yet of the ecosystem’s top protocols. 🚀 What’s New 🗂️ New XRPfi Tab → Real-time analytics with daily-refreshed data + AI agent integration 📊 XRPfi Analytics Table → Compare protocols, explore yields, and visualize XRP's expanding yield-bearing landscape 💬 Chat with the AI Assistant → Bottom-right pop-up where you can ask anything from “How safe are my funds in x protocol?” to “Where does the yield on x protocol come from?” or even “Analyze and rank the active XRPfi protocols by long-term yield sustainability.” 💻 Terminal & Traders Analysis Overhaul → Complete UI/UX redesign for the entire app including the Aigent Terminal, with faster performance and better flow 💡 Why It Matters The new dashboard is the first AI-powered analytics and hub for the XRPfi ecosystem. Turning complex yield data into clear, actionable insights that users can now explore and compare performance, safety, and yield data directly through our dashboard while assisted by specialized AI agents. 🔍 We’re Tracking Analytics from some of the XRPL’s leading XRPfi platforms such as Doppler Finance, Midas / Axelar Network, Kinetic.Market☀️, MoreMarkets, Strobe Finance, Ēnosys, and Soil 🌐 🔗 Try It Now: XRPfi Dashboard (Link in comments below) 👇

aigent.run

64,234 Aufrufe • vor 10 Monaten

google just released 15 AI tools that are completely FREE and can save thousands of $$$ every single monthly. all open-source. MIT licensed. save this in your bookmark." 1️⃣ pomelli ( builds your entire brand identity from just your website URL, then generates on-brand social posts, campaigns, and images. a free jasper + a junior brand marketer. no watermark, no gen cap in beta. 2️⃣ stitch ( describe an interface, get production-ready HTML/CSS/Tailwind + a figma export. google's free figma killer. 350 designs a month without paying a cent. 3️⃣ opal ( build no-code AI mini-apps and multi-step workflows just by describing them in plain english. basically a free n8n with Gemini baked in. no usage caps. 4️⃣ antigravity ( agentic IDE that plans, edits across files, and builds full apps from a single prompt. the "cursor-killer," free tier runs Gemini 3 Pro + Claude Sonnet 4.5. 5️⃣ mixboard ( canva x pinterest for AI. generate and remix images into moodboards, then edit right on the canvas with plain language. free while in beta. 6️⃣ disco ( turns your messy open browser tabs into custom interactive AI apps. competitor tabs become a comparison matrix, travel tabs become an itinerary. zero code. 7️⃣ notebookLM ( upload PDFs, videos, and notes, get instant summaries, mind maps, quizzes, even a podcast of your own material. replaces notion AI + perplexity + readwise. 8️⃣ Learn Your Way ( turns any topic into a personalized, AI-built course. immersive text, audio lessons, mind maps, and quizzes adapted to how you actually learn. free tutoring. 🔟 Google AI Studio ( prototype and ship AI apps in seconds with a free API key and a 1M-token context window. replaces the openai playground + paid API credits. 1️⃣1️⃣ Jules ( assign it a github issue, it spins up a VM, writes a plan, makes the changes, and opens a PR. a free devin. 15 tasks a day. 1️⃣2️⃣ Gemini CLI ( claude-code in your terminal. reads your codebase, runs commands, ships PRs. genuinely open source (Apache 2.0) and free. 1️⃣3️⃣ Code Wiki ( point it at any public github repo, get a living, self-updating wiki with architecture diagrams and a Gemini chat, every section hyperlinked to the code. 1️⃣4️⃣ Firebase Studio ( AI cockpit for your backend and cloud logic. heads up: existing users only, google is winding it down, so don't start a new project here. 1️⃣5️⃣ Gemini Code Assist ( free github copilot: 180k code completions a month + AI code reviews in VS Code, JetBrains, and github. the free tier that actually out-specs copilot. Follow me and turn on 🔔 post notifications.

m0h

84,062 Aufrufe • vor 1 Monat

I've been building a music player with Next.js for fun. Here's a quick demo of how it works (it's open source!) • Demo: • Code: If you want to learn more about how it's built, here's more details ↓ I'm using Postgres (with Drizzle) to store information about the songs and playlists. Audio and image files are stored in Vercel Blob (object storage), and the URLs are then referenced in the database. For the UI, I'm using shadcn/ui (so Tailwind CSS and Radix). This made it easy to copy/paste in some nice components, like the dropdown menus. I built the entire first version of the UI in v0 and then iterated from there, feeding it my Drizzle schema as a source in the project and having it scaffold some of the boilerplate for me: I added support for keyboard navigation (using arrow keys) or vim motions (j/k to go up/down, and h/l to go between playlists and tracks). Also, space to toggle the now playing song, and / to focus the search input. The search function has a nice utility to highlight the currently searched text on the page in yellow. Then, I was exploring how to pass metadata from my application to macOS or iOS. Turns out there's an API for that – MediaSession. Web apps can share metadata about what media is playing (title, artist, album artwork) and sync play/pause/seek with system media controls. Works across modern browsers — even integrates with iOS dynamic island and shows up on lock screens: I set up my app like a PWA – it has a manifest.json file, so it can be installed to my iOS home screen or added to my dock on macOS. On iOS, it then uses the full screen height `100dvh` (dynamic viewport) and has padding on the bottom for the safe area with the `env()` CSS function. Finally, I was able to use the Vercel AI SDK in a script to clean up the metadata on audio files I downloaded from YouTube. Bonus: I even was able to dogfood the React Compiler, which helped me fix a performance bug! That's all! It's fun to make personal software:

I've been building a music player with Next.js for fun. Here's a quick demo of how it works (it's open source!) • Demo: • Code: If you want to learn more about how it's built, here's more details ↓ I'm using Postgres (with Drizzle) to store information about the songs and playlists. Audio and image files are stored in Vercel Blob (object storage), and the URLs are then referenced in the database. For the UI, I'm using shadcn/ui (so Tailwind CSS and Radix). This made it easy to copy/paste in some nice components, like the dropdown menus. I built the entire first version of the UI in v0 and then iterated from there, feeding it my Drizzle schema as a source in the project and having it scaffold some of the boilerplate for me: I added support for keyboard navigation (using arrow keys) or vim motions (j/k to go up/down, and h/l to go between playlists and tracks). Also, space to toggle the now playing song, and / to focus the search input. The search function has a nice utility to highlight the currently searched text on the page in yellow. Then, I was exploring how to pass metadata from my application to macOS or iOS. Turns out there's an API for that – MediaSession. Web apps can share metadata about what media is playing (title, artist, album artwork) and sync play/pause/seek with system media controls. Works across modern browsers — even integrates with iOS dynamic island and shows up on lock screens: I set up my app like a PWA – it has a manifest.json file, so it can be installed to my iOS home screen or added to my dock on macOS. On iOS, it then uses the full screen height `100dvh` (dynamic viewport) and has padding on the bottom for the safe area with the `env()` CSS function. Finally, I was able to use the Vercel AI SDK in a script to clean up the metadata on audio files I downloaded from YouTube. Bonus: I even was able to dogfood the React Compiler, which helped me fix a performance bug! That's all! It's fun to make personal software:

Lee Robinson

118,242 Aufrufe • vor 1 Jahr