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Ana Sayfaya Dön

React Native hasn't shipped a new UI primitive in years. No slider. No date picker. No segmented control. So you install a community package and pray it survives your next upgrade. Expo UI kills that. Real native SwiftUI + Jetpack Compose components, written in JSX. 30-min crash course on... show more

Beto

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132,985 görüntüleme • 1 yıl önce

Expo Router just unlocked a new level of native on iOS 🚀 For years, cross-platform meant tradeoffs. Your app worked everywhere, but it never felt quite right. That gap is finally closing. With the latest version of Expo Router, native iOS APIs are now exposed declaratively. No UIKit wrestling. No fake UI. If you want your app to feel truly native on iOS, these are the APIs you should be using: - Native Tabs (real system tab bar) - Stack Toolbar (native header controls) - Bottom toolbars with placement=“bottom” - Bottom accessories attached to the tab bar - Zoom transitions for fluid navigation - Native sheet footers (experimental) I wrote a full breakdown with code examples and video demos of these features in my blog (link below 👇)

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Introducing primeui. Build sites fast. Fear no code. Available today • 200+ handcrafted marketing UI components and templates • Sitemap planner • Prototype + experiment on an infinite canvas • Clean export to Next.js, Tailwind + shadcn/ui compatible • Not just landing pages: build Blog, Docs, Pricing, and more Coming soon • MCP • Skills • AI Designer We started Prime UI because we believe site builders that do not output real code end up slowing you down. So instead of building another “app builder,” we focused on marketing sites, the work we know best after 10+ years of designing and building high-end websites at Pixel Point. Human expertise combined with AI scalability is what we believe in. Prime UI isn’t here (yet) to fully replace your stack, but it is already capable of saving you hundreds of hours in prototyping and the early phases of your next site project. What’s next: MCP: continuously add new pages to your site from Prime UI, aligned with your project setup and style. Skills: an AI-agent-friendly concentrate of our years of website design and development expertise. It is time to ditch old habits. Fear no code and build sites fast, ready for the AI era.

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Konrad Reczko

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just dropped a 24-min walkthrough showing how I turn raw n8n automations into actual front-end apps that your team can use no clunky JSON files, no ugly interfaces, and no dev team required I built a clean UI for one of my n8n flows - start to finish - all in one session it’s not a polished SaaS - but it is a working MVP you can test, share, or hand off step-by-step: – mapped the UX in ChatGPT – built the UI live in Bolt – connected it to the backend automation by the end, I had a usable internal tool that felt like a real product — all without writing a single line of frontend code if you're building powerful automations but not wrapping them in UI… you’re missing half the value also dropped my full prompt stack for planning and generating UIs with Claude or ChatGPT want the prompts? comment “UI”, follow + repost and I’ll send them over (must be following so I can DM)

just dropped a 24-min walkthrough showing how I turn raw n8n automations into actual front-end apps that your team can use no clunky JSON files, no ugly interfaces, and no dev team required I built a clean UI for one of my n8n flows - start to finish - all in one session it’s not a polished SaaS - but it is a working MVP you can test, share, or hand off step-by-step: – mapped the UX in ChatGPT – built the UI live in Bolt – connected it to the backend automation by the end, I had a usable internal tool that felt like a real product — all without writing a single line of frontend code if you're building powerful automations but not wrapping them in UI… you’re missing half the value also dropped my full prompt stack for planning and generating UIs with Claude or ChatGPT want the prompts? comment “UI”, follow + repost and I’ll send them over (must be following so I can DM)

J.B.

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Ziwen

18,451 görüntüleme • 4 gün önce

We wanted to show the performance and the insane power of the Static Hermes native FFI. But we don't yet support the all language features needed to compile React Native (soon though!), so we improvised. We imported the bindings for DearImGui (a popular C++ imperative game UI library that renders meshes), and Sokol (an amazing lightweight 3D backend in C) and wrote a small demo. "Imperative UI" means that the entire UI and the state of the screen is recreated on every frame, which suits our purposes to demonstrate SH very well. The demo runs 100% compiled native code. JavaScript runs in every frame and recreates the entire state of the screen. It is portable to all platforms, though the screen layout is not optimized for phone. We wrote the demo in C++ and in JS, to compare, and they both ran with the same performance. In the attached videos you can see the demo running at the stable screen refresh rate - 120Hz on my Mac, 60Hz on a old Moto G5 phone. It includes some widgets, an n-body simulation of planets, a playable game demo, etc.

We wanted to show the performance and the insane power of the Static Hermes native FFI. But we don't yet support the all language features needed to compile React Native (soon though!), so we improvised. We imported the bindings for DearImGui (a popular C++ imperative game UI library that renders meshes), and Sokol (an amazing lightweight 3D backend in C) and wrote a small demo. "Imperative UI" means that the entire UI and the state of the screen is recreated on every frame, which suits our purposes to demonstrate SH very well. The demo runs 100% compiled native code. JavaScript runs in every frame and recreates the entire state of the screen. It is portable to all platforms, though the screen layout is not optimized for phone. We wrote the demo in C++ and in JS, to compare, and they both ran with the same performance. In the attached videos you can see the demo running at the stable screen refresh rate - 120Hz on my Mac, 60Hz on a old Moto G5 phone. It includes some widgets, an n-body simulation of planets, a playable game demo, etc.

Tzvetan Mikov

826,175 görüntüleme • 2 yıl önce

I took Clicky and I made it 5x Faster So I saw that Farza 🇵🇰🇺🇸 was using uses Claude's vision to find UI elements on screen, send a screenshot, wait for coordinates back. It works, but it's slow. I replaced that with OmniParser V2 by Microsoft which is a local Object detection model trained specifically on UI elements. It runs on-device, detects every button, menu, and icon in 400ms, and gives me pixel-precise coordinates. No API call, no latency, no cost. The green highlights you see around the UI elements is the detection overlay and you can see as I am switching the screen it takes no time to detect and highlight which is pretty neat! With Local models improving by the day, Its the right direction for applications like these. Next up: video-synced tutorials where a YouTube tutorial pauses and waits for you to perform each action in the real app. I am not stopping!

I took Clicky and I made it 5x Faster So I saw that Farza 🇵🇰🇺🇸 was using uses Claude's vision to find UI elements on screen, send a screenshot, wait for coordinates back. It works, but it's slow. I replaced that with OmniParser V2 by Microsoft which is a local Object detection model trained specifically on UI elements. It runs on-device, detects every button, menu, and icon in 400ms, and gives me pixel-precise coordinates. No API call, no latency, no cost. The green highlights you see around the UI elements is the detection overlay and you can see as I am switching the screen it takes no time to detect and highlight which is pretty neat! With Local models improving by the day, Its the right direction for applications like these. Next up: video-synced tutorials where a YouTube tutorial pauses and waits for you to perform each action in the real app. I am not stopping!

Milind S

73,349 görüntüleme • 4 ay önce

I've been collecting the best dev resources, and workflows for years. tutorials, tools, UI libs… everything that actually helps you ship today I'm putting it all into one place: this is my biggest project so far in the age of AI, tools are everywhere but real builders and real communities matter more than ever one time entry. no subscriptions. early members will shape what this becomes let's build ⚔️

I've been collecting the best dev resources, and workflows for years. tutorials, tools, UI libs… everything that actually helps you ship today I'm putting it all into one place: this is my biggest project so far in the age of AI, tools are everywhere but real builders and real communities matter more than ever one time entry. no subscriptions. early members will shape what this becomes let's build ⚔️

OrcDev

72,280 görüntüleme • 4 ay önce

most people spend hours describing what they want to Claude Code this guy just browsed a catalog of thousands of animated UI components, found one he liked, and hit "copy prompt" that's it. the prompt goes into Claude Code and it builds it. > 21st(.)dev - a library of community-made components built for React, Next.js, Tailwind > every component has a ready-made prompt attached > you pick the effect, copy, paste, done no describing animations from scratch. no explaining what "smooth scroll" or "hover glow" means. someone already figured out the exact prompt that produces it. gap between people who know this exists and people who don't is measured in hours per project full walkthrough in the article below

most people spend hours describing what they want to Claude Code this guy just browsed a catalog of thousands of animated UI components, found one he liked, and hit "copy prompt" that's it. the prompt goes into Claude Code and it builds it. > 21st(.)dev - a library of community-made components built for React, Next.js, Tailwind > every component has a ready-made prompt attached > you pick the effect, copy, paste, done no describing animations from scratch. no explaining what "smooth scroll" or "hover glow" means. someone already figured out the exact prompt that produces it. gap between people who know this exists and people who don't is measured in hours per project full walkthrough in the article below

monokern

64,484 görüntüleme • 1 ay önce

I am very excited to release GeoLibre v1.0 🌍 GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. In this video, I walk through GeoLibre 1.0 step by step: how to install and run it, load vector and raster data, stream gigabyte-scale cloud-native datasets without downloading them, edit attributes and geometry, work with PMTiles, 3D tiles, LiDAR point clouds, and DuckDB, and share your projects as static links. GeoLibre is built on MapLibre GL JS, React + TypeScript, Tauri (Rust), DuckDB, and Try it: GitHub: Full video tutorial: If you have feature requests or run into bugs, leave a comment or open an issue on GitHub. And if you find GeoLibre useful, please give it a star. #GIS #OpenSource #Geospatial #MapLibre #Python #DataVisualization #GeoLibre

I am very excited to release GeoLibre v1.0 🌍 GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. In this video, I walk through GeoLibre 1.0 step by step: how to install and run it, load vector and raster data, stream gigabyte-scale cloud-native datasets without downloading them, edit attributes and geometry, work with PMTiles, 3D tiles, LiDAR point clouds, and DuckDB, and share your projects as static links. GeoLibre is built on MapLibre GL JS, React + TypeScript, Tauri (Rust), DuckDB, and Try it: GitHub: Full video tutorial: If you have feature requests or run into bugs, leave a comment or open an issue on GitHub. And if you find GeoLibre useful, please give it a star. #GIS #OpenSource #Geospatial #MapLibre #Python #DataVisualization #GeoLibre

Qiusheng Wu

39,593 görüntüleme • 2 ay önce

Anthropic's in trouble, again! They spent years building what's now fully open-source. What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box. For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response. Every major AI product tried to replicate it. But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shipped natively with LangGraph, CrewAI, or Google ADK. So teams started building an owned version that required engineering the entire interface layer from scratch. Most teams, however, just settled for shipping the agent as a backend API in a chat box since rendering the UI is only one piece of it. To actually make it work, the interface layer also needed real-time streaming, state kept in sync between agent and UI, conversations that persist across sessions, and reconnection when a user refreshes mid-run. CopilotKit🪁 is now the only open-source framework that actually lets you build your own full-stack Claude-like apps. It decouples the agent from the interface, talking over AG-UI (an open protocol for agent-to-user communication). Being a standard protocol, the frontend never needs to know whether it is talking to a LangGraph or a CrewAI agent. You can change the backend anytime and the UI will never notice. In practice, CopilotKit's interface layer gives several pre-implemented React building blocks that wire the agent directly into the app, like: - generative UI, so the agent renders real components instead of text - chat windows, sidebars, and popups, or a fully headless setup - shared state, so the agent and app stay in sync - human-in-the-loop approvals, where the agent waits before acting - persistent threads that store the whole session, including the agent-user interactions and generated UI, not just text And because that full history is captured, those interactions can feed a self-learning layer that also improves the agent from real usage over time. The interface layer that Anthropic spent years engineering in-house is now literally available to any developer/team. CopilotKit is open-source with 30k+ GitHub stars, and AG-UI, the protocol underneath, is already supported across every major agent framework: LangGraph, CrewAI, Mastra, Google ADK, and more. CopilotKit GitHub repo → (don't forget to star it ⭐ ) If you want to go deeper, I found a detailed breakdown by Shubham Saboo recently on the three Generative UI patterns, with implementation. Read it below.

Anthropic's in trouble, again! They spent years building what's now fully open-source. What made Claude feel different from a normal app is that the agent could act inside the interface instead of only talking in a chat box. For instance, Claude Artifacts let an agent render real UI, charts, dashboards, and interactive components that assemble live inside the response. Every major AI product tried to replicate it. But the problem was that unlike reasoning, planning, tool-calling, etc., none of it shipped natively with LangGraph, CrewAI, or Google ADK. So teams started building an owned version that required engineering the entire interface layer from scratch. Most teams, however, just settled for shipping the agent as a backend API in a chat box since rendering the UI is only one piece of it. To actually make it work, the interface layer also needed real-time streaming, state kept in sync between agent and UI, conversations that persist across sessions, and reconnection when a user refreshes mid-run. CopilotKit🪁 is now the only open-source framework that actually lets you build your own full-stack Claude-like apps. It decouples the agent from the interface, talking over AG-UI (an open protocol for agent-to-user communication). Being a standard protocol, the frontend never needs to know whether it is talking to a LangGraph or a CrewAI agent. You can change the backend anytime and the UI will never notice. In practice, CopilotKit's interface layer gives several pre-implemented React building blocks that wire the agent directly into the app, like: - generative UI, so the agent renders real components instead of text - chat windows, sidebars, and popups, or a fully headless setup - shared state, so the agent and app stay in sync - human-in-the-loop approvals, where the agent waits before acting - persistent threads that store the whole session, including the agent-user interactions and generated UI, not just text And because that full history is captured, those interactions can feed a self-learning layer that also improves the agent from real usage over time. The interface layer that Anthropic spent years engineering in-house is now literally available to any developer/team. CopilotKit is open-source with 30k+ GitHub stars, and AG-UI, the protocol underneath, is already supported across every major agent framework: LangGraph, CrewAI, Mastra, Google ADK, and more. CopilotKit GitHub repo → (don't forget to star it ⭐ ) If you want to go deeper, I found a detailed breakdown by Shubham Saboo recently on the three Generative UI patterns, with implementation. Read it below.

Avi Chawla

458,882 görüntüleme • 3 ay önce

Apple’s new Gaussian Splat model seems like the perfect tech for a native Maps app on Vision Pro. Imagine an immersive version of Look Around where you can actually walk through cities and explore places from every angle, in 3D. I tried it with some of my favorite places, and it genuinely feels like being there again. It’s wild that this works from just a single image.

Apple’s new Gaussian Splat model seems like the perfect tech for a native Maps app on Vision Pro. Imagine an immersive version of Look Around where you can actually walk through cities and explore places from every angle, in 3D. I tried it with some of my favorite places, and it genuinely feels like being there again. It’s wild that this works from just a single image.

Phil Traut ᯅ

31,958 görüntüleme • 8 ay önce

Local models just got a free intelligence upgrade. Someone took the new Qwen3.8-27B (the one that already runs in 22GB) and only changed the chat template. No fine-tune. No new training. Just a smarter system prompt that kills all the filler and forces the model to stay sharp. Result: the same weights are now fixing real post-cutoff bugs faster and cleaner than Claude Opus 5 High in their tests. They call it the Sharp template. It’s free. Drop it on any Qwen3.5 / 3.6 / 3.8 model and it just works with llama.cpp. This is the kind of quiet upgrade that actually moves the needle for people running models locally.

Local models just got a free intelligence upgrade. Someone took the new Qwen3.8-27B (the one that already runs in 22GB) and only changed the chat template. No fine-tune. No new training. Just a smarter system prompt that kills all the filler and forces the model to stay sharp. Result: the same weights are now fixing real post-cutoff bugs faster and cleaner than Claude Opus 5 High in their tests. They call it the Sharp template. It’s free. Drop it on any Qwen3.5 / 3.6 / 3.8 model and it just works with llama.cpp. This is the kind of quiet upgrade that actually moves the needle for people running models locally.

Harman

73,661 görüntüleme • 14 gün önce

🔥 Guys, I think I COOKED something special... Introducing HelpKit for Mobile Apps! 📲 You can now embed a native help center directly in your consumer app that actually feels like it belongs there. 🔴 Live on Product Hunt today (Link below) 📱 React Native SDK (Swift coming soon) 📝 Ready-made mobile app FAQ template ⚡ Edit in Notion → Sync → No app update needed 📉 60-80% fewer support tickets Perfect for consumer app founders ready to automate support so you can get back to building and growing. If you have a second would love your support on Product Hunt! 🚀 Link in first comment 👇

🔥 Guys, I think I COOKED something special... Introducing HelpKit for Mobile Apps! 📲 You can now embed a native help center directly in your consumer app that actually feels like it belongs there. 🔴 Live on Product Hunt today (Link below) 📱 React Native SDK (Swift coming soon) 📝 Ready-made mobile app FAQ template ⚡ Edit in Notion → Sync → No app update needed 📉 60-80% fewer support tickets Perfect for consumer app founders ready to automate support so you can get back to building and growing. If you have a second would love your support on Product Hunt! 🚀 Link in first comment 👇

Dominik Sobe ツ

10,406 görüntüleme • 1 yıl önce

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

Santiago

17,438 görüntüleme • 2 ay önce

ANTHROPIC JUST KILLED A DOZEN AI MEMORY STARTUPS WITH ONE BUILT IN TOOL people raised millions to give AI long term memory. Anthropic just shipped it straight into the API. free, no framework, no vector database. it is a folder of files Claude reads and writes. that is it. the trick: it is client side. Claude never touches your data directly. it only requests a file operation, and your app runs it against storage you control. before every task Claude checks its /memories directory, pulls back what it learned last time, and keeps going. when it learns something new, it writes it down. six plain operations do all of it: > view, create, str_replace, insert, delete, rename why it actually wins: > just in time retrieval, it reads on demand instead of loading everything up front > it survives a context reset, so a long job resumes instead of starting over > every path is locked to /memories, so it cannot wander your filesystem > works on every Claude 4 model, no beta flag, generally available Anthropic even pairs it with context editing and compaction, so the live window stays tiny while the important stuff lives on disk. the whole thing in one line: Claude keeps the notes, you keep the storage. bookmark this before you pay for a memory layer you no longer need.

ANTHROPIC JUST KILLED A DOZEN AI MEMORY STARTUPS WITH ONE BUILT IN TOOL people raised millions to give AI long term memory. Anthropic just shipped it straight into the API. free, no framework, no vector database. it is a folder of files Claude reads and writes. that is it. the trick: it is client side. Claude never touches your data directly. it only requests a file operation, and your app runs it against storage you control. before every task Claude checks its /memories directory, pulls back what it learned last time, and keeps going. when it learns something new, it writes it down. six plain operations do all of it: > view, create, str_replace, insert, delete, rename why it actually wins: > just in time retrieval, it reads on demand instead of loading everything up front > it survives a context reset, so a long job resumes instead of starting over > every path is locked to /memories, so it cannot wander your filesystem > works on every Claude 4 model, no beta flag, generally available Anthropic even pairs it with context editing and compaction, so the live window stays tiny while the important stuff lives on disk. the whole thing in one line: Claude keeps the notes, you keep the storage. bookmark this before you pay for a memory layer you no longer need.

NO1ennn

42,946 görüntüleme • 18 gün önce