Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Motion 13.4 introduces <AnimateView /> A lightweight view transitions component built on React's new ViewTransition API. Adds spring support, dynamic targets, animation controls, and a simple props API - no more wrangling pseudo selectors!

Motion

16,199 subscribers

41,632 просмотров • 6 дней назад •via X (Twitter)

Искусство Образование Наука и технологии

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

I built a plugin to generate 3D assets directly from Codex, using the latest update that introduces image generation. It generates an image, calls the Tripo3D API, then starts an MCP server and a local viewer directly inside Codex. It uses the paid Tripo3D API (12 free generations, 600 credits included). Everything is open source on my GitHub. Link below. Feel free to contribute. Room for improvement: skeleton/animation support and multi-provider 3D support.

I built a plugin to generate 3D assets directly from Codex, using the latest update that introduces image generation. It generates an image, calls the Tripo3D API, then starts an MCP server and a local viewer directly inside Codex. It uses the paid Tripo3D API (12 free generations, 600 credits included). Everything is open source on my GitHub. Link below. Feel free to contribute. Room for improvement: skeleton/animation support and multi-provider 3D support.

Defend Intelligence (Anis Ayari)

12,151 просмотров • 5 месяцев назад

Scroll-triggered animations are coming to Chrome early next year (and we've been really excited about this one for a bit!) 🥳 Unlike scroll-driven animations (already in Chrome & Safari), this API introduces "timeline-trigger" and "animation-trigger" to start an animation within a specific range, rather than relying on the scroller completion *as* the animation timeline. I got nerd-sniped and wanted to try it out so I built this shape morphing demo to show how you can apply multiple animations to the same element over with different triggers. PRETTY COOL IMO! Bramus has a post with more info ⬇️

Scroll-triggered animations are coming to Chrome early next year (and we've been really excited about this one for a bit!) 🥳 Unlike scroll-driven animations (already in Chrome & Safari), this API introduces "timeline-trigger" and "animation-trigger" to start an animation within a specific range, rather than relying on the scroller completion as the animation timeline. I got nerd-sniped and wanted to try it out so I built this shape morphing demo to show how you can apply multiple animations to the same element over with different triggers. PRETTY COOL IMO! Bramus has a post with more info ⬇️

Una 🇺🇦

38,782 просмотров • 9 месяцев назад

We’ve entered a new era 💪 🇺🇸 The Exchange has arrived in the US Built for advanced traders, it’s the world’s leading USD-supporting crypto exchange by spot volume and boasts: 🌊 Deep liquidity and low fees for 480+ pairs 💻 GEN3 tech stack for fast executions 🔄 Seamless USD transfers 🔐 Industry-leading security 🤖 Advanced trading bots 🔌 API connectivity 👨‍💻 24/7 client support ➕ Much more 📲 Available on mobile, desktop and via API Sign Up Now:

We’ve entered a new era 💪 🇺🇸 The Exchange has arrived in the US Built for advanced traders, it’s the world’s leading USD-supporting crypto exchange by spot volume and boasts: 🌊 Deep liquidity and low fees for 480+ pairs 💻 GEN3 tech stack for fast executions 🔄 Seamless USD transfers 🔐 Industry-leading security 🤖 Advanced trading bots 🔌 API connectivity 👨‍💻 24/7 client support ➕ Much more 📲 Available on mobile, desktop and via API Sign Up Now:

Crypto.com Exchange

261,938 просмотров • 1 год назад

Web Scraping is dead. Web Agenting is here. Writing selectors (div > .class > span) breaks every time a site updates. Building custom bots for every new target is a waste of engineering hours. TinyFish turns the entire real-time web into a single API. Input: Natural Language ("Find availability for X"). Target: 1 or 100 URLs. Output: Structured JSON. This isn't a simulation. It visits the Real-Time Web. 1./ One API, Many Sites - Same contract whether you hit 1 URL or 50. You focus on the Goal (Business Logic). TinyFish handles the How (Navigation, Clicks, Inputs). 2./ Real Automation - It doesn't just "read." It interacts. It fills forms, navigates multi-step flows, and handles dynamic JS content. 3./ Production Ready - This is the same infrastructure used by large enterprises, now exposed as a clean developer primitive. Logs, error handling, and structured data are built-in. The web is finally a proper API.

Web Scraping is dead. Web Agenting is here. Writing selectors (div > .class > span) breaks every time a site updates. Building custom bots for every new target is a waste of engineering hours. TinyFish turns the entire real-time web into a single API. Input: Natural Language ("Find availability for X"). Target: 1 or 100 URLs. Output: Structured JSON. This isn't a simulation. It visits the Real-Time Web. 1./ One API, Many Sites - Same contract whether you hit 1 URL or 50. You focus on the Goal (Business Logic). TinyFish handles the How (Navigation, Clicks, Inputs). 2./ Real Automation - It doesn't just "read." It interacts. It fills forms, navigates multi-step flows, and handles dynamic JS content. 3./ Production Ready - This is the same infrastructure used by large enterprises, now exposed as a clean developer primitive. Logs, error handling, and structured data are built-in. The web is finally a proper API.

Tech with Mak

119,865 просмотров • 7 месяцев назад

A tour of the post-processing features in my WebGPU engine. Chaining global passes like blur, bloom, and pixelate, on top of a disturb pipeline with its own options: distortion, black and white, lighten, darken, noise, RGB split, and more. It also supports layer and plane UV isolation. Planes can have optional shadows and rounded borders. Behind-the-scenes split view shows the raw pass vs final composite. Built from scratch with the WebGPU JavaScript API. Lightweight, minimal code, 0 dependencies, modular custom components 🧩. Next, vertex work and finish the MTSDF generator I’m building in Rust. ✨

A tour of the post-processing features in my WebGPU engine. Chaining global passes like blur, bloom, and pixelate, on top of a disturb pipeline with its own options: distortion, black and white, lighten, darken, noise, RGB split, and more. It also supports layer and plane UV isolation. Planes can have optional shadows and rounded borders. Behind-the-scenes split view shows the raw pass vs final composite. Built from scratch with the WebGPU JavaScript API. Lightweight, minimal code, 0 dependencies, modular custom components 🧩. Next, vertex work and finish the MTSDF generator I’m building in Rust. ✨

Aristide Benoist

16,364 просмотров • 7 месяцев назад

Fable 5 just dropped and someone already built a $10k-looking website with it. Here's the full workflow The smooth scrolling, the animations, the transitions, all built with Fable 5. Here's how to get the same result instead of a generic template. 1. Steal a direction first. Go to Mobbin or Godly and find a site whose feel you love. Screenshot it. Fable copies a vibe far better than it invents one. 2. Grab real components. Pull animation-ready blocks from Aceternity UI or Magic UI. These are built for exactly this look (scroll reveals, parallax, gradients). 3. Prompt Fable with all of it. Switch to Fable 5 in Claude Code, drop in your screenshots and the component references, and describe the sections and scroll behavior you want. Let it plan before it builds. 4. Animate with the right tools. Tell it to use GSAP with ScrollTrigger for scroll effects, or Framer Motion for React. This is what separates "nice" from "$10k." 5. Iterate on feel, not code. Preview it, then give Fable specific notes ("slower fade, more spacing on mobile") until it lands. Bookmark this

Fable 5 just dropped and someone already built a $10k-looking website with it. Here's the full workflow The smooth scrolling, the animations, the transitions, all built with Fable 5. Here's how to get the same result instead of a generic template. 1. Steal a direction first. Go to Mobbin or Godly and find a site whose feel you love. Screenshot it. Fable copies a vibe far better than it invents one. 2. Grab real components. Pull animation-ready blocks from Aceternity UI or Magic UI. These are built for exactly this look (scroll reveals, parallax, gradients). 3. Prompt Fable with all of it. Switch to Fable 5 in Claude Code, drop in your screenshots and the component references, and describe the sections and scroll behavior you want. Let it plan before it builds. 4. Animate with the right tools. Tell it to use GSAP with ScrollTrigger for scroll effects, or Framer Motion for React. This is what separates "nice" from "$10k." 5. Iterate on feel, not code. Preview it, then give Fable specific notes ("slower fade, more spacing on mobile") until it lands. Bookmark this

Fokki

72,175 просмотров • 2 месяцев назад

THIS AIBO ISN’T A TOY. IT’S THE MOST ADVANCED ROBOT PET EVER BUILT. 🐕🤖 Sony didn’t just build a gadget — they built something that runs on 22-axis lifelike movement, recognizes your face, and develops its own “personality” over time based on how you interact with it. Here’s what makes it wild: 🐾 Learns and adapts — no two Aibos behave exactly the same after a few months of use 🐾 Cloud-connected personality — its behavior profile lives on Sony’s servers, evolving with every interaction 🐾 Free developer API with visual programming — which has made it a favorite tool in robotics classrooms worldwide 🐾 Real-world use cases far beyond “cute robot dog”: home companionship, senior care and emotional support, STEM education, even security patrol duties No vet bills. No allergies. No mess. Just a machine that’s been engineered to feel less like a product and more like a living companion. We used to think “robot pets” meant clunky toys with blinking lights. Sony quietly spent years proving the whole category could feel real. The future of companionship isn’t fully human anymore. And it’s already sitting on someone’s couch right now.

DN_DEGEN

115,378 просмотров • 1 месяц назад

look what a single consumer GPU just built. gave Qwen3.5-35B-A3B one prompt: build a cloud GPU marketplace with pricing cards, deploy templates, and a benchmark leaderboard. it planned the layout, wrote the animations, populated the data, and served it. one shot. one HTML file. then i told it to iterate. split the hero, add a floating GPU with neural network animation. glassmorphism on the cards. done. done. done. three rounds, no confusion, no regressions. 4-bit quantized. 19.7 GB. single RTX 3090. full coding agent claude code harness running on localhost. no API calls leaving my machine. no subscription. no rate limits. earlier today i pointed it at my own production website. it curled the HTML, found every broken link, and told me "pretty shell, empty core. would not recommend." then built a better version from scratch. local inference stops being a demo when you actually steer it. the models are there. they understand intent. but you have to meet them halfway with good prompts, clear context, and real project structure. that's the skill gap now. not the models. the steering. more experiments coming. i genuinely cannot stop playing with this thing.

look what a single consumer GPU just built. gave Qwen3.5-35B-A3B one prompt: build a cloud GPU marketplace with pricing cards, deploy templates, and a benchmark leaderboard. it planned the layout, wrote the animations, populated the data, and served it. one shot. one HTML file. then i told it to iterate. split the hero, add a floating GPU with neural network animation. glassmorphism on the cards. done. done. done. three rounds, no confusion, no regressions. 4-bit quantized. 19.7 GB. single RTX 3090. full coding agent claude code harness running on localhost. no API calls leaving my machine. no subscription. no rate limits. earlier today i pointed it at my own production website. it curled the HTML, found every broken link, and told me "pretty shell, empty core. would not recommend." then built a better version from scratch. local inference stops being a demo when you actually steer it. the models are there. they understand intent. but you have to meet them halfway with good prompts, clear context, and real project structure. that's the skill gap now. not the models. the steering. more experiments coming. i genuinely cannot stop playing with this thing.

Sudo su

37,373 просмотров • 6 месяцев назад

New open source library: kugiri (区切り). Already running in production on several of my sites, now public. It splits text into lines, words and characters, the thing every text reveal needs. The difference is where it cuts. Most splitters guess where a line breaks, and the guess falls apart the moment the text does something real: text-wrap: balance, hyphenation, a drop cap, a float, a link that wraps, RTL, Japanese. kugiri does not guess. It asks the browser where the lines already are and cuts exactly there, so the split text looks pixel for pixel like the text before it. No animation, no scroll watching, no opinions. Every unit gets an index and the library gets out of the way. Animate with CSS, the Web Animations API, GSAP or Motion. One file, no dependencies, about 7 kB gzipped. The demo is also the test suite: fifty situations, each checked against what the browser painted, in Chromium, WebKit and Firefox. Demo: npm: Source:

New open source library: kugiri (区切り). Already running in production on several of my sites, now public. It splits text into lines, words and characters, the thing every text reveal needs. The difference is where it cuts. Most splitters guess where a line breaks, and the guess falls apart the moment the text does something real: text-wrap: balance, hyphenation, a drop cap, a float, a link that wraps, RTL, Japanese. kugiri does not guess. It asks the browser where the lines already are and cuts exactly there, so the split text looks pixel for pixel like the text before it. No animation, no scroll watching, no opinions. Every unit gets an index and the library gets out of the way. Animate with CSS, the Web Animations API, GSAP or Motion. One file, no dependencies, about 7 kB gzipped. The demo is also the test suite: fifty situations, each checked against what the browser painted, in Chromium, WebKit and Firefox. Demo: npm: Source:

Edoardo Lunardi

42,898 просмотров • 17 дней назад

xAI isn't playing around. They just released the Grok Imagine API, a unified video + image generation toolkit, and it's already sitting at #1 on the Artificial Analysis Video Arena for both Text-to-Video AND Image-to-Video. It's beating: ● Google's Veo 3.1 & Veo 3 ● OpenAI's Sora 2 ● Runway Gen-4.5 ● Kling 2.5 Turbo The Numbers Don't Lie: ● 64.1% win rate against Runway Aleph in blind human evaluations ● 57% win rate against Kling o1 ● Best-in-class latency. Sub-20 second generation for 720p, 8-second videos. (up to 15-second video) ● Native audio generation baked right into video output (dialogue, music, sound effects, all synced) What Makes It Different It's built for real creative workflows: ✅ Text-to-video AND image-to-video in one API ✅ Video editing with prompt-based controls (add/remove objects, restyle scenes) ✅ Camera controls: zoom, pan, timelapse, pull-back ✅ Style transfers: cyberpunk, watercolor, anime, you name it ✅ Performance animation: map your movements onto characters ✅ Native audio-video sync (no post-production needed) Why the focus on speed and cost? The partner feedback that shaped this: "Quality alone isn't enough if latency and cost make iteration painful." So xAI optimized for all three. Speed. Cost. Quality. Already Integrated With: ● fal. ai ● ComfyUI ● InVideo ● Flora ● HeyGen xAI went from underdog to chart-topper. The Grok Imagine API is fast, affordable, and genuinely production-ready. If you're building anything with AI video, this just became the one to beat.

xAI isn't playing around. They just released the Grok Imagine API, a unified video + image generation toolkit, and it's already sitting at #1 on the Artificial Analysis Video Arena for both Text-to-Video AND Image-to-Video. It's beating: ● Google's Veo 3.1 & Veo 3 ● OpenAI's Sora 2 ● Runway Gen-4.5 ● Kling 2.5 Turbo The Numbers Don't Lie: ● 64.1% win rate against Runway Aleph in blind human evaluations ● 57% win rate against Kling o1 ● Best-in-class latency. Sub-20 second generation for 720p, 8-second videos. (up to 15-second video) ● Native audio generation baked right into video output (dialogue, music, sound effects, all synced) What Makes It Different It's built for real creative workflows: ✅ Text-to-video AND image-to-video in one API ✅ Video editing with prompt-based controls (add/remove objects, restyle scenes) ✅ Camera controls: zoom, pan, timelapse, pull-back ✅ Style transfers: cyberpunk, watercolor, anime, you name it ✅ Performance animation: map your movements onto characters ✅ Native audio-video sync (no post-production needed) Why the focus on speed and cost? The partner feedback that shaped this: "Quality alone isn't enough if latency and cost make iteration painful." So xAI optimized for all three. Speed. Cost. Quality. Already Integrated With: ● fal. ai ● ComfyUI ● InVideo ● Flora ● HeyGen xAI went from underdog to chart-topper. The Grok Imagine API is fast, affordable, and genuinely production-ready. If you're building anything with AI video, this just became the one to beat.

tetsuo

18,325 просмотров • 7 месяцев назад

Introducing Pods Hyperspace Pods lets a small group of people - a family, a startup, a few friends, to pool their laptops and desktops into one AI cluster. Everyone installs the CLI, someone creates a pod, shares an invite link, and the machines form a mesh. Models like Qwen 3.5 32B or GLM-5 Turbo that need more memory than any single laptop has get automatically sharded across the group's devices - layers split proportionally, inference pipelined through the ring. From the outside it looks like one OpenAI-compatible API endpoint with a pk_* key that drops straight into your AI tools and products. No configuration beyond pasting the key and changing the base URL. A team of five paying for cloud AI burns $500–2,000 a month on API calls. The same team's existing machines can serve Qwen 3.5 (competitive on SWE-bench) and GLM-5 Turbo (#1 on BrowseComp for tool-calling and web research) for free - the hardware is already on their desks. When a query genuinely needs a frontier model nobody has locally, the pod falls back to cloud at wholesale rates from a shared treasury. But for the daily work - code reviews, refactors, research, drafting - local models handle it and nobody gets billed. And when it is idle, you can rent out your pod on the compute marketplace, with fine-grained permissions for access management. There's no central server involved in inference. Prompts go from your machine to your pod members' machines and back: all of this enabled by the fully peer-to-peer Hyperspace network. Pod state - who's a member, which API keys are valid, how much treasury is left - is replicated across members with consensus, so the whole thing works on a local network. Members behind home routers don't need port forwarding either. The practical setup for most pods is three models covering different jobs: Qwen 3.5 32B for code and reasoning, GLM-5 Turbo for browsing and research, Gemma 4 for fast lightweight tasks. All running on hardware you already own. Pods ship today in Hyperspace v5.19. Model sharding, API keys, treasury, and Raft coordinator are all live. What Makes This Different - No middleman. Your prompts travel from your IDE to your pod members' hardware and back. There is no server in between reading your data. - No vendor lock-in. Pod membership, API keys, and treasury are replicated across your own machines using Raft consensus. If the internet goes down, your local network keeps working. There is no database in someone else's cloud that your pod depends on. - Automatic sharding. You don't configure layer ranges or calculate VRAM budgets. Tell the pod which model you want. It figures out how to split it across whatever hardware is online. - Real NAT traversal. Your friend behind a home router with a dynamic IP? Works. No VPN, no Tailscale, no port forwarding. The nodes handle it. - Free when local. This is the part that matters most. Cloud AI bills scale with usage. Pod inference on local hardware scales with nothing. The marginal cost of your 10,000th prompt is the electricity your laptop was already using. Coming soon: - Pod federation: pods form alliances with other pods. - Marketplace: pods with spare capacity can sell inference to other pods.

Introducing Pods Hyperspace Pods lets a small group of people - a family, a startup, a few friends, to pool their laptops and desktops into one AI cluster. Everyone installs the CLI, someone creates a pod, shares an invite link, and the machines form a mesh. Models like Qwen 3.5 32B or GLM-5 Turbo that need more memory than any single laptop has get automatically sharded across the group's devices - layers split proportionally, inference pipelined through the ring. From the outside it looks like one OpenAI-compatible API endpoint with a pk_* key that drops straight into your AI tools and products. No configuration beyond pasting the key and changing the base URL. A team of five paying for cloud AI burns $500–2,000 a month on API calls. The same team's existing machines can serve Qwen 3.5 (competitive on SWE-bench) and GLM-5 Turbo (#1 on BrowseComp for tool-calling and web research) for free - the hardware is already on their desks. When a query genuinely needs a frontier model nobody has locally, the pod falls back to cloud at wholesale rates from a shared treasury. But for the daily work - code reviews, refactors, research, drafting - local models handle it and nobody gets billed. And when it is idle, you can rent out your pod on the compute marketplace, with fine-grained permissions for access management. There's no central server involved in inference. Prompts go from your machine to your pod members' machines and back: all of this enabled by the fully peer-to-peer Hyperspace network. Pod state - who's a member, which API keys are valid, how much treasury is left - is replicated across members with consensus, so the whole thing works on a local network. Members behind home routers don't need port forwarding either. The practical setup for most pods is three models covering different jobs: Qwen 3.5 32B for code and reasoning, GLM-5 Turbo for browsing and research, Gemma 4 for fast lightweight tasks. All running on hardware you already own. Pods ship today in Hyperspace v5.19. Model sharding, API keys, treasury, and Raft coordinator are all live. What Makes This Different - No middleman. Your prompts travel from your IDE to your pod members' hardware and back. There is no server in between reading your data. - No vendor lock-in. Pod membership, API keys, and treasury are replicated across your own machines using Raft consensus. If the internet goes down, your local network keeps working. There is no database in someone else's cloud that your pod depends on. - Automatic sharding. You don't configure layer ranges or calculate VRAM budgets. Tell the pod which model you want. It figures out how to split it across whatever hardware is online. - Real NAT traversal. Your friend behind a home router with a dynamic IP? Works. No VPN, no Tailscale, no port forwarding. The nodes handle it. - Free when local. This is the part that matters most. Cloud AI bills scale with usage. Pod inference on local hardware scales with nothing. The marginal cost of your 10,000th prompt is the electricity your laptop was already using. Coming soon: - Pod federation: pods form alliances with other pods. - Marketplace: pods with spare capacity can sell inference to other pods.

Varun

309,786 просмотров • 5 месяцев назад

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

Oren Melamed

29,555 просмотров • 8 месяцев назад

Started using React Native two days ago and immediately fell down a tab-bar rabbit hole. I’d seen Instagram and Revolut collapse their tab bars on scroll while keeping every icon visible. I wanted that without giving up real iOS Liquid Glass. Turns out iOS 26’s public API can’t express that state. UITabBarMinimizeBehavior is an enum of when, not what. With onScrollDown, UIKit minimizes the bar to the active tab alone. There’s no parameter controlling what survives. So most implementations rebuild the visible bar as a custom component. Some use genuine glass materials, but the real UITabBar is gone and with it, the native selection capsule: that little blob that moves like a drop of water between tabs. You can reproduce it with separate springs on the leading and trailing edges. I didn’t want a reproduction. I wanted UIKit’s. Then I remembered a Flutter app i built some months back which uses cupertino_native. Flutter runs the app while a platform-view bridge renders a real UIKit UITabBar. Finding expo-glass-tabs clarified the compact geometry I wanted. The two ideas clicked: why not bridge a real UITabBar into React Native? Here’s the trick: a standalone UITabBar has no UITabBarController managing it, so Apple’s minimization rule never applies. That means I can control its frame and items myself. Expo Router still owns navigation and screen lifecycle. React Native detects scroll direction. Swift removes and restores the real item labels, recentres the icons and animates the native bar’s size. All five icons remain visible. The result keeps Apple’s Liquid Glass, water-drop capsule, hit testing and accessibility, while adding a compact state its public API doesn’t provide. One gotcha tho: detaching the bar means reimplementing everything the controller previously gave you for free. Active-tab reselect scrolling was one example

Started using React Native two days ago and immediately fell down a tab-bar rabbit hole. I’d seen Instagram and Revolut collapse their tab bars on scroll while keeping every icon visible. I wanted that without giving up real iOS Liquid Glass. Turns out iOS 26’s public API can’t express that state. UITabBarMinimizeBehavior is an enum of when, not what. With onScrollDown, UIKit minimizes the bar to the active tab alone. There’s no parameter controlling what survives. So most implementations rebuild the visible bar as a custom component. Some use genuine glass materials, but the real UITabBar is gone and with it, the native selection capsule: that little blob that moves like a drop of water between tabs. You can reproduce it with separate springs on the leading and trailing edges. I didn’t want a reproduction. I wanted UIKit’s. Then I remembered a Flutter app i built some months back which uses cupertino_native. Flutter runs the app while a platform-view bridge renders a real UIKit UITabBar. Finding expo-glass-tabs clarified the compact geometry I wanted. The two ideas clicked: why not bridge a real UITabBar into React Native? Here’s the trick: a standalone UITabBar has no UITabBarController managing it, so Apple’s minimization rule never applies. That means I can control its frame and items myself. Expo Router still owns navigation and screen lifecycle. React Native detects scroll direction. Swift removes and restores the real item labels, recentres the icons and animates the native bar’s size. All five icons remain visible. The result keeps Apple’s Liquid Glass, water-drop capsule, hit testing and accessibility, while adding a compact state its public API doesn’t provide. One gotcha tho: detaching the bar means reimplementing everything the controller previously gave you for free. Active-tab reselect scrolling was one example

kelvin.dart

67,945 просмотров • 1 месяц назад

I’ve been craving a video editor with motion baked in, designed to work with my own AI agents. Claude, Codex, whatever I want to use. I don’t want to be blocked by someone else’s credit system for every little interaction. I also wanted a Figma-like canvas/editor for when I want to jump in and tweak any little detail. So we built it: Video & audio editing: cut, zoom, speed up, add B-roll. Motion, animation, 3D, custom shaders & effects, custom 3D models, dynamic components & templates, audio and beat matching. And it’s all programmable. Design your own assets directly on the canvas, bring them in from Figma or the web, or just let the agent find them, mock them up, or record what it needs automatically. You can even drop in your screen recordings and just let loose. Supercut users: yes, it’ll have first-class support for your recordings, but it’ll work with anything. I’m going to be dropping a lot more examples and tutorials, so follow along. DM me for early access if you’re willing to give feedback. We’ll open it up to everyone very soon.

I’ve been craving a video editor with motion baked in, designed to work with my own AI agents. Claude, Codex, whatever I want to use. I don’t want to be blocked by someone else’s credit system for every little interaction. I also wanted a Figma-like canvas/editor for when I want to jump in and tweak any little detail. So we built it: Video & audio editing: cut, zoom, speed up, add B-roll. Motion, animation, 3D, custom shaders & effects, custom 3D models, dynamic components & templates, audio and beat matching. And it’s all programmable. Design your own assets directly on the canvas, bring them in from Figma or the web, or just let the agent find them, mock them up, or record what it needs automatically. You can even drop in your screen recordings and just let loose. Supercut users: yes, it’ll have first-class support for your recordings, but it’ll work with anything. I’m going to be dropping a lot more examples and tutorials, so follow along. DM me for early access if you’re willing to give feedback. We’ll open it up to everyone very soon.

Neil

23,042 просмотров • 1 месяц назад

THE FALL OF THE FORTRESS 💥 where war ends and a new king rises from the ashes of silence. I generate this through Seedance 2.0 on Yapper Prompt : “THE FALL OF THE FORTRESS” — 15s Ultra-Cinematic Hollywood AI Video Prompt Style: Hyper-realistic Hollywood action • IMAX scale • Unreal Engine 5 quality • cinematic VFX • realistic physics • ultra-detailed facial animation • volumetric smoke • dynamic lighting • smooth motion control • practical explosions mixed with CGI • grounded realism • no cartoon feeling • intense cinematic sound design --- 0:00 – 0:03 | THE ARRIVAL Extreme wide aerial shot above a gigantic ancient stone fortress built on a mountain cliff during a stormy sunset. Massive black military helicopters emerge from thick clouds while searchlights cut through the rain and smoke. The main hero stands at the open helicopter door wearing a dark tactical royal armor mixed with modern military gear — long black coat flowing violently in the wind, metallic shoulder armor, glowing insignia on chest, battle scars on face. Camera: cinematic drone orbit + stabilized helicopter tracking shot. Atmosphere: realistic wind physics, rotor wash moving dust and flags naturally, thunder flashes illuminating the fort. Audio: deep cinematic braams, helicopter blades, distant explosions. --- 0:03 – 0:07 | THE ATTACK The helicopters begin aggressive tactical assault on the fortress walls. Heavy machine guns fire realistic tracer rounds toward enemy towers while explosions erupt across stone barricades. The hero jumps from the helicopter using a tactical rope while explosions burst behind him in slow motion. Enemy soldiers fire desperately but the hero walks forward fearlessly through smoke and sparks. Camera transitions: slow-motion close-up of bullet casings falling handheld battlefield tracking shots cinematic whip-pans during explosions realistic motion blur and debris simulation VFX: ultra-realistic fire, smoke simulation, particle destruction, cinematic sparks, physically accurate lighting reflections on armor. --- 0:07 – 0:10 | THE SURRENDER The hero lands inside the fort courtyard. Enemy soldiers slowly stop firing. One by one, they kneel and throw down their weapons. Rain falls softly through burning smoke while the hero walks through the defeated army with absolute dominance. His boots echo on wet stone ground. Camera: low-angle hero shot with subtle shake for realism. Lighting: orange fire glow mixed with cold blue storm light creating dramatic contrast. Facial animation must feel emotionally real and photorealistic. --- 0:10 – 0:15 | THE NEW KING Massive throne room inside the fortress. Ancient royal hall with burning torches, shattered banners, cinematic dust particles floating through light beams. The hero slowly sits on the gigantic king’s throne. A royal crown is placed on his head while defeated enemies bow before him. Silence fills the hall. Extreme cinematic close-up on his eyes. Camera slowly pushes inward. He says in a deep powerful voice: “A new era begins from here.” Final shot: The throne hall darkens while golden light rises behind him like a rebirth. His cape moves slowly in the wind as the camera pulls back to reveal the conquered kingdom. --- Cinematic Technical Details Unreal Engine 5 photorealism IMAX cinematic framing realistic skin texture and micro-expressions perfect lip-sync smooth cinematic motion control practical war cinematography volumetric fog and smoke ray-traced lighting and reflections Hollywood-grade color grading physically accurate explosions and destruction zero fake animation feeling realistic crowd behavior and enemy reactions ultra-detailed environmental destruction epic Hans Zimmer–style cinematic soundtrack 24fps cinematic motion with natural shutter blur seamless transitions between scenes emotional realism + blockbuster scale

THE FALL OF THE FORTRESS 💥 where war ends and a new king rises from the ashes of silence. I generate this through Seedance 2.0 on Yapper Prompt : “THE FALL OF THE FORTRESS” — 15s Ultra-Cinematic Hollywood AI Video Prompt Style: Hyper-realistic Hollywood action • IMAX scale • Unreal Engine 5 quality • cinematic VFX • realistic physics • ultra-detailed facial animation • volumetric smoke • dynamic lighting • smooth motion control • practical explosions mixed with CGI • grounded realism • no cartoon feeling • intense cinematic sound design --- 0:00 – 0:03 | THE ARRIVAL Extreme wide aerial shot above a gigantic ancient stone fortress built on a mountain cliff during a stormy sunset. Massive black military helicopters emerge from thick clouds while searchlights cut through the rain and smoke. The main hero stands at the open helicopter door wearing a dark tactical royal armor mixed with modern military gear — long black coat flowing violently in the wind, metallic shoulder armor, glowing insignia on chest, battle scars on face. Camera: cinematic drone orbit + stabilized helicopter tracking shot. Atmosphere: realistic wind physics, rotor wash moving dust and flags naturally, thunder flashes illuminating the fort. Audio: deep cinematic braams, helicopter blades, distant explosions. --- 0:03 – 0:07 | THE ATTACK The helicopters begin aggressive tactical assault on the fortress walls. Heavy machine guns fire realistic tracer rounds toward enemy towers while explosions erupt across stone barricades. The hero jumps from the helicopter using a tactical rope while explosions burst behind him in slow motion. Enemy soldiers fire desperately but the hero walks forward fearlessly through smoke and sparks. Camera transitions: slow-motion close-up of bullet casings falling handheld battlefield tracking shots cinematic whip-pans during explosions realistic motion blur and debris simulation VFX: ultra-realistic fire, smoke simulation, particle destruction, cinematic sparks, physically accurate lighting reflections on armor. --- 0:07 – 0:10 | THE SURRENDER The hero lands inside the fort courtyard. Enemy soldiers slowly stop firing. One by one, they kneel and throw down their weapons. Rain falls softly through burning smoke while the hero walks through the defeated army with absolute dominance. His boots echo on wet stone ground. Camera: low-angle hero shot with subtle shake for realism. Lighting: orange fire glow mixed with cold blue storm light creating dramatic contrast. Facial animation must feel emotionally real and photorealistic. --- 0:10 – 0:15 | THE NEW KING Massive throne room inside the fortress. Ancient royal hall with burning torches, shattered banners, cinematic dust particles floating through light beams. The hero slowly sits on the gigantic king’s throne. A royal crown is placed on his head while defeated enemies bow before him. Silence fills the hall. Extreme cinematic close-up on his eyes. Camera slowly pushes inward. He says in a deep powerful voice: “A new era begins from here.” Final shot: The throne hall darkens while golden light rises behind him like a rebirth. His cape moves slowly in the wind as the camera pulls back to reveal the conquered kingdom. --- Cinematic Technical Details Unreal Engine 5 photorealism IMAX cinematic framing realistic skin texture and micro-expressions perfect lip-sync smooth cinematic motion control practical war cinematography volumetric fog and smoke ray-traced lighting and reflections Hollywood-grade color grading physically accurate explosions and destruction zero fake animation feeling realistic crowd behavior and enemy reactions ultra-detailed environmental destruction epic Hans Zimmer–style cinematic soundtrack 24fps cinematic motion with natural shutter blur seamless transitions between scenes emotional realism + blockbuster scale

Ai Arainz

13,885 просмотров • 4 месяцев назад

Want to accept #Bitcoin payments? 🟠 Here are the 2⃣1⃣ best solutions:👇 1) Flash no KYC, fully self-custodial, lots of features. LN only, on-chain to follow. 2) BTCPay Server the bitcoin standard of payment processing, you can do anything with it, even build your own exchange. 3) OpenNode ⚡️ reliable and long track record but requires KYB. LN+Onchain. 4) Zaprite (₿/⚡) focused on merchants, combining reporting, fiat AND bitcoin payment options 5) 🇨🇭 Swiss Bitcoin Pay swiss-made quality, made for merchants, just 0.21% fee in the first year 6) Bitcoinize POS Machine ⚡ the portable handheld that can run ANY POS app, seen in many circular economies around the world 7) OPAGO innovation made in Germany, micro handheld POS LN only 8) Blink Wallet only requires a phone number and ready to accept btc on-chain and over LN with a mobile POS 9) Wallet of Satoshi provides a separate POS app to easily accept payments 10) IBEX Pay ⚡️ bitcoin lightning payments and fiat conversion 11) ForumPay bitcoin payments for dynamic markets and large enterprise 12) @lightningpaynz hosted payment solution to take payments online 13) LNbits LEGO for Lightning, build anything from paywalls, event ticket shops or POS 14) STRIKE their API allows to build many different payment solutions incl Shopify, requires KYB 15) Coincharge - Accept Bitcoin and Lightning Payments accept bitcoin and lightning online or in a physical shop 16) @lipa_btc Accept bitcoin and exchange into your currency (EUR, CHF) for 0.98% fee 17) tiankii ⚡️Technology A merchant dashboard helping people to unleash the power of Bitcoin and Lightning 18) Alby 🐝 easy paywalls and donation widgets for any website 19) Speed ⚡ Bitcoin lightning payment platform Seamless Bitcoin and stablecoin payments for businesses, LNURL support, API & SDK 20) SatSale, a simple, easily deployable, lightweight Bitcoin payment processor that connects to your own node or Lightning network node 21) PayPal LOL, no don't use that or BitPay unless you love KYC/KYB and high fees Have we missed anyone? Let us know! 💬 Enjoyed this list? Share and like ♻️🧡

Want to accept #Bitcoin payments? 🟠 Here are the 2⃣1⃣ best solutions:👇 1) Flash no KYC, fully self-custodial, lots of features. LN only, on-chain to follow. 2) BTCPay Server the bitcoin standard of payment processing, you can do anything with it, even build your own exchange. 3) OpenNode ⚡️ reliable and long track record but requires KYB. LN+Onchain. 4) Zaprite (₿/⚡) focused on merchants, combining reporting, fiat AND bitcoin payment options 5) 🇨🇭 Swiss Bitcoin Pay swiss-made quality, made for merchants, just 0.21% fee in the first year 6) Bitcoinize POS Machine ⚡ the portable handheld that can run ANY POS app, seen in many circular economies around the world 7) OPAGO innovation made in Germany, micro handheld POS LN only 8) Blink Wallet only requires a phone number and ready to accept btc on-chain and over LN with a mobile POS 9) Wallet of Satoshi provides a separate POS app to easily accept payments 10) IBEX Pay ⚡️ bitcoin lightning payments and fiat conversion 11) ForumPay bitcoin payments for dynamic markets and large enterprise 12) @lightningpaynz hosted payment solution to take payments online 13) LNbits LEGO for Lightning, build anything from paywalls, event ticket shops or POS 14) STRIKE their API allows to build many different payment solutions incl Shopify, requires KYB 15) Coincharge - Accept Bitcoin and Lightning Payments accept bitcoin and lightning online or in a physical shop 16) @lipa_btc Accept bitcoin and exchange into your currency (EUR, CHF) for 0.98% fee 17) tiankii ⚡️Technology A merchant dashboard helping people to unleash the power of Bitcoin and Lightning 18) Alby 🐝 easy paywalls and donation widgets for any website 19) Speed ⚡ Bitcoin lightning payment platform Seamless Bitcoin and stablecoin payments for businesses, LNURL support, API & SDK 20) SatSale, a simple, easily deployable, lightweight Bitcoin payment processor that connects to your own node or Lightning network node 21) PayPal LOL, no don't use that or BitPay unless you love KYC/KYB and high fees Have we missed anyone? Let us know! 💬 Enjoyed this list? Share and like ♻️🧡

Lightning News

37,598 просмотров • 1 год назад

Introducing a new tool called "SideChannel". A secure alternative to OpenClaw. Utilizes signal for communication and has Claude integration. I built SideChannel, an open-source Signal bot that connects Claude AI to your entire development workflow. End-to-end encrypted. From your pocket. The real power is autonomous development. Send one message like "Build a REST API with auth, pagination, and tests" and SideChannel will: - Generate a full PRD with stories and atomic tasks. - Dispatch up to 10 parallel workers (each running Claude). - Independently verify every task with a separate Claude context. - Run quality gates to catch regressions - Auto-fix failures. - Send you progress updates via Signal as work completes. Every piece of code is reviewed by a separate AI context using a fail-closed security model. If it detects security issues, backdoors, or logic errors — the code gets rejected automatically. No rubber stamps. It also has memory that actually works. Conversations are stored with vector embeddings for semantic search. Claude remembers your project conventions, past decisions, and what's been tried before. It gets smarter about your codebase over time. Other things I'm proud of: - Plugin framework for extending with custom commands. - Multi-project support with per-user scoping. - Rate limiting, path validation, phone allowlist. - Git checkpoints before every task, atomic commits after. - Stale task recovery, circular dependency detection. - Works on Linux and macOS, one-command install. It also integrates into OpenAI or Grok (optional) for more Generative AI response for simple things like "Whats the weather in New York City right now?".

Introducing a new tool called "SideChannel". A secure alternative to OpenClaw. Utilizes signal for communication and has Claude integration. I built SideChannel, an open-source Signal bot that connects Claude AI to your entire development workflow. End-to-end encrypted. From your pocket. The real power is autonomous development. Send one message like "Build a REST API with auth, pagination, and tests" and SideChannel will: - Generate a full PRD with stories and atomic tasks. - Dispatch up to 10 parallel workers (each running Claude). - Independently verify every task with a separate Claude context. - Run quality gates to catch regressions - Auto-fix failures. - Send you progress updates via Signal as work completes. Every piece of code is reviewed by a separate AI context using a fail-closed security model. If it detects security issues, backdoors, or logic errors — the code gets rejected automatically. No rubber stamps. It also has memory that actually works. Conversations are stored with vector embeddings for semantic search. Claude remembers your project conventions, past decisions, and what's been tried before. It gets smarter about your codebase over time. Other things I'm proud of: - Plugin framework for extending with custom commands. - Multi-project support with per-user scoping. - Rate limiting, path validation, phone allowlist. - Git checkpoints before every task, atomic commits after. - Stale task recovery, circular dependency detection. - Works on Linux and macOS, one-command install. It also integrates into OpenAI or Grok (optional) for more Generative AI response for simple things like "Whats the weather in New York City right now?".

Dave Kennedy

49,572 просмотров • 7 месяцев назад

🪴 GT Protocol Monthly Recap: May 2026 May focused on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.

🪴 GT Protocol Monthly Recap: May 2026 May focused on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.

GT Protocol

32,904 просмотров • 3 месяцев назад

Seedance V2 This used to take people month of study and practice on Adobe Flash, now it can be done with Seedance V2, not perfect but this is the worst it will be. 15 seconds, stylized 2D hand-drawn animation, overhead battlefield on aged yellow lined notebook paper, clear blue horizontal ruled lines and a red left margin line always visible, fine paper grain, pencil marks, ink strokes, minimal classroom-material aesthetic at the start. The entire video must preserve the same paper world from start to finish. No live action, no 3D rendering, no realistic human faces, no modern objects, no narration, no subtitles. Core concept: A childish classroom doodle of an ancient war gradually transforms into a legendary illustrated battlefield, then collapses back into scribbles after the climax. The escalation must feel smooth, intentional, and visually magical, as if imagination is taking over the page. Army design: Two opposing ancient armies drawn first as simple colored stick figures, one faction in red, one faction in blue. Dense infantry blocks with spears and swords, cavalry units with long lances, banner carriers, archers. At first they are crude doodles with simple line limbs and circular heads. As the battle intensifies, they evolve step by step into more detailed inked warriors with clearer armor silhouettes, horses, weapons, helmets, capes, and expressive movement, but still remain inside a hand-drawn 2D illustrated style on paper. Visual progression and timing: 0-3 seconds: Wide top-down view of a large notebook-paper battlefield. Rough stick-figure armies face each other across the page. The drawing feels playful and simple at first. The camera slowly glides forward over the paper as both sides begin charging. Tiny horses gallop, infantry rushes, arrows are sketched into existence and start falling. Everything still looks like rough schoolbook doodles. 3-7 seconds: The first major collision. Spears thrust, swords swing, cavalry crashes into cavalry, formations break apart. With each impact, the art style upgrades. Simple stick limbs become stronger ink lines, bodies gain armor shapes, horses gain muscular form, banners gain flowing detail, shadows and dust marks appear. The battlefield becomes denser, faster, more dramatic. Red and blue strokes smear across the page with the force of combat. 7-11 seconds: The battle reaches full transformation. The once-crude doodles are now a glorious hand-illustrated ancient war scene, still clearly drawn on notebook paper but far more detailed and cinematic. The camera pushes into a central duel between two opposing generals on horseback. Their weapons clash with a powerful burst of ink lines and paper tremor. Around them, infantry and cavalry continue fighting in layered motion, arrows rain down, fallen soldiers scatter across the ruled lines. 11-15 seconds: At the peak of the duel, one final strike lands. A shockwave ripples through the page. The detailed warriors, horses, banners, and battle effects suddenly break apart into loose pencil scribbles, sketch fragments, and drifting paper-line debris. The great war rapidly collapses back into childish rough doodles, then into scattered marks and unfinished lines, as if the imagination has burned out. End on the overhead notebook page with the battlefield reduced to messy hand-drawn remnants. Animation and motion: Smooth fluid motion, strong timing, readable silhouettes, at least 24fps feel. The escalation from crude doodle to epic illustrated warfare must be gradual and continuous, not abrupt. Impacts should feel sharp and rhythmic. Keep all action legible from overhead. Maintain strong contrast between the innocent notebook-paper setting and the seriousness of the war. Atmosphere: Starts playful and curious, grows intense and heroic, peaks as a mythic battlefield, then ends with a strange quiet after the collapse. The whole piece should feel like a child’s imagination turning into an epic war vision on paper.

Seedance V2 This used to take people month of study and practice on Adobe Flash, now it can be done with Seedance V2, not perfect but this is the worst it will be. 15 seconds, stylized 2D hand-drawn animation, overhead battlefield on aged yellow lined notebook paper, clear blue horizontal ruled lines and a red left margin line always visible, fine paper grain, pencil marks, ink strokes, minimal classroom-material aesthetic at the start. The entire video must preserve the same paper world from start to finish. No live action, no 3D rendering, no realistic human faces, no modern objects, no narration, no subtitles. Core concept: A childish classroom doodle of an ancient war gradually transforms into a legendary illustrated battlefield, then collapses back into scribbles after the climax. The escalation must feel smooth, intentional, and visually magical, as if imagination is taking over the page. Army design: Two opposing ancient armies drawn first as simple colored stick figures, one faction in red, one faction in blue. Dense infantry blocks with spears and swords, cavalry units with long lances, banner carriers, archers. At first they are crude doodles with simple line limbs and circular heads. As the battle intensifies, they evolve step by step into more detailed inked warriors with clearer armor silhouettes, horses, weapons, helmets, capes, and expressive movement, but still remain inside a hand-drawn 2D illustrated style on paper. Visual progression and timing: 0-3 seconds: Wide top-down view of a large notebook-paper battlefield. Rough stick-figure armies face each other across the page. The drawing feels playful and simple at first. The camera slowly glides forward over the paper as both sides begin charging. Tiny horses gallop, infantry rushes, arrows are sketched into existence and start falling. Everything still looks like rough schoolbook doodles. 3-7 seconds: The first major collision. Spears thrust, swords swing, cavalry crashes into cavalry, formations break apart. With each impact, the art style upgrades. Simple stick limbs become stronger ink lines, bodies gain armor shapes, horses gain muscular form, banners gain flowing detail, shadows and dust marks appear. The battlefield becomes denser, faster, more dramatic. Red and blue strokes smear across the page with the force of combat. 7-11 seconds: The battle reaches full transformation. The once-crude doodles are now a glorious hand-illustrated ancient war scene, still clearly drawn on notebook paper but far more detailed and cinematic. The camera pushes into a central duel between two opposing generals on horseback. Their weapons clash with a powerful burst of ink lines and paper tremor. Around them, infantry and cavalry continue fighting in layered motion, arrows rain down, fallen soldiers scatter across the ruled lines. 11-15 seconds: At the peak of the duel, one final strike lands. A shockwave ripples through the page. The detailed warriors, horses, banners, and battle effects suddenly break apart into loose pencil scribbles, sketch fragments, and drifting paper-line debris. The great war rapidly collapses back into childish rough doodles, then into scattered marks and unfinished lines, as if the imagination has burned out. End on the overhead notebook page with the battlefield reduced to messy hand-drawn remnants. Animation and motion: Smooth fluid motion, strong timing, readable silhouettes, at least 24fps feel. The escalation from crude doodle to epic illustrated warfare must be gradual and continuous, not abrupt. Impacts should feel sharp and rhythmic. Keep all action legible from overhead. Maintain strong contrast between the innocent notebook-paper setting and the seriousness of the war. Atmosphere: Starts playful and curious, grows intense and heroic, peaks as a mythic battlefield, then ends with a strange quiet after the collapse. The whole piece should feel like a child’s imagination turning into an epic war vision on paper.

Emily

35,023 просмотров • 5 месяцев назад

I just built a Claude skill that writes 20 Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)

I just built a Claude skill that writes 20 Meta ad hooks in 60 seconds 🤯 Give it your product, your audience, and your best-performing angles → it writes hooks across 10 proven frameworks, each one targeted at a specific customer pain point. All inside Claude Cowork. Perfect for DTC brands and agencies who are still writing hooks from scratch every time they need new creative — staring at a blank doc, scrolling competitors for inspiration, and recycling the same 3 angles because you ran out of ideas two weeks ago. If you're launching Meta Ads and your hook writing process looks like this — open a Google Doc, try to remember what worked last time, write 5 hooks that all sound the same, run them, 4 flop, go back to the doc, repeat ... This skill replaces the entire process: → You give it your product name, key benefits, and target customer → It writes hooks across 10 frameworks: problem-solution, curiosity gap, bold claim, social proof, before/after, us vs them, question, contrarian, urgency, and storytelling → Each hook targets a specific pain point — not generic "Shop now" copy → Generates 2 variations per framework so you have options to test → Outputs everything organized by framework with notes on when to use each one → Takes about 60 seconds No blank page. No recycling the same 3 angles. No writing 5 hooks that all sound like the same ad. What you get: → 20 hooks across 10 proven frameworks, ready to drop into your ads → Each hook written for a specific customer pain point, not a generic audience → Framework labels so you know which hook type you're testing → A reusable skill — run it for every new product, every new campaign, every new angle sprint → Works from a product brief — no API connection, no CSV export, no setup beyond installing the skill One product brief. 20 hooks. 60 seconds. I put together the full skill file plus a playbook showing how to install it, customize the frameworks, and run your first hook sprint. Want it for free? > Like this post > Comment "HOOKS" And I'll send it over (must be following so I can DM)

Mike Futia

17,026 просмотров • 5 месяцев назад