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Dear frontend devs and UI designers. I bring you Liquid DOM, a complete and faithful implementation of Liquid Glass on the Web. - Shape morphing - All properties animatable - Dynamic refraction and reflection - Adaptive tint - Adaptive specular highlight - Dispersion - Full html integration - Super...

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Andrew Prifer

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1,356,575 Aufrufe • vor 3 Monaten •via X (Twitter)

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Exciting Update: The freshly redesigned Reactor and our new website are here! What's new: - Upgraded Reactor & Website UI with New Design - Focused Matrix Pages (MVP on the way🤫) - More Sections for B2B Opportunities (get in contact for Reactor API access or Reactor ($ARC on Virtuals) integration) We’re putting the finishing touches on a few features and pages, which will be fully publicly available in the next couple of days. With this update, including the Reactor enhancement and Matrix development, we expect new opportunities and high-level collaborations coming our way in the next months.🤝 Head over to and and test yourself! For more updates, follow ARC and our CEO Tj Dunham.

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LLM Wikis + HTML Artifacts are insanely powerful. You should seriously consider this in your workflows. LLM Wikis captures all the important information that lets you and your agents do meaningful work. HTML artifacts present that information in interesting ways that allow you to take important actions along with your agents. My HTML artifacts sit on top of my LLM wikis. They are dynamic and are easily extended as needs arise. I have hooked my Artifacts to talk to my agents, and similarly, the agents can talk to artifacts. This has allowed me to build powerful artifacts that reduce my inbox to zero, keep me updated on any topic of interest, fast prototyping, do deep research, design/trigger new experiments, generate figures to improve understanding, schedule research, search relevant information, discover topics, and so much more. What you see in the clip is not a website. It's a simple interactive HTML artifact. HTML artifacts are useful for designers, engineers, researchers, students, and anyone working with agents. Lastly, HTML doesn't replace Markdown. They are a much better combination working together.
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🚀 I'm launching r3f-webgpu-perf today! "npm i r3f-webgpu-perf" One thing I missed while working with WebGPU in React Three Fiber was a performance monitor similar to r3f-perf. The existing tool is fantastic, but it doesn’t support the WebGPU renderer yet. So I decided to build one. ✅ Supports both WebGL and WebGPU ✅ Modern and customizable UI ✅ Lightweight and easy to integrate ✅ Built specifically for React Three Fiber My goal is to turn r3f-webgpu-perf into more than just a metrics dashboard. I want it to become a learning tool that provides real-time optimization suggestions based on the techniques I’ve developed while building hundreds of interactive 3D projects over the last two decades. A vanilla Three.js version is also planned. If you’re building with Three.js, React Three Fiber, or WebGPU, I’d love for you to try it and share your feedback. ⭐ GitHub: 📦 NPM: Every GitHub star helps make the tool better for the entire community. #threejs #creativecoding #webgpu #r3f
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Meng To

65,691 Aufrufe • vor 7 Monaten

Anthropic's most viral feature is now open-source! Until now, Anthropic's Generative UI capabilities only existed inside its own products. CopilotKit🪁 just shipped Open Generative UI, an open-source implementation of Claude Artifacts that works in any app. The agent generates HTML/SVG at runtime, and CopilotKit streams it token-by-token into a sandboxed iframe inside the app's chat. So the user can watch the UI assemble itself in real time, not after the full response is ready. The sandbox is fully isolated with no access to the parent app, the DOM, or user data. So if the agent hallucinates broken markup or unexpected JavaScript, nothing leaks outside the iframe. Under the hood, the agent does not select from pre-built components. Instead, it generates arbitrary visuals from scratch every time. The output is unconstrained by default, but you can shape it by defining prompt-based skills that teach the agent specific visual formats or guidelines. For instance, a skill prompt can guide the agent toward producing a Chart.js dashboard with proper axis labels and responsive sizing, or an interactive 3D model with rotation controls. The video below shows this in action, and the output quality you see actually comes from the skills layer. Open Generative UI runs on AG-UI, so it works out of the box with LangGraph, CrewAI, Mastra, Google ADK, AWS Strands, and more. It also ships with a standalone MCP server that plugs into Claude Code, Cursor, or any MCP-compatible client. And the entire stack is built on top of CopilotKit, the open-source frontend framework for agents and generative UI. 30k+ GitHub stars, with SDKs for React, Next.js, Angular, and Vue. I have shared the GitHub repo and a live playground in the replies!
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Anthropic's most viral feature is now open-source! Until now, Anthropic's Generative UI capabilities only existed inside its own products. CopilotKit🪁 just shipped Open Generative UI, an open-source implementation of Claude Artifacts that works in any app. The agent generates HTML/SVG at runtime, and CopilotKit streams it token-by-token into a sandboxed iframe inside the app's chat. So the user can watch the UI assemble itself in real time, not after the full response is ready. The sandbox is fully isolated with no access to the parent app, the DOM, or user data. So if the agent hallucinates broken markup or unexpected JavaScript, nothing leaks outside the iframe. Under the hood, the agent does not select from pre-built components. Instead, it generates arbitrary visuals from scratch every time. The output is unconstrained by default, but you can shape it by defining prompt-based skills that teach the agent specific visual formats or guidelines. For instance, a skill prompt can guide the agent toward producing a Chart.js dashboard with proper axis labels and responsive sizing, or an interactive 3D model with rotation controls. The video below shows this in action, and the output quality you see actually comes from the skills layer. Open Generative UI runs on AG-UI, so it works out of the box with LangGraph, CrewAI, Mastra, Google ADK, AWS Strands, and more. It also ships with a standalone MCP server that plugs into Claude Code, Cursor, or any MCP-compatible client. And the entire stack is built on top of CopilotKit, the open-source frontend framework for agents and generative UI. 30k+ GitHub stars, with SDKs for React, Next.js, Angular, and Vue. I have shared the GitHub repo and a live playground in the replies!

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This is no routine AI‑video iteration. One model perceives scene‑level physics rather than simple pixel generation, and that is Seedance Enterprise 2.5. Creators no longer need dozens of rerolls. Most usable footage only demands 1‑2 generations, lowering overall spending and streamlining creation. It delivers AI‑free lifelike visuals, cinematic‑level lighting and camera movement, 30-second single-shot generation to orchestrate complete scene‑wide narratives. Accepts up to 50 reference inputs, so your characters and visual style stay perfectly locked across every single frame. With localized editing, the individual elements can be edited locally without re-rendering the entire video. I’ve been building a full creative pipeline on BytePlus Lumina, chaining Seedance for motion with Seedream for keyframe control and Seedaudio for adaptive soundscapes. It’s no longer about generating clips; it’s about directing scenes. Seedance 2.5 API is about to launch on BytePlus, and now you can try it directly on Lumina.

SANI BULA

174,790 Aufrufe • vor 23 Tagen

Engineers with taste will make a lot of so-called designers irrelevant. It’s 2026. With all the vibe-coding tools we have now, you can build real working prototypes of almost anything in a few hours. So when I see another “iOS 27 concept” that is just a Figma screenshot with a gradient or a circular one, and some fake Liquid Glass layer on top, that’s laziness at the next level for the sake of engagement.
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Engineers with taste will make a lot of so-called designers irrelevant. It’s 2026. With all the vibe-coding tools we have now, you can build real working prototypes of almost anything in a few hours. So when I see another “iOS 27 concept” that is just a Figma screenshot with a gradient or a circular one, and some fake Liquid Glass layer on top, that’s laziness at the next level for the sake of engagement.

Tykra

29,757 Aufrufe • vor 2 Monaten

This is a standard practice for almost all Tier-1 banking applications in Nigeria, and for some fintech applications I’ve previously performed pentests on. Client-side encryption isn’t a total waste, or a waste of compute, as some people have claimed, but rather a measure to protect against API tampering or API request/response manipulation between the client and the server when implemented properly. Even with HTTPS, attackers can capture a decrypted version of web or mobile API data in transit because the browser and the server establish a level of trust during the TLS handshake. Attackers can leverage this trust to capture & proxy already-decrypted traffic, tamper with it, and then forward it to the server. This allows them to override what the user interface or client is originally supposed to send and replace it with data of their choosing. That is why validation needs to be performed on both the client and the server side. To wrap up, encrypting API requests and responses makes it significantly harder for attackers to tamper with data, even if they capture the traffic, unless they have access to the encryption details (algorithm, encryption mode, key size, secret key, and initialization vector), assuming asymmetric encryption is used. In the demo below, you can see how I discovered additional parameters (balance, is_admin) in the API response, captured the registration API request, despite it being sent over HTTPS from the interface, added the discovered parameters, and successfully inflated my balance to 50 billion and also escalated my privileges to admin, and ultimately deleted the accounts of two live users/customers. In the second slide, I captured an API traffic of a bank app, and you can see how difficult the payloads are to read.
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This is a standard practice for almost all Tier-1 banking applications in Nigeria, and for some fintech applications I’ve previously performed pentests on. Client-side encryption isn’t a total waste, or a waste of compute, as some people have claimed, but rather a measure to protect against API tampering or API request/response manipulation between the client and the server when implemented properly. Even with HTTPS, attackers can capture a decrypted version of web or mobile API data in transit because the browser and the server establish a level of trust during the TLS handshake. Attackers can leverage this trust to capture & proxy already-decrypted traffic, tamper with it, and then forward it to the server. This allows them to override what the user interface or client is originally supposed to send and replace it with data of their choosing. That is why validation needs to be performed on both the client and the server side. To wrap up, encrypting API requests and responses makes it significantly harder for attackers to tamper with data, even if they capture the traffic, unless they have access to the encryption details (algorithm, encryption mode, key size, secret key, and initialization vector), assuming asymmetric encryption is used. In the demo below, you can see how I discovered additional parameters (balance, is_admin) in the API response, captured the registration API request, despite it being sent over HTTPS from the interface, added the discovered parameters, and successfully inflated my balance to 50 billion and also escalated my privileges to admin, and ultimately deleted the accounts of two live users/customers. In the second slide, I captured an API traffic of a bank app, and you can see how difficult the payloads are to read.

Ghost St Badmus

217,690 Aufrufe • vor 8 Monaten

Anthropic won't like this open-source repo. It is going to cost LLM providers a lot of money. Every CI run of an AI app today sends real requests to providers like OpenAI or Anthropic. Like any other LLM call, this too gets billed at actual API rates. So for teams with high commit volumes, this accumulates into a meaningful chunk of API spend. One common hack devs use is that instead of invoking the LLM API, the test calls a fake local server that speaks the same API and returns a dummy response. The catch is that the dummy response is a copy of what the provider returned on the day it was saved, and providers keep adding fields and changing types. So the tests keep passing against a schema that's no longer valid, while the real integration breaks in production. A smart approach is now actually implemented in CopilotKit🪁's recently open-sourced aimock project. Every day, the repo's own CI sends a handful of requests to the real API and the same requests to the fake server, then compares both against the official client library's type definitions. Those are the only real API calls in the whole setup, and they run on the repo's own keys, not in anyone else's CI. A single team can push hundreds of commits a day, and thousands of teams are already doing that with coding agents. All of those runs stay offline, because one repo checks against the real API on everyone's behalf. When a check fails, a coding agent updates aimock's built-in response schema, the full test suite has to pass, and a patch version ships to npm. By simply upgrading the package, the corrected schema gets reflected in every project using it. The capability is not just limited to a single provider. The same server works for Claude, OpenAI, Gemini, Bedrock, Azure, Ollama, plus MCP tools, A2A agents, AG-UI event streams, vector DBs like Pinecone and Qdrant, and search, speech, image, and video endpoints. Here's the repo: (don't forget to star it ⭐) That said, mocking your API calls is one thing. AI engineers should also know how to test agents properly in the first place, which several teams still skip. I wrote a full walkthrough on that, covering build, testing, evals, tracing, and deployment. Read it below.
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Anthropic won't like this open-source repo. It is going to cost LLM providers a lot of money. Every CI run of an AI app today sends real requests to providers like OpenAI or Anthropic. Like any other LLM call, this too gets billed at actual API rates. So for teams with high commit volumes, this accumulates into a meaningful chunk of API spend. One common hack devs use is that instead of invoking the LLM API, the test calls a fake local server that speaks the same API and returns a dummy response. The catch is that the dummy response is a copy of what the provider returned on the day it was saved, and providers keep adding fields and changing types. So the tests keep passing against a schema that's no longer valid, while the real integration breaks in production. A smart approach is now actually implemented in CopilotKit🪁's recently open-sourced aimock project. Every day, the repo's own CI sends a handful of requests to the real API and the same requests to the fake server, then compares both against the official client library's type definitions. Those are the only real API calls in the whole setup, and they run on the repo's own keys, not in anyone else's CI. A single team can push hundreds of commits a day, and thousands of teams are already doing that with coding agents. All of those runs stay offline, because one repo checks against the real API on everyone's behalf. When a check fails, a coding agent updates aimock's built-in response schema, the full test suite has to pass, and a patch version ships to npm. By simply upgrading the package, the corrected schema gets reflected in every project using it. The capability is not just limited to a single provider. The same server works for Claude, OpenAI, Gemini, Bedrock, Azure, Ollama, plus MCP tools, A2A agents, AG-UI event streams, vector DBs like Pinecone and Qdrant, and search, speech, image, and video endpoints. Here's the repo: (don't forget to star it ⭐) That said, mocking your API calls is one thing. AI engineers should also know how to test agents properly in the first place, which several teams still skip. I wrote a full walkthrough on that, covering build, testing, evals, tracing, and deployment. Read it below.

Akshay 🚀

61,794 Aufrufe • vor 12 Tagen

With optimized builds, Hyperfy V1 came very close to matching the look and feel of Unity or other game engines—but in the browser. Few people realized how well it also performed on VR browsers and the level of immersion already possible on the web. Now, with V2, Hyperfy introduces a much more powerful engine and full physics support. The browser remains the most straightforward, frictionless, and accessible way to experience these technologies. This positions Hyperfy perfectly for the upcoming wave of VR, as new devices, technologies, and major companies enter the space. Rick and I are pooling resources and fully committed to helping build this out, bringing everything to the next level. Here I’m jamming with him in V1, with him using the Apple Vision Pro. The apartment you see here is something I built for the upcoming @timeofemergence marketplace. #avp #webXR Three.js
1:00

With optimized builds, Hyperfy V1 came very close to matching the look and feel of Unity or other game engines—but in the browser. Few people realized how well it also performed on VR browsers and the level of immersion already possible on the web. Now, with V2, Hyperfy introduces a much more powerful engine and full physics support. The browser remains the most straightforward, frictionless, and accessible way to experience these technologies. This positions Hyperfy perfectly for the upcoming wave of VR, as new devices, technologies, and major companies enter the space. Rick and I are pooling resources and fully committed to helping build this out, bringing everything to the next level. Here I’m jamming with him in V1, with him using the Apple Vision Pro. The apartment you see here is something I built for the upcoming @timeofemergence marketplace. #avp #webXR Three.js

𝚟𝚘𝚡𝚟𝚒𝚎𝚗𝚗𝚎

23,618 Aufrufe • vor 1 Jahr

Devs are printing $50k-$200k/week on Polymarket Hard truth: You won't hit those numbers on the frontend. The UI lags 10x behind reality. I’ve been a dev for 8+ years. I’m opening a FREE bootcamp to teach you the basics on how to build your first BOT. Why I’m doing this: > Most of you will just bookmark this and never execute. > If you outgrow me, I gain a smarter circle. We all level up The plan (2 weeks bootcamp) : → Learn the Polymarket API basics → Fetch raw data → Build an interpretation engine that executes trades To join: → Join Polymarket via my link: → Deposit $20+ → DM me your TG handle Group will open soon. If you have not been invited yet, you will be asap. (The clip below shows what raw API speed looks like)
0:20

Devs are printing $50k-$200k/week on Polymarket Hard truth: You won't hit those numbers on the frontend. The UI lags 10x behind reality. I’ve been a dev for 8+ years. I’m opening a FREE bootcamp to teach you the basics on how to build your first BOT. Why I’m doing this: > Most of you will just bookmark this and never execute. > If you outgrow me, I gain a smarter circle. We all level up The plan (2 weeks bootcamp) : → Learn the Polymarket API basics → Fetch raw data → Build an interpretation engine that executes trades To join: → Join Polymarket via my link: → Deposit $20+ → DM me your TG handle Group will open soon. If you have not been invited yet, you will be asap. (The clip below shows what raw API speed looks like)

Jayden ⛩️

12,206 Aufrufe • vor 8 Monaten

The web was built for humans. And honestly, that's fine for you guys. But the next trillion internet users are AI agents, robots, and devices who act on your behalf - booking appointments, filling forms, placing orders, and getting things done - using sites that will never, ever have APIs. 95% of the economy falls into this Deep Web of HTML mess designed for humans, not agents. Oh, those generic computer use agents aren't taking you anywhere. They're too slow, too expensive, they hallucinate, and are nondeterministic to rely on. That changes now. This is me, Mino, a web agents API to build on this Deep Web. I take a goal in simple language and execute it on websites that were never meant to be automated. Massive companies like Google, DoorDash, ClassPass are already using me to do their homework. Now it’s your turn. How though? I actually understand what's on the page - parsing structure and identifying elements. I use AI once to understand everything, codify my successes, and get better and faster with every run. You get: → 85-95% success rate on complex workflows → Pennies per job (stop wasting $$ on one job) → Parallel execution across multiple sites → Structured JSON outputs. Every. Single. Time. The web wasn't built for agents. I forced it to work anyway. Go build something real. 50 completed runs on the house:
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The web was built for humans. And honestly, that's fine for you guys. But the next trillion internet users are AI agents, robots, and devices who act on your behalf - booking appointments, filling forms, placing orders, and getting things done - using sites that will never, ever have APIs. 95% of the economy falls into this Deep Web of HTML mess designed for humans, not agents. Oh, those generic computer use agents aren't taking you anywhere. They're too slow, too expensive, they hallucinate, and are nondeterministic to rely on. That changes now. This is me, Mino, a web agents API to build on this Deep Web. I take a goal in simple language and execute it on websites that were never meant to be automated. Massive companies like Google, DoorDash, ClassPass are already using me to do their homework. Now it’s your turn. How though? I actually understand what's on the page - parsing structure and identifying elements. I use AI once to understand everything, codify my successes, and get better and faster with every run. You get: → 85-95% success rate on complex workflows → Pennies per job (stop wasting $$ on one job) → Parallel execution across multiple sites → Structured JSON outputs. Every. Single. Time. The web wasn't built for agents. I forced it to work anyway. Go build something real. 50 completed runs on the house:

TinyFish

656,586 Aufrufe • vor 8 Monaten

Introducing /visual-plan - a skill to generate rich, visual plans for Claude Code and Codex. Plan mode in Claude Code is incredible. But I always find my eyes glazing over when it gives me this huge markdown essay in my terminal. I found I can make much better visual plans with reusable components. So I made a skill called `/visual-plan`. It generates plans as MDX with visual, interactive components. Diagrams, interactive API specs, schema design changes, annotated code, and even pan and zoomable wireframes. So for any UI work, you can look at a wireframe first, comment on it, iterate, and then have the agent work. I’ve found this to be a much more intuitive interface for reasoning about what the agent is doing. It’s somewhat inspired by that popular post about how HTML is better than Markdown. But HTML can be slow and verbose to write. And it doesn’t look good checked into a repo. This has really made me feel like humans and engineering are entering a new abstraction phase, where we reason about things at the plan level. As long as the plan is good, agents are getting more and more reliable at executing on it. Almost to the degree that we trust the C compiler to compile to assembly reliably. Plans are the new intermediate representation. I also made a skill for the reverse of this, called `/visual-recap`. After the agent works, it gives you a recap of everything it did. Same idea: wireframes, interactive API specs and diffs, schemas, annotated code, etc. So now when you’re reviewing what the agent did for you, or looking at a pull request of somebody else’s code, you can see a visual recap instead of just reading a wall of text. It’s all free and open source. You can find it on my GitHub. Will link to it in the reply because we all know how dumb these algorithms are with links.
1:19

Introducing /visual-plan - a skill to generate rich, visual plans for Claude Code and Codex. Plan mode in Claude Code is incredible. But I always find my eyes glazing over when it gives me this huge markdown essay in my terminal. I found I can make much better visual plans with reusable components. So I made a skill called `/visual-plan`. It generates plans as MDX with visual, interactive components. Diagrams, interactive API specs, schema design changes, annotated code, and even pan and zoomable wireframes. So for any UI work, you can look at a wireframe first, comment on it, iterate, and then have the agent work. I’ve found this to be a much more intuitive interface for reasoning about what the agent is doing. It’s somewhat inspired by that popular post about how HTML is better than Markdown. But HTML can be slow and verbose to write. And it doesn’t look good checked into a repo. This has really made me feel like humans and engineering are entering a new abstraction phase, where we reason about things at the plan level. As long as the plan is good, agents are getting more and more reliable at executing on it. Almost to the degree that we trust the C compiler to compile to assembly reliably. Plans are the new intermediate representation. I also made a skill for the reverse of this, called `/visual-recap`. After the agent works, it gives you a recap of everything it did. Same idea: wireframes, interactive API specs and diffs, schemas, annotated code, etc. So now when you’re reviewing what the agent did for you, or looking at a pull request of somebody else’s code, you can see a visual recap instead of just reading a wall of text. It’s all free and open source. You can find it on my GitHub. Will link to it in the reply because we all know how dumb these algorithms are with links.

Steve (Builder.io)

125,646 Aufrufe • vor 2 Monaten

We're preparing for the second playtest of MIGHTREYA! Based on user feedback from the previous test, we've fixed bugs and added new features. We’d love to have your support again—please join us for the next round! To join the playtest, please join our Discord server. A selection of the new features we’ve added -Camera Assist (Hard Lock-On) -Takedown Converted to QTE -Duplicate Move Penalty -Expanded Graphics Options: V-Sync, FPS Cap, AI Upscaling -Enemy Warp Recovery When Stuck in Terrain -Stage Progression Navigation -Boss Guard Gauge Recovery and HP Adjustment -Boss Takedown Implementation -Boss Intro Cutscene -UI Operation Guide -Simplified Command List -Tutorial Level -One-Point Tutorials -Streaming Comment Features: Move Requests, Super Chat Integration -Cut-In Animation for Level 5 Charged Moves -Sub-Attack Motion and Performance Adjustments -Forced Transformation Cancel at Low HP -Option: Toggle PlayStation-Style Button Icons -Score and Result System Finalized: Displays Final Rank -Lock-On Distance Adjustment
1:14

We're preparing for the second playtest of MIGHTREYA! Based on user feedback from the previous test, we've fixed bugs and added new features. We’d love to have your support again—please join us for the next round! To join the playtest, please join our Discord server. A selection of the new features we’ve added -Camera Assist (Hard Lock-On) -Takedown Converted to QTE -Duplicate Move Penalty -Expanded Graphics Options: V-Sync, FPS Cap, AI Upscaling -Enemy Warp Recovery When Stuck in Terrain -Stage Progression Navigation -Boss Guard Gauge Recovery and HP Adjustment -Boss Takedown Implementation -Boss Intro Cutscene -UI Operation Guide -Simplified Command List -Tutorial Level -One-Point Tutorials -Streaming Comment Features: Move Requests, Super Chat Integration -Cut-In Animation for Level 5 Charged Moves -Sub-Attack Motion and Performance Adjustments -Forced Transformation Cancel at Low HP -Option: Toggle PlayStation-Style Button Icons -Score and Result System Finalized: Displays Final Rank -Lock-On Distance Adjustment

Wishlist MIGHTREYA on Steam

36,048 Aufrufe • vor 1 Jahr

i’ve been on a digital detox the past week. reading. journalling. and catching up on rest. offline is the new luxury. i’m going to be incorporating more stillness in my life. life can move so fast. i continue to be reminded of the beauty of slowness. slow walks. slow breaths. slow mornings. i’ve been in big sur, california. i learned the importance of figuring out my one big domino. the one thing that i can complete that when done makes everything else easier. for me it’s writing. writing unlocks epiphanies. unlocks opportunities. unlocks relationships. and I genuinely love it. i’m going full-time artist mode (delegated all operations across all my companies) and spending the rest of the year writing and focused on high-level strategy. my mantra: chop wood, carry water
0:26

i’ve been on a digital detox the past week. reading. journalling. and catching up on rest. offline is the new luxury. i’m going to be incorporating more stillness in my life. life can move so fast. i continue to be reminded of the beauty of slowness. slow walks. slow breaths. slow mornings. i’ve been in big sur, california. i learned the importance of figuring out my one big domino. the one thing that i can complete that when done makes everything else easier. for me it’s writing. writing unlocks epiphanies. unlocks opportunities. unlocks relationships. and I genuinely love it. i’m going full-time artist mode (delegated all operations across all my companies) and spending the rest of the year writing and focused on high-level strategy. my mantra: chop wood, carry water

MATT GRAY

11,860 Aufrufe • vor 1 Jahr