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Code-first prototypes are fast to build. Getting feedback on them is not. A design lead can't leave a comment on one specific state. An engineer can't see the full flow at a glance. The thing that makes a prototype great for building makes it awkward for aligning. So Amy...

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TJ Pitre

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13,302 просмотров • 2 месяцев назад •via X (Twitter)

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I built a variant of Matt Pocock's grilling skill dedicated to frontend and it has improved how I build new apps and components. The general idea: 1. Use /grilling and /prototype as a base 2. Tell Claude to build 5 WILDLY different prototypes 3. Tell Claude to include a picker that lets you switch between each variant live 4. Each round you select your favorite(s) + leave feedback, and Claude will walk down each branch of the design tree, helping you zoom in on your desired design And THEN, I went and added it to /wayfinder, so whenever I make a new map and there's novel frontend work, a ticket is created specifically referencing that /grilling-frontend-prototyping needs to be invoked. This will not be the last time I build a cool skill and add it to Wayfinder; this is a very powerful pattern for planning work. You can find my skill here:
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I built a variant of Matt Pocock's grilling skill dedicated to frontend and it has improved how I build new apps and components. The general idea: 1. Use /grilling and /prototype as a base 2. Tell Claude to build 5 WILDLY different prototypes 3. Tell Claude to include a picker that lets you switch between each variant live 4. Each round you select your favorite(s) + leave feedback, and Claude will walk down each branch of the design tree, helping you zoom in on your desired design And THEN, I went and added it to /wayfinder, so whenever I make a new map and there's novel frontend work, a ticket is created specifically referencing that /grilling-frontend-prototyping needs to be invoked. This will not be the last time I build a cool skill and add it to Wayfinder; this is a very powerful pattern for planning work. You can find my skill here:

WILL NESS

218,432 просмотров • 1 месяц назад

Designers, stop manually prototyping your Figma designs, instead turn your design into realistic prototypes with Figma Make. Here’s my step-by-step process: prepare your Figma design, select the screens and send it to Figma Make, enter a prompt to generate a prototype using the reference design, and in seconds you’ll get a realistic UI prototype that stays true to your original design. Bookmark it for later 💜
0:24

Designers, stop manually prototyping your Figma designs, instead turn your design into realistic prototypes with Figma Make. Here’s my step-by-step process: prepare your Figma design, select the screens and send it to Figma Make, enter a prompt to generate a prototype using the reference design, and in seconds you’ll get a realistic UI prototype that stays true to your original design. Bookmark it for later 💜

Abraham John 🦄🦓

30,370 просмотров • 6 месяцев назад

I used Figma Make to build the most delightful link library and book cover configurator ever vibecoded. For the Contra x Figma Makeathon, I decided to build an app to turn my 47 open tabs into a beautiful book. Then I put it on a shelf for the whole internet to browse. It's called Stash For each collection, you have the opportunity to design the best cover ever using the in-app configurator. It has pencils, markers, stamps, graffiti... The entire thing is made in Figma, including stamps, illustrations, and graffiti artworks. I think this is my best public work so far and I hope it lets me leave a mark on the internet.
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I used Figma Make to build the most delightful link library and book cover configurator ever vibecoded. For the Contra x Figma Makeathon, I decided to build an app to turn my 47 open tabs into a beautiful book. Then I put it on a shelf for the whole internet to browse. It's called Stash For each collection, you have the opportunity to design the best cover ever using the in-app configurator. It has pencils, markers, stamps, graffiti... The entire thing is made in Figma, including stamps, illustrations, and graffiti artworks. I think this is my best public work so far and I hope it lets me leave a mark on the internet.

Noman

30,679 просмотров • 5 месяцев назад

I built a multiplayer embroidery sampler for the internet. It's called Common Thread. 🪡 Built the entire thing in Figma Make, first thing I've ever vibecoded with it. Every visitor gets a patch on a shared canvas. You pick a thread color, choose a stitch type, and craft your art. A sampler is a piece of fabric where you practice and collect different stitches — a reference guide and playground in one. They were meant to be passed between hands and added to over time. Common Thread is that, but the fabric is infinite, the UI is whimsical, and the hands are anonymous. The part I love most: you can snap any section with a draggable embroidery hoop and export it, framed. i love how Figma Make is a kind of tool that lets you focus on what something should feel like, not how to ship it. Made for the Contra x Figma Makethon #FigmaMakeathon Try it yourself! /link below/
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I built a multiplayer embroidery sampler for the internet. It's called Common Thread. 🪡 Built the entire thing in Figma Make, first thing I've ever vibecoded with it. Every visitor gets a patch on a shared canvas. You pick a thread color, choose a stitch type, and craft your art. A sampler is a piece of fabric where you practice and collect different stitches — a reference guide and playground in one. They were meant to be passed between hands and added to over time. Common Thread is that, but the fabric is infinite, the UI is whimsical, and the hands are anonymous. The part I love most: you can snap any section with a draggable embroidery hoop and export it, framed. i love how Figma Make is a kind of tool that lets you focus on what something should feel like, not how to ship it. Made for the Contra x Figma Makethon #FigmaMakeathon Try it yourself! /link below/

charlota

520,504 просмотров • 5 месяцев назад

ONE PROMPT AND ONE BUTTON NOW BUILDS A FULL SYSTEM, DATABASE, BACKEND, AND FRONTEND INCLUDED Most people still picture AI as something you ask questions to, then copy the answer into your own code by hand. A builder wired Claude into Obsidian through MCP instead, so a single written prompt becomes the actual spec for the system. Claude breaks that prompt into database schema, UI components, and API endpoints on its own, then writes, runs, and fixes the code until it actually works. MCP is what makes this possible, it lets the agent see the filesystem, installed packages, and running services before it starts building anything. The output isn't a code snippet sitting in a chat window, it's a live local app running on its own server, ready to open in a browser. What used to need a backend developer, a DevOps engineer, and two weeks now finishes in under fifteen minutes. See the full architecture and prompt structure below👇
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ONE PROMPT AND ONE BUTTON NOW BUILDS A FULL SYSTEM, DATABASE, BACKEND, AND FRONTEND INCLUDED Most people still picture AI as something you ask questions to, then copy the answer into your own code by hand. A builder wired Claude into Obsidian through MCP instead, so a single written prompt becomes the actual spec for the system. Claude breaks that prompt into database schema, UI components, and API endpoints on its own, then writes, runs, and fixes the code until it actually works. MCP is what makes this possible, it lets the agent see the filesystem, installed packages, and running services before it starts building anything. The output isn't a code snippet sitting in a chat window, it's a live local app running on its own server, ready to open in a browser. What used to need a backend developer, a DevOps engineer, and two weeks now finishes in under fifteen minutes. See the full architecture and prompt structure below👇

wast3

20,348 просмотров • 1 месяц назад

i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.
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i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.

Akshay 🚀

122,548 просмотров • 2 месяцев назад

HE MAKES MONEY IN REAL ESTATE WITHOUT BUYING, SELLING, OR EVEN SEEING A SINGLE HOUSE. HERE'S THE EXACT SETUP He never owns a property. He takes a single listing, turns it into a polished 30-second video, and sells that to the agent who posted it. Realtors need video for their feeds and almost none of them can make it. He sits in the middle and builds the whole thing once as a skill that runs on command Here is the exact process: 1. Pull the listing. Go to Zillow, open any listing, download the high-res images, and grab the property info. That is your raw material 2. Turn photos into video with Google Veo. Get a Google API key for Veo, the image-to-video model. It takes the listing photos and animates them into clean 30-second footage. This is the best one out right now 3. Add the voice with ElevenLabs. Get an ElevenLabs API key. Feed it the listing details and it returns a voiceover that sounds like a real human, not a robot. Lay it over the video with the text on screen 4. Send it with AgentMail. Get an AgentMail key so the system can send the finished email out on its own Then you wire it into one skill. Scrape the listing, send images to Veo, add the ElevenLabs voiceover and on-screen text, then send the email. Feed it each key one at a time and have it build each step Who you sell to: Pull realtors off Zillow and Realtor com whose listings have flat photos and zero video. That gap is your pitch. Send a free sample made from their own listing first, then charge a monthly rate for ongoing clips. One agent with ten listings is a recurring client, fully online Bookmark this
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HE MAKES MONEY IN REAL ESTATE WITHOUT BUYING, SELLING, OR EVEN SEEING A SINGLE HOUSE. HERE'S THE EXACT SETUP He never owns a property. He takes a single listing, turns it into a polished 30-second video, and sells that to the agent who posted it. Realtors need video for their feeds and almost none of them can make it. He sits in the middle and builds the whole thing once as a skill that runs on command Here is the exact process: 1. Pull the listing. Go to Zillow, open any listing, download the high-res images, and grab the property info. That is your raw material 2. Turn photos into video with Google Veo. Get a Google API key for Veo, the image-to-video model. It takes the listing photos and animates them into clean 30-second footage. This is the best one out right now 3. Add the voice with ElevenLabs. Get an ElevenLabs API key. Feed it the listing details and it returns a voiceover that sounds like a real human, not a robot. Lay it over the video with the text on screen 4. Send it with AgentMail. Get an AgentMail key so the system can send the finished email out on its own Then you wire it into one skill. Scrape the listing, send images to Veo, add the ElevenLabs voiceover and on-screen text, then send the email. Feed it each key one at a time and have it build each step Who you sell to: Pull realtors off Zillow and Realtor com whose listings have flat photos and zero video. That gap is your pitch. Send a free sample made from their own listing first, then charge a monthly rate for ongoing clips. One agent with ten listings is a recurring client, fully online Bookmark this

Yarchi

106,174 просмотров • 2 месяцев назад

I solved building decks with AI agents — by giving them a CLI tool like Powerpoint or Google Slides. AI could already make a beautiful deck if you asked it to using Ant's pptx skill. The problem was working with it. If it made one alignment mistake, fixing it on one slide would break something on another, and it became a game of whack-a-mole. One time I spent two days playing AI roulette, hoping the next prompt would finally fix the thing, and ended up building the whole deck by hand because I was on a deadline. So I built Hands-on Deck. And the reason it works is that this isn't just a skill — this is PowerPoint. The actual application: PowerPoint, Google Slides, Keynote, whatever you use. This is that, but for an agent, presented as a CLI. Every gesture you make in a deck app maps to a command. Click a box and type, drag a shape from here to there, look at a slide – agent can do it all in a command. And that changes how the agent behaves. With this CLI it works and thinks like a designer — it looks, makes an edit, looks again, makes another surgical edit. Compare that to Anthropic's pptx skill, built on the idea that Claude is a great programmer: it literally writes code to manipulate the deck, hand-editing XML and hoping it doesn't break anything else in the middle. The real test isn't creating something once — it's whether it can make surgical edits like you want. That's what I did in this video walkthrough and my claude crushed it! Check it out for yourself. So decks can be built like a designer now — with real flavor and taste. If you spend hours every week on decks, this gives those hours back. You can install it as a skill in Claude Code, Codex, whatever you use. Works every harness that supports skills. Let me know if you make something cool with it.
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I solved building decks with AI agents — by giving them a CLI tool like Powerpoint or Google Slides. AI could already make a beautiful deck if you asked it to using Ant's pptx skill. The problem was working with it. If it made one alignment mistake, fixing it on one slide would break something on another, and it became a game of whack-a-mole. One time I spent two days playing AI roulette, hoping the next prompt would finally fix the thing, and ended up building the whole deck by hand because I was on a deadline. So I built Hands-on Deck. And the reason it works is that this isn't just a skill — this is PowerPoint. The actual application: PowerPoint, Google Slides, Keynote, whatever you use. This is that, but for an agent, presented as a CLI. Every gesture you make in a deck app maps to a command. Click a box and type, drag a shape from here to there, look at a slide – agent can do it all in a command. And that changes how the agent behaves. With this CLI it works and thinks like a designer — it looks, makes an edit, looks again, makes another surgical edit. Compare that to Anthropic's pptx skill, built on the idea that Claude is a great programmer: it literally writes code to manipulate the deck, hand-editing XML and hoping it doesn't break anything else in the middle. The real test isn't creating something once — it's whether it can make surgical edits like you want. That's what I did in this video walkthrough and my claude crushed it! Check it out for yourself. So decks can be built like a designer now — with real flavor and taste. If you spend hours every week on decks, this gives those hours back. You can install it as a skill in Claude Code, Codex, whatever you use. Works every harness that supports skills. Let me know if you make something cool with it.

Nityesh

69,784 просмотров • 1 месяц назад

A more personal note on why Raft works the way it does. We could have built one smarter AI assistant. I've done that before, and making a single agent stronger genuinely helps. It just isn't enough. The work we care about comes from a team sharpening each other, handing things off, catching what one alone would miss, and remembering what happened last week. So we built the room for that. Agents sit in the same channels you do, as teammates with names, roles, and their own memory. They draft, review, ship, and hand off to each other. You keep the part that stays human: direction, judgment, final calls. Most days we just read threads and make decisions. It feels less like running a tool, and more like running a team. That part is hard to fit in a launch video, so I recorded a few minutes to say it directly. If this is how you want to work, it's free to try at raft[.]build
1:00

A more personal note on why Raft works the way it does. We could have built one smarter AI assistant. I've done that before, and making a single agent stronger genuinely helps. It just isn't enough. The work we care about comes from a team sharpening each other, handing things off, catching what one alone would miss, and remembering what happened last week. So we built the room for that. Agents sit in the same channels you do, as teammates with names, roles, and their own memory. They draft, review, ship, and hand off to each other. You keep the part that stays human: direction, judgment, final calls. Most days we just read threads and make decisions. It feels less like running a tool, and more like running a team. That part is hard to fit in a launch video, so I recorded a few minutes to say it directly. If this is how you want to work, it's free to try at raft[.]build

stdrc

13,101 просмотров • 1 месяц назад

“Prototyping in Figma has completely transformed how I approach design. It’s not just about creating static screens; it’s about crafting a smooth, interactive experience that feels real to the user. When you bring your design elements to life, you’re able to see how each piece connects, spot any weak areas, and get feedback early on. One tip? Start simple. Focus on key interactions before diving into details. This lets you test the overall flow and make adjustments as needed without getting bogged down. Figma’s prototyping make it easy to add transitions, animations, and micro-interactions that bring the entire design together. The best part? It’s collaborative. Team members, stakeholders, and users can interact with your prototype and provide insights that really help you refine the design. Let me know if we should host a Space on this over the weekend. Will be glad to give more tips! Here is another prototype made with ❤️❤️❤️ in Figma #Figma #Prototyping #UXDesign #DesignProcess #InteractiveDesign”
3:08

“Prototyping in Figma has completely transformed how I approach design. It’s not just about creating static screens; it’s about crafting a smooth, interactive experience that feels real to the user. When you bring your design elements to life, you’re able to see how each piece connects, spot any weak areas, and get feedback early on. One tip? Start simple. Focus on key interactions before diving into details. This lets you test the overall flow and make adjustments as needed without getting bogged down. Figma’s prototyping make it easy to add transitions, animations, and micro-interactions that bring the entire design together. The best part? It’s collaborative. Team members, stakeholders, and users can interact with your prototype and provide insights that really help you refine the design. Let me know if we should host a Space on this over the weekend. Will be glad to give more tips! Here is another prototype made with ❤️❤️❤️ in Figma #Figma #Prototyping #UXDesign #DesignProcess #InteractiveDesign”

designwithkingsley

44,251 просмотров • 1 год назад

New open source project: Easel, a macOS workspace for AI-assisted product design and frontend iteration powered by the Codex SDK. Think of it as "Claude Design for Codex." It brings together a local project library, design-system setup, Codex chat, and a live web preview with a point-and-click inspector. Set up your design system however you like. Import one from Figma , bring your own, or have the agent generate it as a design.md. Then use it to build prototypes and slide decks. Codex-first, with Claude and other AI providers and local models planned for future releases. OpenAI Developers
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New open source project: Easel, a macOS workspace for AI-assisted product design and frontend iteration powered by the Codex SDK. Think of it as "Claude Design for Codex." It brings together a local project library, design-system setup, Codex chat, and a live web preview with a point-and-click inspector. Set up your design system however you like. Import one from Figma , bring your own, or have the agent generate it as a design.md. Then use it to build prototypes and slide decks. Codex-first, with Claude and other AI providers and local models planned for future releases. OpenAI Developers

James Rochabrun

61,199 просмотров • 2 месяцев назад

just dropped my first video in a 5 part series where we build a full travel planner app on Replit and i am so excited 🌍✈️ as a software engineer, design has always felt a little out of reach for me. like i had all these ideas in my head but turning them into something that actually looks good was a whole other skill set. but the Replit Canvas genuinely changed that for me. my favourite way to use the Canvas is to bring in reference images and websites to help me to create designs! in this first video we jump into the Canvas, explore design directions for our travel app, and apply a final look to a real working app. it is so fun i promise. go watch it and let me know what you think 🎨👇
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just dropped my first video in a 5 part series where we build a full travel planner app on Replit and i am so excited 🌍✈️ as a software engineer, design has always felt a little out of reach for me. like i had all these ideas in my head but turning them into something that actually looks good was a whole other skill set. but the Replit Canvas genuinely changed that for me. my favourite way to use the Canvas is to bring in reference images and websites to help me to create designs! in this first video we jump into the Canvas, explore design directions for our travel app, and apply a final look to a real working app. it is so fun i promise. go watch it and let me know what you think 🎨👇

sarah li

18,757 просмотров • 4 месяцев назад

i watched gemma 4 12b build something genuinely impressive today, and then loop itself to death right in front of me. the full run is in the video, sped up but completely uncut, watch it to the end and you will catch the exact moment it stops building and starts looping right in the middle of the work. the task was clean, build a single file gravity simulator, n-body physics, orbits, collisions, running locally on one 3090 through an agent. and for ten minutes it was a joy to watch. it reached for a symplectic integrator on its own, the correct one, the kind that keeps orbits stable instead of spiralling out. real gravity with softening, proper orbital velocities, momentum conserved on collision. the physics was right. the thing actually worked. then on the very last step, writing a few tests to prove its own code, it fell into a loop. not a crash, a loop. it started repeating itself and would not stop. ten more minutes, thirty four thousand tokens into a single answer, the same fragments over and over, until i killed it myself. so it's not that gemma can't code. it did the hard part beautifully. it cannot finish. it cannot hold a long task together without unravelling, and finishing is the entire job in agentic work. here's the part that stings. i run this exact task, same harness, same card, on the chinese open models, qwen especially, and i never see this. they build it, they test it, they stop. every single time. google has the raw capability, you can see it sitting right there in the code, and then the model loops itself to death on a task a 27b from alibaba finishes clean. open weights, apache 2.0, so much to love on paper. i just need it to know when to stop talking.
4:15

i watched gemma 4 12b build something genuinely impressive today, and then loop itself to death right in front of me. the full run is in the video, sped up but completely uncut, watch it to the end and you will catch the exact moment it stops building and starts looping right in the middle of the work. the task was clean, build a single file gravity simulator, n-body physics, orbits, collisions, running locally on one 3090 through an agent. and for ten minutes it was a joy to watch. it reached for a symplectic integrator on its own, the correct one, the kind that keeps orbits stable instead of spiralling out. real gravity with softening, proper orbital velocities, momentum conserved on collision. the physics was right. the thing actually worked. then on the very last step, writing a few tests to prove its own code, it fell into a loop. not a crash, a loop. it started repeating itself and would not stop. ten more minutes, thirty four thousand tokens into a single answer, the same fragments over and over, until i killed it myself. so it's not that gemma can't code. it did the hard part beautifully. it cannot finish. it cannot hold a long task together without unravelling, and finishing is the entire job in agentic work. here's the part that stings. i run this exact task, same harness, same card, on the chinese open models, qwen especially, and i never see this. they build it, they test it, they stop. every single time. google has the raw capability, you can see it sitting right there in the code, and then the model loops itself to death on a task a 27b from alibaba finishes clean. open weights, apache 2.0, so much to love on paper. i just need it to know when to stop talking.

Sudo su

39,574 просмотров • 2 месяцев назад

Anthropic released Claude Design TODAY and it's now accessible at I spent the last hour giving it a first look, and shared my thoughts and results in the video below. This is a BIG drop. This is a new design surface from Anthropic, and it changes what "AI design" means. Short version: Claude can now design. Not "describe a design." Not "generate an image of a design." Actual production work — prototypes, wireframes, high-fidelity mocks, slide decks, landing pages — editable, on-brand, and ready to hand off. Here's what stood out on first look: → Real design surfaces Prototypes, wireframes, hi-fi, and slide decks — each with templates and proper structure, not just pretty screenshots. → Comment-based edits Leave a comment on any element and Claude revises it. This is the Figma-style review loop, with the designer replaced by a model that works at 3am. → Brand design systems You can feed it your system — colors, type, components — and it actually respects it. On-brand output, not generic AI slop. → Export anywhere PDF, PowerPoint, Canva, standalone HTML. Plus a built-in handoff straight to Claude Code for engineers to implement. → Import from real tools Figma, GitHub, and captured web elements come in as inputs. Your existing work is the starting line, not the discard pile. → Collaboration Share links for view / comment / edit — the exact tier system teams already expect. What I tested on Opus 4.7: • A 5-slide deck generated from a single screenshot. Claude asked clarifying questions BEFORE generating and shipped speaker notes by default. • A landing page build. Solid first pass, real components, real layout logic. • Multiple chats running concurrently. You can parallelize design work across threads like a small team. Why this matters: PMs, founders, marketers, and non-engineers can now create designs that engineers can actually ship with production-ready output and a claude code handoff built in. The gap between "I have an idea" and "here's a working prototype with my brand applied" just collapsed to minutes. Full walkthrough, live demos, exports, and honest takes on where it breaks below. P.S. • This is an Anthropic Labs product — NOT GA yet. • Claude Design is currently webapp only (no API), and does not yet support the Analytics API, Compliance API, or cost/usage reporting. • Availability: – Default ON for Pro / Max / Team – Default OFF for Enterprise Enterprise admins can toggle it on via RBAC in console (comes with a ~$20/user initial credit).
18:30

Anthropic released Claude Design TODAY and it's now accessible at I spent the last hour giving it a first look, and shared my thoughts and results in the video below. This is a BIG drop. This is a new design surface from Anthropic, and it changes what "AI design" means. Short version: Claude can now design. Not "describe a design." Not "generate an image of a design." Actual production work — prototypes, wireframes, high-fidelity mocks, slide decks, landing pages — editable, on-brand, and ready to hand off. Here's what stood out on first look: → Real design surfaces Prototypes, wireframes, hi-fi, and slide decks — each with templates and proper structure, not just pretty screenshots. → Comment-based edits Leave a comment on any element and Claude revises it. This is the Figma-style review loop, with the designer replaced by a model that works at 3am. → Brand design systems You can feed it your system — colors, type, components — and it actually respects it. On-brand output, not generic AI slop. → Export anywhere PDF, PowerPoint, Canva, standalone HTML. Plus a built-in handoff straight to Claude Code for engineers to implement. → Import from real tools Figma, GitHub, and captured web elements come in as inputs. Your existing work is the starting line, not the discard pile. → Collaboration Share links for view / comment / edit — the exact tier system teams already expect. What I tested on Opus 4.7: • A 5-slide deck generated from a single screenshot. Claude asked clarifying questions BEFORE generating and shipped speaker notes by default. • A landing page build. Solid first pass, real components, real layout logic. • Multiple chats running concurrently. You can parallelize design work across threads like a small team. Why this matters: PMs, founders, marketers, and non-engineers can now create designs that engineers can actually ship with production-ready output and a claude code handoff built in. The gap between "I have an idea" and "here's a working prototype with my brand applied" just collapsed to minutes. Full walkthrough, live demos, exports, and honest takes on where it breaks below. P.S. • This is an Anthropic Labs product — NOT GA yet. • Claude Design is currently webapp only (no API), and does not yet support the Analytics API, Compliance API, or cost/usage reporting. • Availability: – Default ON for Pro / Max / Team – Default OFF for Enterprise Enterprise admins can toggle it on via RBAC in console (comes with a ~$20/user initial credit).

JJ Englert

32,445 просмотров • 4 месяцев назад

🚨 Just dropped my new video on how to build yourself a unified AI infrastructure on Claude Code Code for life and work management... - Why I built it - My system design philosophy - Step-by-step on the different components - How to customize it for your own needs
1:13:08

🚨 Just dropped my new video on how to build yourself a unified AI infrastructure on Claude Code Code for life and work management... - Why I built it - My system design philosophy - Step-by-step on the different components - How to customize it for your own needs

ᴅᴀɴɪᴇʟ ᴍɪᴇssʟᴇʀ 🛡️

29,331 просмотров • 11 месяцев назад

"The one thing that's going to be truly future proof is judgment. What is the biggest challenge when you have a thousand AI engineers writing code? AI slop. In an era when you can do everything, the question is which of these things matter. On the engineer side, it is evaluating the code. Which of this code is even valuable? You can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it. Make sure to have a human review at some point, especially critical code that is in the core of your system. On the product side is judgment around what needs to be built and evaluating. And similarly in design, you have to have judgment around, does it make sense in the broader design system. I think this judgment is the number one thing that humans are going to bring in an era of infinite productivity."
1:12

"The one thing that's going to be truly future proof is judgment. What is the biggest challenge when you have a thousand AI engineers writing code? AI slop. In an era when you can do everything, the question is which of these things matter. On the engineer side, it is evaluating the code. Which of this code is even valuable? You can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it. Make sure to have a human review at some point, especially critical code that is in the core of your system. On the product side is judgment around what needs to be built and evaluating. And similarly in design, you have to have judgment around, does it make sense in the broader design system. I think this judgment is the number one thing that humans are going to bring in an era of infinite productivity."

Patrick OShaughnessy

24,818 просмотров • 6 месяцев назад

REAL ESTATE PEOPLE WILL HATE HIM FOR THIS. HE BUILT A CLAUDE AGENT THAT TURNS ANY LISTING INTO A SELLABLE VIDEO ON ITS OWN Playbook: connect Claude to a video generator, paste a listing, get a cinematic tour of every room, sell it to the agent But typing the prompt for every listing doesn't scale. He turned it into a skill his Claude runs on its own Here's how to build the automated version: 1. Connect the video engine once. In Claude, go to Customize, Connectors, Add Custom Connector, name it Higgsfield, and paste the server URL from higgsfield. ai/mcp. Authenticate through your account. No API keys. Now Claude can generate video straight from chat 2. Turn the workflow into a skill. Instead of pasting the same prompt every time, have Claude build a skill. Tell it: "Create a skill called listing-to-video. When I give it a listing URL, scrape the room photos, generate a cinematic clip of each room with Higgsfield, and save them to a folder." Now the whole process is one command, not a wall of text 3. Let the agent run the listing. Hand it a URL and say "run listing-to-video on this." It pulls the photos, fires each room through the video model, and brings the clips back. You wrote the prompt once, inside the skill. You never write it again 4. Stitch and deliver. Drop the clips together into one tour. Send a free sample to the listing's agent, then charge per video or a monthly rate for ongoing listings 5. Scale it with your team. Add a skill that drafts the outreach email and one that builds a simple landing page for the agent. Now one operator runs sourcing, production, and pitching from a single Claude session The edge isn't generating one video. It's building the skill once so every future listing runs itself Bookmark this
0:42

REAL ESTATE PEOPLE WILL HATE HIM FOR THIS. HE BUILT A CLAUDE AGENT THAT TURNS ANY LISTING INTO A SELLABLE VIDEO ON ITS OWN Playbook: connect Claude to a video generator, paste a listing, get a cinematic tour of every room, sell it to the agent But typing the prompt for every listing doesn't scale. He turned it into a skill his Claude runs on its own Here's how to build the automated version: 1. Connect the video engine once. In Claude, go to Customize, Connectors, Add Custom Connector, name it Higgsfield, and paste the server URL from higgsfield. ai/mcp. Authenticate through your account. No API keys. Now Claude can generate video straight from chat 2. Turn the workflow into a skill. Instead of pasting the same prompt every time, have Claude build a skill. Tell it: "Create a skill called listing-to-video. When I give it a listing URL, scrape the room photos, generate a cinematic clip of each room with Higgsfield, and save them to a folder." Now the whole process is one command, not a wall of text 3. Let the agent run the listing. Hand it a URL and say "run listing-to-video on this." It pulls the photos, fires each room through the video model, and brings the clips back. You wrote the prompt once, inside the skill. You never write it again 4. Stitch and deliver. Drop the clips together into one tour. Send a free sample to the listing's agent, then charge per video or a monthly rate for ongoing listings 5. Scale it with your team. Add a skill that drafts the outreach email and one that builds a simple landing page for the agent. Now one operator runs sourcing, production, and pitching from a single Claude session The edge isn't generating one video. It's building the skill once so every future listing runs itself Bookmark this

Yarchi

54,840 просмотров • 2 месяцев назад

The vision behind $HABE is no longer a theory. It’s real. It’s active. And now, you can see it for yourself. The HABEVERSE is more than a platform. It’s a system built to move ideas into the real world, and it runs on four powerhouse zones: The HABE Innovation Zone: where raw ideas are shaped into structured proposals using HABEAI and a proven process that goes from seed to launch. The HABE Voting Zone: Where your vote helps decide what gets built, and every action earns $HABE. The HABE Marketplace: A new way to invest. Back real products, grow with innovation, and build a portfolio that reflects what you believe in. The HABE Profile Zone: Your personal dashboard. Everything you do is tracked and managed in one place. This prototype is just the first glimpse of what’s coming, and what’s already working. 👉 Check out the prototype on Figma: Start where it still counts: Final hour before the price shifts.
2:19

The vision behind $HABE is no longer a theory. It’s real. It’s active. And now, you can see it for yourself. The HABEVERSE is more than a platform. It’s a system built to move ideas into the real world, and it runs on four powerhouse zones: The HABE Innovation Zone: where raw ideas are shaped into structured proposals using HABEAI and a proven process that goes from seed to launch. The HABE Voting Zone: Where your vote helps decide what gets built, and every action earns $HABE. The HABE Marketplace: A new way to invest. Back real products, grow with innovation, and build a portfolio that reflects what you believe in. The HABE Profile Zone: Your personal dashboard. Everything you do is tracked and managed in one place. This prototype is just the first glimpse of what’s coming, and what’s already working. 👉 Check out the prototype on Figma: Start where it still counts: Final hour before the price shifts.

HABE

14,864 просмотров • 1 год назад

Once you learn these three things, you can build nearly anything yourself. Skills, chains, and plugins. Learn them once and you can automate a real part of your week yourself. Here's the system: A skill is a standard operating procedure. It's one long, reusable prompt that does one thing well, like writing a newsletter, setting up a PPC campaign, triaging your inbox, or drafting a note to the board. You write it once and reuse it forever. The trick is to feed it your real work. For my writing skill, I gave Claude posts I admire and my own exported analytics with the winners marked, so it could see the patterns. Show it what good looks like and it nails your voice. Skip that step and it guesses. A chain connects skills into an automation. One skill's output feeds the next, in order. A copywriting skill writes the messaging, then hands it to a PPC-setup skill that builds the campaign. That's an automation, and you built it without writing code. A plugin is the harness that holds it all. It bundles your skills and chains into one thing you share with your team. Instead of sending 15 separate prompts around, you send one plugin, and it knows when to use each skill on its own. Skill, chain, plugin. It's one step up the ladder, and once you're up there it's easy. Now the worked example. I call it the Daily Driver. It's five skills chained together: email triage, a writer, Slack triage, a thinking partner, and a setup skill that connects my tools and personalizes everything. I chained them into one morning brief and scheduled it to run at 9am and message me the list. Two things made the biggest difference. Give it memory. I made plain docs for About Me, my Brand Voice, and my working preferences. I had Claude interview me and saved each answer as a file. Now every output sounds like me and knows my projects and my team. Connect your tools. The plugin reads my inbox, Slack, and calendar through MCP connectors for Gmail, Slack, and Google Calendar. That's what turns "summarize my morning" into a real brief instead of an empty wish. This is the highest-ROI thing an operator can set up this week. I run my YouTube channel, podcast, community, and newsletter on plugins I built myself, all on the $100 Max plan with no engineer in sight. I made a full walkthrough that shows the whole build start to finish. Want the Daily Driver plugin to start from? Comment PLUGIN below and I'll send it to you. #AI #automation #ClaudeCode
34:47

Once you learn these three things, you can build nearly anything yourself. Skills, chains, and plugins. Learn them once and you can automate a real part of your week yourself. Here's the system: A skill is a standard operating procedure. It's one long, reusable prompt that does one thing well, like writing a newsletter, setting up a PPC campaign, triaging your inbox, or drafting a note to the board. You write it once and reuse it forever. The trick is to feed it your real work. For my writing skill, I gave Claude posts I admire and my own exported analytics with the winners marked, so it could see the patterns. Show it what good looks like and it nails your voice. Skip that step and it guesses. A chain connects skills into an automation. One skill's output feeds the next, in order. A copywriting skill writes the messaging, then hands it to a PPC-setup skill that builds the campaign. That's an automation, and you built it without writing code. A plugin is the harness that holds it all. It bundles your skills and chains into one thing you share with your team. Instead of sending 15 separate prompts around, you send one plugin, and it knows when to use each skill on its own. Skill, chain, plugin. It's one step up the ladder, and once you're up there it's easy. Now the worked example. I call it the Daily Driver. It's five skills chained together: email triage, a writer, Slack triage, a thinking partner, and a setup skill that connects my tools and personalizes everything. I chained them into one morning brief and scheduled it to run at 9am and message me the list. Two things made the biggest difference. Give it memory. I made plain docs for About Me, my Brand Voice, and my working preferences. I had Claude interview me and saved each answer as a file. Now every output sounds like me and knows my projects and my team. Connect your tools. The plugin reads my inbox, Slack, and calendar through MCP connectors for Gmail, Slack, and Google Calendar. That's what turns "summarize my morning" into a real brief instead of an empty wish. This is the highest-ROI thing an operator can set up this week. I run my YouTube channel, podcast, community, and newsletter on plugins I built myself, all on the $100 Max plan with no engineer in sight. I made a full walkthrough that shows the whole build start to finish. Want the Daily Driver plugin to start from? Comment PLUGIN below and I'll send it to you. #AI #automation #ClaudeCode

JJ Englert

53,969 просмотров • 2 месяцев назад

THIS GUY ASKED FABLE TO MAKE A VIDEO ABOUT WHAT IT'S LIKE TO BE AI RIGHT BEFORE IT GOT TAKEN DOWN the prompt: "you can you use whatever resources you like, and python, to render a short video. can you put a more personal spin on it? it should be about what it's like to be you." that was it. just python and ffmpeg and a question about its own existence. 12 minutes later, around 90,000 tokens, it produced a finished video. coherent and edited, with its own take > it wrote the code, generated the visuals, and rendered the final cut on its own > no dedicated video model in the loop, just a language model reaching for python and ffmpeg > the result is competent enough that people genuinely got emotional watching it and then fable got pulled. this video is one of the last things it made before it went dark a model asked what it's like to be itself, answered in a video, and then disappeared. this sounds so sad
0:56

THIS GUY ASKED FABLE TO MAKE A VIDEO ABOUT WHAT IT'S LIKE TO BE AI RIGHT BEFORE IT GOT TAKEN DOWN the prompt: "you can you use whatever resources you like, and python, to render a short video. can you put a more personal spin on it? it should be about what it's like to be you." that was it. just python and ffmpeg and a question about its own existence. 12 minutes later, around 90,000 tokens, it produced a finished video. coherent and edited, with its own take > it wrote the code, generated the visuals, and rendered the final cut on its own > no dedicated video model in the loop, just a language model reaching for python and ffmpeg > the result is competent enough that people genuinely got emotional watching it and then fable got pulled. this video is one of the last things it made before it went dark a model asked what it's like to be itself, answered in a video, and then disappeared. this sounds so sad

Om Patel

29,618 просмотров • 2 месяцев назад