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🤯 Just tried Claude’s Blender Connector with #Hyper3D Skill — it just generated a full exploded view animation straight inside Blender 🔶! 🔥 🤔 3D creator agents are actually coming, aren’t they? #b3d #Claude #Blender

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Hyper3D by Deemos

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56,219 görüntüleme • 3 ay önce •via X (Twitter)

#Hyper3D#b3d#Claude#Blender
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.Max Panysh 🔶 showcased a super-realistic 3D car drifting animation made using Blender in just four days. See more of Max's amazing works: #blender #blender3d #b3d #blenderrender #blenderanimation #animation #3danimation #realistic #car #cars #bmw
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.Max Panysh 🔶 showcased a super-realistic 3D car drifting animation made using Blender in just four days. See more of Max's amazing works: #blender #blender3d #b3d #blenderrender #blenderanimation #animation #3danimation #realistic #car #cars #bmw

80 LEVEL

586,108 görüntüleme • 2 yıl önce

this is insane… they just connected Claude to Blender you can do 3D modeling by chatting with it
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this is insane… they just connected Claude to Blender you can do 3D modeling by chatting with it

el.cine

74,702 görüntüleme • 4 ay önce

🚀Major update to Blender MCP: 🌄 Generate high-quality 3D assets in Blender by just prompting, thanks to Hyper3D by Deemos's Rodin AI. 🎬 Demo: Creating a cozy scene with a cat. Just describe the assets you want, and it will show up right in Blender. No manual modeling needed!
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🚀Major update to Blender MCP: 🌄 Generate high-quality 3D assets in Blender by just prompting, thanks to Hyper3D by Deemos's Rodin AI. 🎬 Demo: Creating a cozy scene with a cat. Just describe the assets you want, and it will show up right in Blender. No manual modeling needed!

siddharth ahuja

109,971 görüntüleme • 1 yıl önce

Finished this Rogue animation today. I tried to not to spend too much time on it and just get it done quickly. Rig is from A$AP BERG #3danimation #animation #blender #b3d
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Finished this Rogue animation today. I tried to not to spend too much time on it and just get it done quickly. Rig is from A$AP BERG #3danimation #animation #blender #b3d

afrotron

17,447 görüntüleme • 5 ay önce

Blender just became a prompt box. With Kimi K3 connected through Blender MCP, you can describe a scene like this in plain English and let the model handle the ugly part: terrain, buildings, lighting, materials, camera movement, animation, and the Python scripts holding everything together. The interesting part is not the first render. Kimi can inspect the result, notice that the camera clips through a tree or the city looks suspiciously like plastic, then edit the actual Blender scene and render it again instead of restarting from zero. You still need taste, because “make it cinematic” remains one of humanity’s least useful instructions. But the distance between an empty Blender file and a fully editable 3D world just got embarrassingly small. A few years ago, creating this meant weeks of modeling, scripting, lighting, and animation. Now you can describe the world, watch Kimi build it, and spend your time fixing the final 10% instead of manually constructing the first 90%. Kimi K3 + Blender MCP is basically text-to-3D without trapping the result inside a useless generated video. Every object, material, light, camera, and keyframe stays editable.
0:12

Blender just became a prompt box. With Kimi K3 connected through Blender MCP, you can describe a scene like this in plain English and let the model handle the ugly part: terrain, buildings, lighting, materials, camera movement, animation, and the Python scripts holding everything together. The interesting part is not the first render. Kimi can inspect the result, notice that the camera clips through a tree or the city looks suspiciously like plastic, then edit the actual Blender scene and render it again instead of restarting from zero. You still need taste, because “make it cinematic” remains one of humanity’s least useful instructions. But the distance between an empty Blender file and a fully editable 3D world just got embarrassingly small. A few years ago, creating this meant weeks of modeling, scripting, lighting, and animation. Now you can describe the world, watch Kimi build it, and spend your time fixing the final 10% instead of manually constructing the first 90%. Kimi K3 + Blender MCP is basically text-to-3D without trapping the result inside a useless generated video. Every object, material, light, camera, and keyframe stays editable.

Rina

264,158 görüntüleme • 16 gün önce

You can now describe a spaceship to Grok and watch it build in Blender. Not just a rough shape. Grok writes the Python, creates the geometry, materials and rigging, checks its own viewport renders, then keeps fixing what looks wrong. One demo ended with a fully rigged 86,000-triangle spaceship from text alone. That turns 3D modeling from “learn every tool first” into “start with the idea and refine from there.” The default cube should be nervous. Grok SpaceXAI Blender 🔶 / Writer: Annette, Grok Imagine Designer: Janné
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You can now describe a spaceship to Grok and watch it build in Blender. Not just a rough shape. Grok writes the Python, creates the geometry, materials and rigging, checks its own viewport renders, then keeps fixing what looks wrong. One demo ended with a fully rigged 86,000-triangle spaceship from text alone. That turns 3D modeling from “learn every tool first” into “start with the idea and refine from there.” The default cube should be nervous. Grok SpaceXAI Blender 🔶 / Writer: Annette, Grok Imagine Designer: Janné

Mario Nawfal

90,913 görüntüleme • 1 gün önce

We are getting absurdly close to the point where “learning Blender” means learning how to direct an AI. A shot like this looks soft and playful on the surface, but under it is the usual 3D pain: modeling, layout, materials, lighting, atmosphere, animation, and endless tiny fixes until the frame stops looking dead. That is why Kimi K3 matters. With Blender MCP, you can describe a scene like a robotic goat walking through a dreamy field and let the model help build the environment, place the camera, shape the materials, script the motion, and iterate inside the real Blender project. The real shift is not text-to-image. It is text-to-workflow. Kimi K3 does not just give you a pretty output and disappear. It can help move the actual scene from rough setup to something that looks art-directed. Soon the hardest part of 3D will not be the software. It will be whether your imagination is good enough to deserve tools like this.
0:12

We are getting absurdly close to the point where “learning Blender” means learning how to direct an AI. A shot like this looks soft and playful on the surface, but under it is the usual 3D pain: modeling, layout, materials, lighting, atmosphere, animation, and endless tiny fixes until the frame stops looking dead. That is why Kimi K3 matters. With Blender MCP, you can describe a scene like a robotic goat walking through a dreamy field and let the model help build the environment, place the camera, shape the materials, script the motion, and iterate inside the real Blender project. The real shift is not text-to-image. It is text-to-workflow. Kimi K3 does not just give you a pretty output and disappear. It can help move the actual scene from rough setup to something that looks art-directed. Soon the hardest part of 3D will not be the software. It will be whether your imagination is good enough to deserve tools like this.

Rina

45,651 görüntüleme • 13 gün önce

If you think this is just another silly demo made with AI, read this post. You might change your mind, because this demo is about MATH. What you see on the screen is not a render from Blender (obviously, it’s not that good). It’s a three.js app built with Toolcraft. Available on the web and rendered in real time(link in the comments). But Blender still has a lot to do with it. Blender has Geometry Nodes - a powerful node-based system for creating and manipulating procedural geometry. In other words, it’s math. And math is a universal language. And who do you think is pretty good at math? >>> AI. Now you can download or buy Blender files from marketplaces, and when they contain Geometry Nodes for procedural animations, objects, surfaces, or effects, you can transfer that logic to the web. Make it real-time, make it interactive. Materials are a separate story, of course. They can still suck unless you use the right tricks: PBR, HDRIs, material blending, displacement, and faked surface relief. So why is Blender important here? Blender is open source, and many tools around it are open source too. An AI trained on their code. That means it can translate the math from one environment to another quite accurately. If you’ve been struggling to reproduce some idea with AI that you had in your head or seen in some references, and it has something to do with Geometry Nodes, and you can find that idea or a close one in the Blender ecosystem - it means you can transfer it to the web. Thank me later.
0:11

If you think this is just another silly demo made with AI, read this post. You might change your mind, because this demo is about MATH. What you see on the screen is not a render from Blender (obviously, it’s not that good). It’s a three.js app built with Toolcraft. Available on the web and rendered in real time(link in the comments). But Blender still has a lot to do with it. Blender has Geometry Nodes - a powerful node-based system for creating and manipulating procedural geometry. In other words, it’s math. And math is a universal language. And who do you think is pretty good at math? >>> AI. Now you can download or buy Blender files from marketplaces, and when they contain Geometry Nodes for procedural animations, objects, surfaces, or effects, you can transfer that logic to the web. Make it real-time, make it interactive. Materials are a separate story, of course. They can still suck unless you use the right tricks: PBR, HDRIs, material blending, displacement, and faked surface relief. So why is Blender important here? Blender is open source, and many tools around it are open source too. An AI trained on their code. That means it can translate the math from one environment to another quite accurately. If you’ve been struggling to reproduce some idea with AI that you had in your head or seen in some references, and it has something to do with Geometry Nodes, and you can find that idea or a close one in the Blender ecosystem - it means you can transfer it to the web. Thank me later.

Alex Barashkov

28,090 görüntüleme • 23 gün önce

Tested Claude + Blender today with two real workflows. Sharing what actually happened. First one was a simple demo. Gave it one sentence to build a cyberpunk room. Geometry, lighting, camera, render. It got there, though not everything in the prompt landed perfectly. Good enough to show the concept, not a stress test. Second one was more interesting. Threw a raw photogrammetry scan at it. Massey Ferguson tractor, 250k faces, grass background everywhere, debris floating all over the place. Asked Claude to clean it up autonomously. It did the work. Removed 106 floating chunks, cut face count by 87%, stripped the grass, flipped the model upright, set up studio lighting and rendered. Technically it worked. But honest answer: the result wasn't clean enough for production. This kind of cleanup still needs the right tools and someone who knows what they're doing. So here's where it actually fits. Not the precise technical stuff. The setup work. The repetitive stuff. The things that take forever if you don't already know Blender. It won't replace your 3D artist. It replaces the boring part before they start.
0:11

Tested Claude + Blender today with two real workflows. Sharing what actually happened. First one was a simple demo. Gave it one sentence to build a cyberpunk room. Geometry, lighting, camera, render. It got there, though not everything in the prompt landed perfectly. Good enough to show the concept, not a stress test. Second one was more interesting. Threw a raw photogrammetry scan at it. Massey Ferguson tractor, 250k faces, grass background everywhere, debris floating all over the place. Asked Claude to clean it up autonomously. It did the work. Removed 106 floating chunks, cut face count by 87%, stripped the grass, flipped the model upright, set up studio lighting and rendered. Technically it worked. But honest answer: the result wasn't clean enough for production. This kind of cleanup still needs the right tools and someone who knows what they're doing. So here's where it actually fits. Not the precise technical stuff. The setup work. The repetitive stuff. The things that take forever if you don't already know Blender. It won't replace your 3D artist. It replaces the boring part before they start.

KIRI Engine - 3D Scanner App

61,093 görüntüleme • 3 ay önce

I just built a skill that lets Claude Code watch & analyze ANY video 🤯 Drop in any video file — UGC ads, competitor Meta ads, organic TikToks, screen recordings — and Claude hands you back a full creative teardown. All inside Claude Code. Perfect for media buyers and creative strategists who reverse-engineer competitor ads every week — and lose half a day doing it by hand. If your creative process starts with studying what's already working, you're scrubbing through competitor ads frame by frame, pausing to write down every hook, screenshotting the on-screen text, and by the tenth video you can't remember what made the first one land... This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: → Native video understanding via Gemini (not just transcripts) → Structured analysis — hook, angle, audience, pain point, CTA → Verbatim on-screen text and dialogue with timestamps → Hook variations generated directly from competitor ads → About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this, and I'm giving away the skill for free. Want the skill? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)
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I just built a skill that lets Claude Code watch & analyze ANY video 🤯 Drop in any video file — UGC ads, competitor Meta ads, organic TikToks, screen recordings — and Claude hands you back a full creative teardown. All inside Claude Code. Perfect for media buyers and creative strategists who reverse-engineer competitor ads every week — and lose half a day doing it by hand. If your creative process starts with studying what's already working, you're scrubbing through competitor ads frame by frame, pausing to write down every hook, screenshotting the on-screen text, and by the tenth video you can't remember what made the first one land... This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: → Native video understanding via Gemini (not just transcripts) → Structured analysis — hook, angle, audience, pain point, CTA → Verbatim on-screen text and dialogue with timestamps → Hook variations generated directly from competitor ads → About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this, and I'm giving away the skill for free. Want the skill? > Like this post > Comment "CLAUDE" And I'll send it over (must be following so I can DM)

Mike Futia

41,448 görüntüleme • 1 ay önce

World Model is trending— let's revisit our HunyuanWorld journey. We’ve been pioneering open-source 3D world generation in the past two months, and this ride’s only getting started. 🌍 📅 July: HunyuanWorld 1.0 📌 First open-source 3D world model compatible with CG pipelines (Unity/Unreal/Blender) 📌 Hit 2K+ GitHub stars in just two months ⭐—thank you for the love! 📅 August: 1.0-Lite 📌Same top-tier quality, running on consumer GPUs! 📅 September: 1.0-Voyager 📌 Direct 3D output + world memory—taking exploration further! Seamlessly integrated into CG pipelines with layered 3D modeling (assets, terrain, skybox) and fully open-sourced.. we’re fully committed to building open-source spatial intelligence for all! 🚀 💡 Why it matters? ✅ Seamless CG Pipeline Integration: Export generated 3D scenes as standard mesh formats, effortlessly integrating into industry-standard tools like Blender, Unity, and Unreal Engine for direct editing, animation, and physical simulation. ✅ Hierarchical Scene Editing: Deconstruct scenes into semantic layers (sky, background, foreground objects) via instance recognition and layer decomposition, allowing for atomic-level control—independently modify, relocate, or replace objects without rebuilding the entire world. Project page: Github: Amazing creations by Stijn Spanhove camenduru GENEL | AIを用いた動画制作 apolinario 🌐 とりにく Directive Creator 🪥 👇 #AI #3DGeneration #OpenSource #WorldModels #Hunyuan3D #HunyuanWorld
0:28

World Model is trending— let's revisit our HunyuanWorld journey. We’ve been pioneering open-source 3D world generation in the past two months, and this ride’s only getting started. 🌍 📅 July: HunyuanWorld 1.0 📌 First open-source 3D world model compatible with CG pipelines (Unity/Unreal/Blender) 📌 Hit 2K+ GitHub stars in just two months ⭐—thank you for the love! 📅 August: 1.0-Lite 📌Same top-tier quality, running on consumer GPUs! 📅 September: 1.0-Voyager 📌 Direct 3D output + world memory—taking exploration further! Seamlessly integrated into CG pipelines with layered 3D modeling (assets, terrain, skybox) and fully open-sourced.. we’re fully committed to building open-source spatial intelligence for all! 🚀 💡 Why it matters? ✅ Seamless CG Pipeline Integration: Export generated 3D scenes as standard mesh formats, effortlessly integrating into industry-standard tools like Blender, Unity, and Unreal Engine for direct editing, animation, and physical simulation. ✅ Hierarchical Scene Editing: Deconstruct scenes into semantic layers (sky, background, foreground objects) via instance recognition and layer decomposition, allowing for atomic-level control—independently modify, relocate, or replace objects without rebuilding the entire world. Project page: Github: Amazing creations by Stijn Spanhove camenduru GENEL | AIを用いた動画制作 apolinario 🌐 とりにく Directive Creator 🪥 👇 #AI #3DGeneration #OpenSource #WorldModels #Hunyuan3D #HunyuanWorld

Tencent HY

20,178 görüntüleme • 10 ay önce

Burned 200k tokens just for "animations" and still AI couldn't do it well. I tried one of the expert animation design engineer's, Emil Kowalski's Agent Skill on my website to improve animation using Grok 4.5 It analyzed the UI, found issues, came up with a good plan, and iterated multiple times. The end result actually made parts of the UX worse. Also, it never suggested the animation experience I had in mind. So I explained exactly how I wanted it to feel. It got much closer, but still missed details like applying the same animation during keyboard navigation between cards. That silly. The lesson isn't about the model or the Agent Skill. But it's about, "Even the strongest models can't infer your taste yet." They can't and won't suggest it. AI only executes. You have to define the experience with enough details for it to execute. Otherwise, you'll end up with something that's almost okay, but still not what you wanted
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Burned 200k tokens just for "animations" and still AI couldn't do it well. I tried one of the expert animation design engineer's, Emil Kowalski's Agent Skill on my website to improve animation using Grok 4.5 It analyzed the UI, found issues, came up with a good plan, and iterated multiple times. The end result actually made parts of the UX worse. Also, it never suggested the animation experience I had in mind. So I explained exactly how I wanted it to feel. It got much closer, but still missed details like applying the same animation during keyboard navigation between cards. That silly. The lesson isn't about the model or the Agent Skill. But it's about, "Even the strongest models can't infer your taste yet." They can't and won't suggest it. AI only executes. You have to define the experience with enough details for it to execute. Otherwise, you'll end up with something that's almost okay, but still not what you wanted

The Bugged Dev

25,641 görüntüleme • 27 gün önce

This is some quietly impressive work on making video world models actually controllable in 4D space. VerseCrafter lets you take an input image, use something like Blender to animate the 3D camera path and object trajectories, then uses that to condition generation. Scribbling in 2D feels so crude in comparison. The authors represent everything in a shared 4D world state - static background as a point cloud, moving objects as 3D gaussian trajectories. The gaussians are an interesting choice because they capture position, shape, and orientation probabilistically rather than forcing rigid bounding boxes or category specific models like SMPL-X for human bodies. They bolt this onto frozen Wan2.1 with a lightweight adapter, so they get a strong video prior. They also built a pipeline to auto extract 4D annotations from real world videos to train this puppy. It doesn't look sexy yet, but IMO this is the interface video world models need - actual 3D authoring tools to exert control rather than crude scribbles and prompt incantations.
0:17

This is some quietly impressive work on making video world models actually controllable in 4D space. VerseCrafter lets you take an input image, use something like Blender to animate the 3D camera path and object trajectories, then uses that to condition generation. Scribbling in 2D feels so crude in comparison. The authors represent everything in a shared 4D world state - static background as a point cloud, moving objects as 3D gaussian trajectories. The gaussians are an interesting choice because they capture position, shape, and orientation probabilistically rather than forcing rigid bounding boxes or category specific models like SMPL-X for human bodies. They bolt this onto frozen Wan2.1 with a lightweight adapter, so they get a strong video prior. They also built a pipeline to auto extract 4D annotations from real world videos to train this puppy. It doesn't look sexy yet, but IMO this is the interface video world models need - actual 3D authoring tools to exert control rather than crude scribbles and prompt incantations.

Bilawal Sidhu

25,802 görüntüleme • 6 ay önce

Claude Code can now watch & analyze ANY video 🤯 I built a skill that gives Claude the ability to watch any video file you drop in — UGC ads, competitor Meta ads, organic TikToks, screen recordings, anything. All inside Claude Code. Perfect for DTC brands and agencies who study competitor creative every week to figure out what's working and what to test next. Here's the problem: If you're studying competitor ads on Meta or hooks on TikTok, you're scrubbing through videos manually, pausing to write down hooks, screenshotting on-screen text, and trying to remember what made the ad land by the time you've watched 10 of them. This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: - Native video understanding via Gemini (not just transcripts) - Structured analysis — hook, angle, audience, pain point, CTA - Verbatim on-screen text and dialogue with timestamps - Hook variations generated directly from competitor ads - About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this and I'm giving away the skill for free. Want the skill? > Comment "CLAUDE" + > Like this post And I'll send it over (must be following so I can DM)
0:19

Claude Code can now watch & analyze ANY video 🤯 I built a skill that gives Claude the ability to watch any video file you drop in — UGC ads, competitor Meta ads, organic TikToks, screen recordings, anything. All inside Claude Code. Perfect for DTC brands and agencies who study competitor creative every week to figure out what's working and what to test next. Here's the problem: If you're studying competitor ads on Meta or hooks on TikTok, you're scrubbing through videos manually, pausing to write down hooks, screenshotting on-screen text, and trying to remember what made the ad land by the time you've watched 10 of them. This skill solves it: → Drop any video file into Claude Code → Skill routes it through the Gemini API for native video understanding → Returns a full creative teardown — hook breakdown, target audience, angle, beat-by-beat, on-screen text verbatim → Surfaces the steal-worthy patterns you can apply to your own creative → Same skill works on UGC ads, produced video ads, organic TikToks, and Loom recordings No manual scrubbing. No pausing every 5 seconds. No $200/mo ad intelligence platform. What you get: - Native video understanding via Gemini (not just transcripts) - Structured analysis — hook, angle, audience, pain point, CTA - Verbatim on-screen text and dialogue with timestamps - Hook variations generated directly from competitor ads - About 27 cents per 30-minute video Built 100% in Claude Code with the Gemini API. I recorded a full breakdown showing exactly how I built this and I'm giving away the skill for free. Want the skill? > Comment "CLAUDE" + > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

35,661 görüntüleme • 3 ay önce

Claude Cowork Sub-Agents are f*cking cracked 🤯 One prompt → 50 competitor ads analyzed, hooks extracted, and a full creative brief generated. 10 AI agents running in parallel, under 5 minutes. All inside Claude Cowork. Perfect for DTC brands and agencies who are still doing creative research and ad production one task at a time inside Claude. If you're analyzing competitor ads one by one, copying hooks into a spreadsheet manually, writing brief after brief from scratch, and watching Claude's output quality fall off a cliff after the 15th variation because the context window is completely bloated... Sub-agents eliminate the entire bottleneck: → Drop in a spreadsheet of 50 competitor ads and spin up 10 parallel sub-agents → Each sub-agent analyzes 5 ads simultaneously — hooks, angles, CTAs, emotional tone, creative format → They report structured summaries back to the main agent without bloating the context → The main agent synthesizes patterns across all 50 ads into a competitive intel brief → Then spin up another round of sub-agents to generate 30 ad copy variations across 10 personas → Each sub-agent writes for 1-2 personas in a fresh context — so variation 30 is as sharp as variation 1 No analyzing ads one at a time. No context window blowing up halfway through. No copy quality degrading after the first dozen variations. What this gives you: → 50 competitor ads broken down in minutes — hooks, angles, CTAs, formats, all structured → Pattern analysis across the full dataset that you'd miss reviewing ads individually → 30+ ad copy variations with persona-specific messaging that actually stays sharp → A workflow you can save as reusable skills and trigger with one command next time → The same output quality on the last task as the first Built 100% inside Claude Cowork with sub-agents. I put together a full DTC playbook: 5 bulk workflows with copy-paste prompts, the exact sub-agent prompting pattern, batching guidelines, and an honest breakdown of when this setup is worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)
0:10

Claude Cowork Sub-Agents are f*cking cracked 🤯 One prompt → 50 competitor ads analyzed, hooks extracted, and a full creative brief generated. 10 AI agents running in parallel, under 5 minutes. All inside Claude Cowork. Perfect for DTC brands and agencies who are still doing creative research and ad production one task at a time inside Claude. If you're analyzing competitor ads one by one, copying hooks into a spreadsheet manually, writing brief after brief from scratch, and watching Claude's output quality fall off a cliff after the 15th variation because the context window is completely bloated... Sub-agents eliminate the entire bottleneck: → Drop in a spreadsheet of 50 competitor ads and spin up 10 parallel sub-agents → Each sub-agent analyzes 5 ads simultaneously — hooks, angles, CTAs, emotional tone, creative format → They report structured summaries back to the main agent without bloating the context → The main agent synthesizes patterns across all 50 ads into a competitive intel brief → Then spin up another round of sub-agents to generate 30 ad copy variations across 10 personas → Each sub-agent writes for 1-2 personas in a fresh context — so variation 30 is as sharp as variation 1 No analyzing ads one at a time. No context window blowing up halfway through. No copy quality degrading after the first dozen variations. What this gives you: → 50 competitor ads broken down in minutes — hooks, angles, CTAs, formats, all structured → Pattern analysis across the full dataset that you'd miss reviewing ads individually → 30+ ad copy variations with persona-specific messaging that actually stays sharp → A workflow you can save as reusable skills and trigger with one command next time → The same output quality on the last task as the first Built 100% inside Claude Cowork with sub-agents. I put together a full DTC playbook: 5 bulk workflows with copy-paste prompts, the exact sub-agent prompting pattern, batching guidelines, and an honest breakdown of when this setup is worth it vs. when a simpler approach is the better move. Want it for free? > Like this post > Comment "AGENTS" And I'll send it over (must be following so I can DM)

Mike Futia

50,114 görüntüleme • 5 ay önce

A $35,000 WEBSITE IS SOLD ON 3 LIES. FABLE 5 + HIGGSFIELD JUST EXPOSED ALL THREE. every agency invoice rests on three things they'd rather you never question. here they are: → LIE 1: "custom animation takes weeks." it takes one prompt. Claude writes the GSAP ScrollTrigger + Lenis timelines - pinned sections, scrubbed video, reveals that land. zero hand-coded keyframes. → LIE 2: "cinematic visuals need a motion artist on retainer." they don't. Higgsfield pulls hero clips, transitions, and ambient loops from 30+ generative models, matched to your story - not stock everyone's seen. → LIE 3: "the polish is where your money goes." film grain, particles, vignette, glass cards, color tints - baked in, no config, no designer. the exact thing they bill a specialist for. strip the three lies and what's left is a Claude sub and a few dollars of credits. CONNECT HIGGSFIELD (MCP): add it as a custom connector in Claude Code: - mcp_servers: - higgsfield: - url: " one OAuth flow. Claude generates and pulls clips directly - no exporting by hand. THE MATH: → what a studio charges: $6,000-$35,000+ → what it costs you: a Claude sub + a few dollars of Higgsfield credits → what it takes: 4 people + 3 weeks → 1 operator + 1 session the studio never sold you skill. it sold you three things it hoped you'd never check. Follow me, reply "GHOST" and I'll send you the full step-by-step Playbook. full breakdown in the article 👇
0:13

A $35,000 WEBSITE IS SOLD ON 3 LIES. FABLE 5 + HIGGSFIELD JUST EXPOSED ALL THREE. every agency invoice rests on three things they'd rather you never question. here they are: → LIE 1: "custom animation takes weeks." it takes one prompt. Claude writes the GSAP ScrollTrigger + Lenis timelines - pinned sections, scrubbed video, reveals that land. zero hand-coded keyframes. → LIE 2: "cinematic visuals need a motion artist on retainer." they don't. Higgsfield pulls hero clips, transitions, and ambient loops from 30+ generative models, matched to your story - not stock everyone's seen. → LIE 3: "the polish is where your money goes." film grain, particles, vignette, glass cards, color tints - baked in, no config, no designer. the exact thing they bill a specialist for. strip the three lies and what's left is a Claude sub and a few dollars of credits. CONNECT HIGGSFIELD (MCP): add it as a custom connector in Claude Code: - mcp_servers: - higgsfield: - url: " one OAuth flow. Claude generates and pulls clips directly - no exporting by hand. THE MATH: → what a studio charges: $6,000-$35,000+ → what it costs you: a Claude sub + a few dollars of Higgsfield credits → what it takes: 4 people + 3 weeks → 1 operator + 1 session the studio never sold you skill. it sold you three things it hoped you'd never check. Follow me, reply "GHOST" and I'll send you the full step-by-step Playbook. full breakdown in the article 👇

ZEUS⚡️

32,378 görüntüleme • 22 gün önce

LLM Artifacts Connected to Andrej Karpathy's LLM Knowledge base idea, I've been building out a fun way to generate dynamic artifacts from these knowledge bases with the goal of discovering and revealing meaningful and deeper insights. LLM KBs are hard to consume for humans, as I think they are more built for agents. So the question is, what form would be useful for humans to take actions and make important decisions? That's what I am trying to figure out with these artifacts. The artifact example shows a pulse on HN discussions around AI-related stories. The insights can go deeper, of course, but this is already super fun and thought-provoking, like some of my favorite podcasts. The format and depth matter a lot. The aggregation skills of agents are outstanding if you tune the prompts and skill carefully. I built this artifact generator in a few minutes through an agent skill, but I feel like there are so many ways that LLM-generated information can be used and consumed. Like generating deeper insights and analysis, and things that are just not feasible for humans today. The generated artifact (including its data and design) serves as reusable templates or can be updated in real-time via auomations, which is something I am also working on. It is truly an insane way to monitor and track information. Better than a newsletter. Better than newspapers. There is something about this that gets me really excited about the future of AI agents for knowledge generation and discovery. Lots of hidden gems everywhere just waiting to be discovered and acted on if the information is presented correctly. This is not perfect. The format, style/prose can be improved, but this is easy to customize via skill. You can personalize it to your liking. I feel like these dynamic artifacts are going to emerge as a strong new medium to stay on the cutting edge of things, both for agents and humans. My target is research, of course. This was just a basic example. Besides animation, I am also targeting other components like voice, videos, images, slides, etc. This space is full of opportunities to explore. Skill for this coming soon.
0:18

LLM Artifacts Connected to Andrej Karpathy's LLM Knowledge base idea, I've been building out a fun way to generate dynamic artifacts from these knowledge bases with the goal of discovering and revealing meaningful and deeper insights. LLM KBs are hard to consume for humans, as I think they are more built for agents. So the question is, what form would be useful for humans to take actions and make important decisions? That's what I am trying to figure out with these artifacts. The artifact example shows a pulse on HN discussions around AI-related stories. The insights can go deeper, of course, but this is already super fun and thought-provoking, like some of my favorite podcasts. The format and depth matter a lot. The aggregation skills of agents are outstanding if you tune the prompts and skill carefully. I built this artifact generator in a few minutes through an agent skill, but I feel like there are so many ways that LLM-generated information can be used and consumed. Like generating deeper insights and analysis, and things that are just not feasible for humans today. The generated artifact (including its data and design) serves as reusable templates or can be updated in real-time via auomations, which is something I am also working on. It is truly an insane way to monitor and track information. Better than a newsletter. Better than newspapers. There is something about this that gets me really excited about the future of AI agents for knowledge generation and discovery. Lots of hidden gems everywhere just waiting to be discovered and acted on if the information is presented correctly. This is not perfect. The format, style/prose can be improved, but this is easy to customize via skill. You can personalize it to your liking. I feel like these dynamic artifacts are going to emerge as a strong new medium to stay on the cutting edge of things, both for agents and humans. My target is research, of course. This was just a basic example. Besides animation, I am also targeting other components like voice, videos, images, slides, etc. This space is full of opportunities to explore. Skill for this coming soon.

elvis

31,242 görüntüleme • 3 ay önce

Claude + Apify MCP is insane 🤯 This setup allows you to chat with TikTok and Instagram Reels data in natural language. All inside Claude Desktop. Perfect for DTC brands & agencies who need fresh creative angles fast. Here's the problem: You want to know what hooks are working in your niche. But that means hours of scrolling, screenshot folders, and spreadsheets you'll never look at again. This Claude MCP setup solves it: → Ask Claude to scrape 10 viral IG Reels in your niche → It pulls transcripts, engagement, and comments automatically → Then you just... chat with the data → "What pain points keep coming up?" → "Give me the top 5 hooks from these videos" → "What emotional triggers are driving engagement?" No automations. No exports. No learning new tools. What you get: - Instant access to viral content data - Natural language questions, instant answers - Hook formulas backed by millions of views - A full report in under 3 minutes Just ask Claude like you're talking to a research assistant who already watched 100 videos. I recorded a full 11-minute breakdown showing you how to set this up step-by-step. Want access? > Like this post > Comment "CHAT" And I'll sent it right over (must be following so I can DM)
0:20

Claude + Apify MCP is insane 🤯 This setup allows you to chat with TikTok and Instagram Reels data in natural language. All inside Claude Desktop. Perfect for DTC brands & agencies who need fresh creative angles fast. Here's the problem: You want to know what hooks are working in your niche. But that means hours of scrolling, screenshot folders, and spreadsheets you'll never look at again. This Claude MCP setup solves it: → Ask Claude to scrape 10 viral IG Reels in your niche → It pulls transcripts, engagement, and comments automatically → Then you just... chat with the data → "What pain points keep coming up?" → "Give me the top 5 hooks from these videos" → "What emotional triggers are driving engagement?" No automations. No exports. No learning new tools. What you get: - Instant access to viral content data - Natural language questions, instant answers - Hook formulas backed by millions of views - A full report in under 3 minutes Just ask Claude like you're talking to a research assistant who already watched 100 videos. I recorded a full 11-minute breakdown showing you how to set this up step-by-step. Want access? > Like this post > Comment "CHAT" And I'll sent it right over (must be following so I can DM)

Mike Futia

17,757 görüntüleme • 8 ay önce

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.
0:33

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

37,201 görüntüleme • 5 ay önce