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The pipeline optimisation for brands' visuals Batch image production in 1 window: 〰️ take the image 〰️ rotate the virtual camera 〰️ take shots 〰️ edit & upscale 〰️ resize aspect ratios if needed 〰️ download -> finalise in Figma / Ps One designer becomes a factory 👇

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AmirMušić

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19,864 views • 5 months ago •via X (Twitter)

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Rive Editor 0.8.5321 is live. One of our biggest updates yet: 🌐 Global View Models 🔀 Shape Builder 〰️ Motion Path editing on the stage 🔑 Multi-keyframe editing ⭐ Favorites & pinned projects Full breakdown in the thread 👇
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Rive Editor 0.8.5321 is live. One of our biggest updates yet: 🌐 Global View Models 🔀 Shape Builder 〰️ Motion Path editing on the stage 🔑 Multi-keyframe editing ⭐ Favorites & pinned projects Full breakdown in the thread 👇

Rive

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Best harvest of the season! 🎃 For this clip I used Topaz for Web's new video tools. Topaz for Web is Topaz Labs Topaz Labs first upscaling and enhancement tool for both images and video; all in one browser window, with no complex system requirements or app download needed. Upscale, enhance, adjust frame rate (video), and create new detail in every image and video you create. Extra info and slider vid below 👇
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Best harvest of the season! 🎃 For this clip I used Topaz for Web's new video tools. Topaz for Web is Topaz Labs Topaz Labs first upscaling and enhancement tool for both images and video; all in one browser window, with no complex system requirements or app download needed. Upscale, enhance, adjust frame rate (video), and create new detail in every image and video you create. Extra info and slider vid below 👇

awesome_visuals

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One image. Multiple premium ad concepts. Fotor lets you take a simple product photo and turn it into polished commercial-style content that feels like it belongs in a luxury brand campaign. From extreme close-up details to premium product showcases and cinematic motion shots, you can create completely different visuals from the same reference. What used to require a studio, camera crew, lighting setup, and hours of production can now be done with AI. Product marketing is moving beyond static images. The real game is creating visuals that stop the scroll and make people remember the product.
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One image. Multiple premium ad concepts. Fotor lets you take a simple product photo and turn it into polished commercial-style content that feels like it belongs in a luxury brand campaign. From extreme close-up details to premium product showcases and cinematic motion shots, you can create completely different visuals from the same reference. What used to require a studio, camera crew, lighting setup, and hours of production can now be done with AI. Product marketing is moving beyond static images. The real game is creating visuals that stop the scroll and make people remember the product.

Hope Ai

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🚀 Photo to Video Ads is now live on Pollo AI Turn any product photo into scroll-stopping video ads in seconds. No camera. No crew. No editing. Built for e-commerce brands, Shopify sellers, and modern DTC marketers in beauty, fashion, and beyond. Here’s a real example — a Laneige Lip Sleeping Mask ad generated from just one product image 👇 Want pro-level product videos for your store? Download the Pollo AI App now. Check the comments for the download link and quick access 👇 #Ecommerce #ProductAds #VideoAds #Shopify #AdCreatives #DigitalMarketing #SocialCommerce
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🚀 Photo to Video Ads is now live on Pollo AI Turn any product photo into scroll-stopping video ads in seconds. No camera. No crew. No editing. Built for e-commerce brands, Shopify sellers, and modern DTC marketers in beauty, fashion, and beyond. Here’s a real example — a Laneige Lip Sleeping Mask ad generated from just one product image 👇 Want pro-level product videos for your store? Download the Pollo AI App now. Check the comments for the download link and quick access 👇 #Ecommerce #ProductAds #VideoAds #Shopify #AdCreatives #DigitalMarketing #SocialCommerce

ZoAina_AI

14,019 views • 3 months ago

📖THE STEP MOST CREATORS SKIP IS WHY THEIR AI ANIMATION LOOKS INCONSISTENT Consistency across clips doesn't come from prompting — it comes from the reference image. The pipeline, step by step: ▪ Start with ChatGPT Image 2 — generate a full character design sheet first, not just a single frame. Multiple angles, expressions, and outfit variations in one image keeps the character consistent across every scene ▪ Build a storyboard inside ChatGPT Image 2 as well — define each shot, camera angle, action, and mood before touching Seedance at all. This is the step most people skip and it's the reason clips look disconnected ▪ Define a color palette and lighting mood early — golden afternoon light, soft warm tones, dramatic shadows. Lock those values and repeat them across every prompt ▪ Take each storyboard frame into Seedance 2.0 as the reference image — one frame becomes one clip ▪ Write the Seedance prompt around the character action, not the scene description. The scene is already in the image. The prompt handles motion, camera behavior, and timing ▪ Keep clip duration between 4-6 seconds per shot — shorter clips give more control over pacing and reduce motion drift on character faces ▪ Match camera movement type across consecutive clips — if one shot dollies in, the next should hold or pull back, not dolly again The consistency across these frames comes from the character design sheet, not from luck. Seedance reads the reference image and the prompt together — if the reference is detailed enough, the output stays on-model. This video was created by ALOKXMEHTA 📥 tomorrow: the exact ChatGPT Image 2 prompt structure used to generate a multi-angle character design sheet like this one 🔖One article covers the entire workflow — it is pinned below, do not scroll past it.
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📖THE STEP MOST CREATORS SKIP IS WHY THEIR AI ANIMATION LOOKS INCONSISTENT Consistency across clips doesn't come from prompting — it comes from the reference image. The pipeline, step by step: ▪ Start with ChatGPT Image 2 — generate a full character design sheet first, not just a single frame. Multiple angles, expressions, and outfit variations in one image keeps the character consistent across every scene ▪ Build a storyboard inside ChatGPT Image 2 as well — define each shot, camera angle, action, and mood before touching Seedance at all. This is the step most people skip and it's the reason clips look disconnected ▪ Define a color palette and lighting mood early — golden afternoon light, soft warm tones, dramatic shadows. Lock those values and repeat them across every prompt ▪ Take each storyboard frame into Seedance 2.0 as the reference image — one frame becomes one clip ▪ Write the Seedance prompt around the character action, not the scene description. The scene is already in the image. The prompt handles motion, camera behavior, and timing ▪ Keep clip duration between 4-6 seconds per shot — shorter clips give more control over pacing and reduce motion drift on character faces ▪ Match camera movement type across consecutive clips — if one shot dollies in, the next should hold or pull back, not dolly again The consistency across these frames comes from the character design sheet, not from luck. Seedance reads the reference image and the prompt together — if the reference is detailed enough, the output stays on-model. This video was created by ALOKXMEHTA 📥 tomorrow: the exact ChatGPT Image 2 prompt structure used to generate a multi-angle character design sheet like this one 🔖One article covers the entire workflow — it is pinned below, do not scroll past it.

Zentrix⌚️

14,015 views • 2 months ago

A single product image can now become a cinematic ad in minutes. Created with "𝐏𝐡𝐨𝐭𝐨 𝐭𝐨 𝐕𝐢𝐝𝐞𝐨 𝐀𝐝𝐬" on the Pollo AI mobile app. What used to take a full creative pipeline can now be turned into a polished, conversion-focused video ad in one workflow, making it especially useful for ecommerce sellers who need to launch and test creatives fast. AI advertising is accelerating.... See comment for a Prompt 👇
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A single product image can now become a cinematic ad in minutes. Created with "𝐏𝐡𝐨𝐭𝐨 𝐭𝐨 𝐕𝐢𝐝𝐞𝐨 𝐀𝐝𝐬" on the Pollo AI mobile app. What used to take a full creative pipeline can now be turned into a polished, conversion-focused video ad in one workflow, making it especially useful for ecommerce sellers who need to launch and test creatives fast. AI advertising is accelerating.... See comment for a Prompt 👇

Aneeza Ai

32,912 views • 4 months ago

She makes $3k + a month from AI UGC so real your brain thinks she’s human. Chopsticks to lips. Micro skin texture. Visible pores. Individual eyebrow hairs. Reflections in her eyes. You saw light and skin and decided she was real. She isn’t. The workflow: Strong reference image → Gemini Image-to-JSON → Nano Banana Pro base model → 8 shots → Kling 3.0 animation with start/end frames → CapCut stitch with keyframes for one continuous take. One model. Dozens of reusable assets. Brands pay $60–$100 each. Most creators still fight blurry faces. She built the system once and now it prints on repeat. Comment UGC for the full prompt chain.
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She makes $3k + a month from AI UGC so real your brain thinks she’s human. Chopsticks to lips. Micro skin texture. Visible pores. Individual eyebrow hairs. Reflections in her eyes. You saw light and skin and decided she was real. She isn’t. The workflow: Strong reference image → Gemini Image-to-JSON → Nano Banana Pro base model → 8 shots → Kling 3.0 animation with start/end frames → CapCut stitch with keyframes for one continuous take. One model. Dozens of reusable assets. Brands pay $60–$100 each. Most creators still fight blurry faces. She built the system once and now it prints on repeat. Comment UGC for the full prompt chain.

Rugikk

158,910 views • 2 months ago

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Midjourney sref + Sora 2 Pro is the sauce. With one Midjourney style image, you can give a specific style for your entire project. I created two different 12-second clips and edited them together. Some details aren’t fully consistent, like the iPod or AirPods because the clips were made separately from a single image (Character in a specific style). It could be fixed in post-production, but that would take more time, and this was more of an experimental test. It would be great to add the actual product image with the current one to maintain product consistency. I feel like if there were a way to add 2–4 images into this workflow, it could open up a lot more possibilities and consistency. With an API, it could be possible. Or let’s see what Veo 3.1 has to offer.

Allar Haltsonen

10,141 views • 11 months ago

This guy built an AI pipeline that generates hyperrealistic fashion models in 47 minutes and now dropshippers pay him $1,400 to clone the entire system. He got tired of watching e-com brands lose $8K per photoshoot when a single product angle changed so he built a 9-node workflow that generates 127 product videos from one Pinterest photo without hiring a single model. Here's the exact breakdown: → Claude writes a 34-parameter JSON brand DNA before any image is touched target psychographics, price anchor, vibe matrix, anti-inspiration blacklist → Pinterest becomes the model source library but you can't just download and animate → Kling 2.6 takes that static JPG and turns it into 5-second video but only after the prompt architecture is locked → Negative prompt node runs 41 exclusion terms: no plastic skin, no CGI glow, no symmetry artifacts, no doll face, no synthetic lighting → That one step kills the "AI look" that tanks engagement by 67% in the first 3 seconds → TikTok Studio uploads 19 videos in one batch with zero manual captioning because the brand voice was pre-programmed in step one → Atlas scrapes Amazon product links and auto-generates a Shopify store with hero images, pricing tiers, scarcity copy, and mobile-optimized checkout in 90 seconds → The store goes live before the first TikTok video finishes processing The key move 94% of people skip: you can't animate the photo before you inject the negative prompt. If you send a raw Pinterest image straight into image-to-video the face morphs into a wax figure. The fabric loses texture. The hands grow extra fingers. The whole thing screams "AI" and your CTR dies. His system runs the exclusion filter first so the model moves like she's shot on an iPhone 15 Pro in natural light. One brand hit 2.6M views on TikTok in 11 days with zero paid ads and converted at 3.7% because the videos looked like organic UGC not polished studio content. Brands now pay him $1,400 for the full pipeline setup + $340/month to keep the store synced with new product drops and seasonal video batches. The entire system runs on $23/month in API costs and one laptop. No photographer. No model agency. No product samples. Just a prompt template, a Pinterest account, and the discipline to filter out the AI artifacts before you render movement.
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This guy built an AI pipeline that generates hyperrealistic fashion models in 47 minutes and now dropshippers pay him $1,400 to clone the entire system. He got tired of watching e-com brands lose $8K per photoshoot when a single product angle changed so he built a 9-node workflow that generates 127 product videos from one Pinterest photo without hiring a single model. Here's the exact breakdown: → Claude writes a 34-parameter JSON brand DNA before any image is touched target psychographics, price anchor, vibe matrix, anti-inspiration blacklist → Pinterest becomes the model source library but you can't just download and animate → Kling 2.6 takes that static JPG and turns it into 5-second video but only after the prompt architecture is locked → Negative prompt node runs 41 exclusion terms: no plastic skin, no CGI glow, no symmetry artifacts, no doll face, no synthetic lighting → That one step kills the "AI look" that tanks engagement by 67% in the first 3 seconds → TikTok Studio uploads 19 videos in one batch with zero manual captioning because the brand voice was pre-programmed in step one → Atlas scrapes Amazon product links and auto-generates a Shopify store with hero images, pricing tiers, scarcity copy, and mobile-optimized checkout in 90 seconds → The store goes live before the first TikTok video finishes processing The key move 94% of people skip: you can't animate the photo before you inject the negative prompt. If you send a raw Pinterest image straight into image-to-video the face morphs into a wax figure. The fabric loses texture. The hands grow extra fingers. The whole thing screams "AI" and your CTR dies. His system runs the exclusion filter first so the model moves like she's shot on an iPhone 15 Pro in natural light. One brand hit 2.6M views on TikTok in 11 days with zero paid ads and converted at 3.7% because the videos looked like organic UGC not polished studio content. Brands now pay him $1,400 for the full pipeline setup + $340/month to keep the store synced with new product drops and seasonal video batches. The entire system runs on $23/month in API costs and one laptop. No photographer. No model agency. No product samples. Just a prompt template, a Pinterest account, and the discipline to filter out the AI artifacts before you render movement.

Shade

537,458 views • 4 months ago

“The Impossible” 1964 shot that reportedly left Martin Scorsese speechless. This stunning sequence from the 1964 film I Am Cuba (Soy Cuba) is still regarded as one of the most technically daring shots ever captured on camera. Long before CGI or stabilized drone systems existed, director Mikhail Kalatozov and cinematographer Sergey Urusevsky engineered the sequence using elaborate rigs of cables, pulleys, and custom-built camera setups. The camera begins at street level, ascends the exterior of a building, moves through a cigar factory, and then glides out over the city in a single continuous take, creating a fluid, gravity-defying movement that feels strikingly modern even by today’s standards. The shot is also renowned for its surreal visual quality. Shot on specialized infrared film, the vegetation appears almost luminous white against a deep black sky, giving the image an otherworldly, dreamlike atmosphere. Initially overlooked as Cold War propaganda, the film was rediscovered decades later and restored in the 1990s, after filmmakers like Martin Scorsese and Francis Ford Coppola praised its extraordinary craftsmanship. Even now, it remains a benchmark for what’s possible in practical cinematography.
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“The Impossible” 1964 shot that reportedly left Martin Scorsese speechless. This stunning sequence from the 1964 film I Am Cuba (Soy Cuba) is still regarded as one of the most technically daring shots ever captured on camera. Long before CGI or stabilized drone systems existed, director Mikhail Kalatozov and cinematographer Sergey Urusevsky engineered the sequence using elaborate rigs of cables, pulleys, and custom-built camera setups. The camera begins at street level, ascends the exterior of a building, moves through a cigar factory, and then glides out over the city in a single continuous take, creating a fluid, gravity-defying movement that feels strikingly modern even by today’s standards. The shot is also renowned for its surreal visual quality. Shot on specialized infrared film, the vegetation appears almost luminous white against a deep black sky, giving the image an otherworldly, dreamlike atmosphere. Initially overlooked as Cold War propaganda, the film was rediscovered decades later and restored in the 1990s, after filmmakers like Martin Scorsese and Francis Ford Coppola praised its extraordinary craftsmanship. Even now, it remains a benchmark for what’s possible in practical cinematography.

Historic Vids

293,235 views • 4 months ago

Claude + GPT Image 2 + seedance + Meta ads MCP Replaced my 10k/month performance marketing agency Here's the exact stack (and how it works): Step 1: Research Feed Claude your product URL, your competitors' URLs, and your top-performing ad angles. It builds your full brand brief + competitor intelligence in minutes. No agency strategist needed. Step 2: Static ads in seconds Claude writes image generation prompts based on your brief. Those prompts go straight into GPT Image 2. Out comes scroll-stopping creative. Batched. On-brand. No designer. Step 3: Video ads that convert Claude writes video prompts. Those go into Seedance 2.0. UGC-style videos. AI actor formats. Product showcases. All generated, not filmed. (Both GPT Image 2 + Seedance are live on HeyOz right now.) Step 4: Publish + optimize on autopilot Connect Claude to Meta Ads MCP. It publishes your creatives, monitors performance, and keeps iterating. Your agency was charging you for this. This entire workflow is documented in a guide I put together, covering prompts, setup, and the exact MCP config. Why this matters: Most brands are still paying for slow, expensive creative production. The ones who figure this out in the next 90 days will have an unfair advantage. Don't be the last one to know. Comment "REPLACE" and I'll send it to you directly.
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Claude + GPT Image 2 + seedance + Meta ads MCP Replaced my 10k/month performance marketing agency Here's the exact stack (and how it works): Step 1: Research Feed Claude your product URL, your competitors' URLs, and your top-performing ad angles. It builds your full brand brief + competitor intelligence in minutes. No agency strategist needed. Step 2: Static ads in seconds Claude writes image generation prompts based on your brief. Those prompts go straight into GPT Image 2. Out comes scroll-stopping creative. Batched. On-brand. No designer. Step 3: Video ads that convert Claude writes video prompts. Those go into Seedance 2.0. UGC-style videos. AI actor formats. Product showcases. All generated, not filmed. (Both GPT Image 2 + Seedance are live on HeyOz right now.) Step 4: Publish + optimize on autopilot Connect Claude to Meta Ads MCP. It publishes your creatives, monitors performance, and keeps iterating. Your agency was charging you for this. This entire workflow is documented in a guide I put together, covering prompts, setup, and the exact MCP config. Why this matters: Most brands are still paying for slow, expensive creative production. The ones who figure this out in the next 90 days will have an unfair advantage. Don't be the last one to know. Comment "REPLACE" and I'll send it to you directly.

HeyOz

25,281 views • 4 months ago

IF I WAS FORCED to build a $20K/month AI creative agency using nothing but Photoshop, starting from 0, here's exactly what I would do in steps: The production setup (Days 1–3) 1. Download the Higgsfield plugin inside Photoshop — takes 5 minutes 2. You now have: sketch-to-image, layer decomposer, mockup studio, relight, upscale, face swap, character swap, background removal, AI stylist — all in 1 tool 3. Old creative agency workflow: designer + photographer + editor + 3–5 day turnaround 4. New workflow: 1 person, Photoshop, 30 minutes per deliverable The offer (Days 3–7) 5. Pick 1 niche — ecom brands, real estate agents, or course creators all need visuals constantly 6. Build a simple offer: "10 ad creatives delivered in 24 hours — $500" 7. Old agencies charge $2,000–$5,000/month for the same output 8. Your cost to deliver: $0 beyond the plugin. Pure margin. 9. Create 3 sample mockups using the tool — drop a product image in, generate 9 variations, pick the best 3 10. That's your portfolio. Built in under 1 hour. Cost: $0. The client machine (Days 7–20) 11. Go on X and search "[niche] + need a designer" or "[niche] + creatives" 12. DM 50 people per day — "I'll make you 3 free ad creatives in 24 hours, no catch" 13. Deliver them in 30 minutes using the plugin 14. 50 DMs/day × 14 days = 700 outreach messages 15. Conservative 3% conversion = 21 people see the free work 16. Close 5 of them at $500 = $2,500 in week 3 The scale (Days 20–30) 17. Upsell every client to a $1,500/month retainer — 10 creatives/week, unlimited revisions 18. 1 client per day in Photoshop takes 45 minutes max 19. 10 retainer clients × $1,500 = $15,000/month 20. Add 3 one-off clients at $500/month = $1,500 21. Add a $997 "AI creative system" course teaching other people this exact workflow = $3,000+/month from 3 sales The math: 50 DMs/day × 30 days = 1,500 outreach messages 3% book a call = 45 calls 40% close at $1,500/month retainer = 18 clients 18 × $1,500 = $27,000/month recurring Time per client per day: 45 minutes Total daily work: 4–5 hours Every mockup — AI. Every restyle — AI. Every layer rebuild — AI. Every variation — AI. No photographer. No designer and no reshoot. Start it here. 👇
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IF I WAS FORCED to build a $20K/month AI creative agency using nothing but Photoshop, starting from 0, here's exactly what I would do in steps: The production setup (Days 1–3) 1. Download the Higgsfield plugin inside Photoshop — takes 5 minutes 2. You now have: sketch-to-image, layer decomposer, mockup studio, relight, upscale, face swap, character swap, background removal, AI stylist — all in 1 tool 3. Old creative agency workflow: designer + photographer + editor + 3–5 day turnaround 4. New workflow: 1 person, Photoshop, 30 minutes per deliverable The offer (Days 3–7) 5. Pick 1 niche — ecom brands, real estate agents, or course creators all need visuals constantly 6. Build a simple offer: "10 ad creatives delivered in 24 hours — $500" 7. Old agencies charge $2,000–$5,000/month for the same output 8. Your cost to deliver: $0 beyond the plugin. Pure margin. 9. Create 3 sample mockups using the tool — drop a product image in, generate 9 variations, pick the best 3 10. That's your portfolio. Built in under 1 hour. Cost: $0. The client machine (Days 7–20) 11. Go on X and search "[niche] + need a designer" or "[niche] + creatives" 12. DM 50 people per day — "I'll make you 3 free ad creatives in 24 hours, no catch" 13. Deliver them in 30 minutes using the plugin 14. 50 DMs/day × 14 days = 700 outreach messages 15. Conservative 3% conversion = 21 people see the free work 16. Close 5 of them at $500 = $2,500 in week 3 The scale (Days 20–30) 17. Upsell every client to a $1,500/month retainer — 10 creatives/week, unlimited revisions 18. 1 client per day in Photoshop takes 45 minutes max 19. 10 retainer clients × $1,500 = $15,000/month 20. Add 3 one-off clients at $500/month = $1,500 21. Add a $997 "AI creative system" course teaching other people this exact workflow = $3,000+/month from 3 sales The math: 50 DMs/day × 30 days = 1,500 outreach messages 3% book a call = 45 calls 40% close at $1,500/month retainer = 18 clients 18 × $1,500 = $27,000/month recurring Time per client per day: 45 minutes Total daily work: 4–5 hours Every mockup — AI. Every restyle — AI. Every layer rebuild — AI. Every variation — AI. No photographer. No designer and no reshoot. Start it here. 👇

ALEX SUZUKI

21,454 views • 3 months ago

Claude + GPT Image 2 + Seedance + Meta Ads MCP Just fired my $10k/month performance marketing agency. Here's the exact stack (and how it runs): Step 1: Research Hand Claude your product page, your competitors' pages, and your best ad angles. It spits out a full brand brief + competitor breakdown in minutes. No strategist. No $200/hour consultant. Step 2: Static ads in seconds Claude crafts image prompts from your brief. Drop those into GPT Image 2. You get scroll-stopping creative. Batched. On-brand. No Figma needed. Step 3: Video ads that convert Claude writes video prompts. Feed them into Seedance 2.0. UGC-style clips. AI actor formats. Product showcases. All generated. Zero filming. (Both GPT Image 2 + Seedance are live on HeyOz right now.) Step 4: Publish + optimize on autopilot Hook Claude into Meta Ads MCP. It pushes your creatives live, tracks performance, and keeps iterating. Your agency was billing you hourly for this exact thing. I documented the full workflow in a guide: prompts, setup, and the exact MCP config. Why this matters: Most brands are still bleeding money on slow, overpriced creative production. The ones who crack this in the next 90 days will own an unfair advantage. Don't be the brand that figures it out too late. Comment "REPLACE" and I'll DM it to you.
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Claude + GPT Image 2 + Seedance + Meta Ads MCP Just fired my $10k/month performance marketing agency. Here's the exact stack (and how it runs): Step 1: Research Hand Claude your product page, your competitors' pages, and your best ad angles. It spits out a full brand brief + competitor breakdown in minutes. No strategist. No $200/hour consultant. Step 2: Static ads in seconds Claude crafts image prompts from your brief. Drop those into GPT Image 2. You get scroll-stopping creative. Batched. On-brand. No Figma needed. Step 3: Video ads that convert Claude writes video prompts. Feed them into Seedance 2.0. UGC-style clips. AI actor formats. Product showcases. All generated. Zero filming. (Both GPT Image 2 + Seedance are live on HeyOz right now.) Step 4: Publish + optimize on autopilot Hook Claude into Meta Ads MCP. It pushes your creatives live, tracks performance, and keeps iterating. Your agency was billing you hourly for this exact thing. I documented the full workflow in a guide: prompts, setup, and the exact MCP config. Why this matters: Most brands are still bleeding money on slow, overpriced creative production. The ones who crack this in the next 90 days will own an unfair advantage. Don't be the brand that figures it out too late. Comment "REPLACE" and I'll DM it to you.

Ahad Shams | AI Ads Guy

18,830 views • 4 months ago

Claude Code + Higgsfield MCP is f*cking cracked 🤯 I built an entire DTC ad campaign inside Claude Code using the new Higgsfield MCP. One product URL → hero static, animated hero shot, 2 UGC clips with a creator wearing the product. 5 assets. One Claude conversation. 3 Higgsfield models. All inside Claude Code. Perfect for DTC brands and agencies who need full campaign packages without booking a shoot or briefing a designer. If you're spending hours every week generating statics in one tool, briefing a motion designer for the hero clip, then chasing a UGC creator for the talking-head shots — this MCP eliminates the entire pipeline: → Drop a product URL into Claude Code → Claude pulls the brand brief — voice, hero SKUs, visual style, target customer → Generates the hero static with ChatGPT Images 2.0 → Animates it into a 5-second cinematic opener with Seedance 2.0 → Generates a UGC creator with GPT Image 2 → Drops her in the product and generates 2 native UGC video clips with Seedance 2.0 No tab-switching between tools. No copy-pasting prompts between platforms. No briefing 3 different vendors for one campaign. What you get: → A complete campaign package — static, animation, UGC — from one product URL → Brand-specific outputs that pull from a real brief, not generic AI slop → Claude making creative decisions between every step (which variation wins, which creator fits the persona, which clip needs a re-spin) → A repeatable pipeline you can run for any product in your catalog Built 100% in Claude Code with the Higgsfield MCP. I recorded a full walkthrough showing exactly how this works: the MCP setup, every prompt, every model, the full campaign output. Want the full video walkthrough? > Like this post > Comment "MCP" And I'll send it over (must be following so I can DM)
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Claude Code + Higgsfield MCP is f*cking cracked 🤯 I built an entire DTC ad campaign inside Claude Code using the new Higgsfield MCP. One product URL → hero static, animated hero shot, 2 UGC clips with a creator wearing the product. 5 assets. One Claude conversation. 3 Higgsfield models. All inside Claude Code. Perfect for DTC brands and agencies who need full campaign packages without booking a shoot or briefing a designer. If you're spending hours every week generating statics in one tool, briefing a motion designer for the hero clip, then chasing a UGC creator for the talking-head shots — this MCP eliminates the entire pipeline: → Drop a product URL into Claude Code → Claude pulls the brand brief — voice, hero SKUs, visual style, target customer → Generates the hero static with ChatGPT Images 2.0 → Animates it into a 5-second cinematic opener with Seedance 2.0 → Generates a UGC creator with GPT Image 2 → Drops her in the product and generates 2 native UGC video clips with Seedance 2.0 No tab-switching between tools. No copy-pasting prompts between platforms. No briefing 3 different vendors for one campaign. What you get: → A complete campaign package — static, animation, UGC — from one product URL → Brand-specific outputs that pull from a real brief, not generic AI slop → Claude making creative decisions between every step (which variation wins, which creator fits the persona, which clip needs a re-spin) → A repeatable pipeline you can run for any product in your catalog Built 100% in Claude Code with the Higgsfield MCP. I recorded a full walkthrough showing exactly how this works: the MCP setup, every prompt, every model, the full campaign output. Want the full video walkthrough? > Like this post > Comment "MCP" And I'll send it over (must be following so I can DM)

Mike Futia

29,800 views • 4 months ago

This is one of the wildest AI products I've seen this year. GeoAxis takes any photo and returns its exact location in seconds with no GPS and metadata needed. How it works: Most images online have the metadata stripped. Screenshots, reposts, cropped photos, none of them carry GPS coordinates. So the location has to be recovered from the pixels alone. This model reads several visual signals in parallel: → Landmarks (buildings, statues, signage) → Vegetation (species, density, seasonality) → Architecture (window style, roof pitch, materials) → Terrain (elevation cues, coastline, mountain profile) → Sky and lighting conditions Each signal narrows the search space. Vegetation alone can pin you to a climate zone. Architecture can pin you to a region. A single readable sign or a distinctive skyline can pin you to a city block. The pipeline runs coarse-to-fine: 1. Geo-Estimation: rough country/region prediction 2. Precise Geolocation: meter-level match against their indexed image database 3. Indoor Geolocation and Car Identification are shipping next Claimed accuracy is meter-level in deployed cities, with billions of images indexed. For OSINT, journalism and reverse image search, this changes the workflow. For personal privacy, stripping metadata no longer does anything.
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This is one of the wildest AI products I've seen this year. GeoAxis takes any photo and returns its exact location in seconds with no GPS and metadata needed. How it works: Most images online have the metadata stripped. Screenshots, reposts, cropped photos, none of them carry GPS coordinates. So the location has to be recovered from the pixels alone. This model reads several visual signals in parallel: → Landmarks (buildings, statues, signage) → Vegetation (species, density, seasonality) → Architecture (window style, roof pitch, materials) → Terrain (elevation cues, coastline, mountain profile) → Sky and lighting conditions Each signal narrows the search space. Vegetation alone can pin you to a climate zone. Architecture can pin you to a region. A single readable sign or a distinctive skyline can pin you to a city block. The pipeline runs coarse-to-fine: 1. Geo-Estimation: rough country/region prediction 2. Precise Geolocation: meter-level match against their indexed image database 3. Indoor Geolocation and Car Identification are shipping next Claimed accuracy is meter-level in deployed cities, with billions of images indexed. For OSINT, journalism and reverse image search, this changes the workflow. For personal privacy, stripping metadata no longer does anything.

Hasan Toor

15,030 views • 1 month ago

Everyone's sleeping on image-to-3D AI models. They can make your app look incredibly unique, with just a little effort. Here's how. This is my calorie tracker, built in a week with nothing but prompting. Just Claude Code + a couple APIs. The visuals are all AI-generated. I'll be sharing the full workflow + all the crazy technical stuff Claude and I did to make this work, so nobody has to struggle through it like me. Deep dive coming soon! Till then, this is the high-level idea: 1. Get a clean image of the food (or whatever your asset is) - In my app, the user describes foods via text, or attaches images (or both) - If text, an LLM extracts the food description and formats it into a specific prompt I tuned for this design, and we generate an image using Z-Image Turbo through fal - If image, we do the same thing but with FLUX.2 [dev] to edit the user image into our reference design - Originally, both used Google Nano Banana, but switching to open models cut costs and latency a ton 2. Gaussian splatting (2D image → 3D model) - I tried various 2D-to-3D options on fal and ended up with TripoSplat as my preferred balance of speed, cost, latency; this turns an image into a 3D model that looks super high quality (link below) - The app displays the 2D image while our backend generates the 3D splat - We "groom" the splat to reduce size and load time by culling low-opacity/scale points 3. Render efficiently on device Originally, it looked great but ran at 10 FPS. Getting to 120 FPS was a crazy journey. TL;DR: - SwiftUI had to go; it forced us to render each asset in independent MTKViews, which wasn't workable - Instead, we composite every dish into one full-bleed CAMetalLayer using MetalSplatter (link below) - We had to make some optimizations within MetalSplatter's code too, to reduce the overhead of sorting points per render Then I added some finishing touches like the subtle rotation and parallax as they move around. I think it turned out pretty cool :) Overall, this took some effort, but we still got it done in less than a day. Hopefully your agent can follow in the footsteps of mine and do it much faster. Keep an eye out for the bigger writeup, which'll give your agent everything it needs. If you have any questions, drop em below!
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Everyone's sleeping on image-to-3D AI models. They can make your app look incredibly unique, with just a little effort. Here's how. This is my calorie tracker, built in a week with nothing but prompting. Just Claude Code + a couple APIs. The visuals are all AI-generated. I'll be sharing the full workflow + all the crazy technical stuff Claude and I did to make this work, so nobody has to struggle through it like me. Deep dive coming soon! Till then, this is the high-level idea: 1. Get a clean image of the food (or whatever your asset is) - In my app, the user describes foods via text, or attaches images (or both) - If text, an LLM extracts the food description and formats it into a specific prompt I tuned for this design, and we generate an image using Z-Image Turbo through fal - If image, we do the same thing but with FLUX.2 [dev] to edit the user image into our reference design - Originally, both used Google Nano Banana, but switching to open models cut costs and latency a ton 2. Gaussian splatting (2D image → 3D model) - I tried various 2D-to-3D options on fal and ended up with TripoSplat as my preferred balance of speed, cost, latency; this turns an image into a 3D model that looks super high quality (link below) - The app displays the 2D image while our backend generates the 3D splat - We "groom" the splat to reduce size and load time by culling low-opacity/scale points 3. Render efficiently on device Originally, it looked great but ran at 10 FPS. Getting to 120 FPS was a crazy journey. TL;DR: - SwiftUI had to go; it forced us to render each asset in independent MTKViews, which wasn't workable - Instead, we composite every dish into one full-bleed CAMetalLayer using MetalSplatter (link below) - We had to make some optimizations within MetalSplatter's code too, to reduce the overhead of sorting points per render Then I added some finishing touches like the subtle rotation and parallax as they move around. I think it turned out pretty cool :) Overall, this took some effort, but we still got it done in less than a day. Hopefully your agent can follow in the footsteps of mine and do it much faster. Keep an eye out for the bigger writeup, which'll give your agent everything it needs. If you have any questions, drop em below!

Anshu

29,342 views • 3 months ago

Everyone loves saying: "Why don't Indian brands make products like this?" But they don't see the real problem. A well-wisher sent me a reel of a product that would be a huge hit in India. I checked the numbers. China factory price: $20 Landed cost in India: ~₹3,000 Retail price needed: ~₹6,000 Too expensive for most Indians. The funny part? If we Indianised it, we could probably sell it for ₹3,000 and still make it work. But there is one big wall. Moulds. Just the tooling would cost around $80,000. Before selling even one unit. That's the real challenge with making products in India. Not ideas or demand. But the cost and risk of building from scratch. So for now, we focus on smaller bets. Products where we can afford to take the risk. Still, it hurts seeing great ideas and not being able to build them all. How can we solve this?
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Everyone loves saying: "Why don't Indian brands make products like this?" But they don't see the real problem. A well-wisher sent me a reel of a product that would be a huge hit in India. I checked the numbers. China factory price: $20 Landed cost in India: ~₹3,000 Retail price needed: ~₹6,000 Too expensive for most Indians. The funny part? If we Indianised it, we could probably sell it for ₹3,000 and still make it work. But there is one big wall. Moulds. Just the tooling would cost around $80,000. Before selling even one unit. That's the real challenge with making products in India. Not ideas or demand. But the cost and risk of building from scratch. So for now, we focus on smaller bets. Products where we can afford to take the risk. Still, it hurts seeing great ideas and not being able to build them all. How can we solve this?

Prakash Dadlani

97,779 views • 4 months ago

a business idea you can start today use Higgsfield Supercomputer to build a faceless content factory for local businesses, creators, or niche media pages the workflow is simple: 1. pick one niche fitness coaches, real estate agents, SaaS founders, e-com brands, restaurants, whatever 2. feed Supercomputer the best-performing videos from that niche it researches what's trending, studies the hooks, pacing, thumbnails, voice, structure 3. make it generate 30-50 variations scripts, voiceovers, visuals, edits, thumbnails, posting angles 4. package this as "done-for-you content engine" not "AI video generation", businesses don't care about that they care about getting content that looks native, ships daily, and doesn't require hiring a full creative team 5. charge $1,000-3,000/month per client one tool does what used to take a scriptwriter, editor, thumbnail designer, VA, and social media manager this is the whole point, AI content tools were cool but the margin is in orchestration one person can run 5-10 clients with this probably one of the easiest agency plays of 2026
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a business idea you can start today use Higgsfield Supercomputer to build a faceless content factory for local businesses, creators, or niche media pages the workflow is simple: 1. pick one niche fitness coaches, real estate agents, SaaS founders, e-com brands, restaurants, whatever 2. feed Supercomputer the best-performing videos from that niche it researches what's trending, studies the hooks, pacing, thumbnails, voice, structure 3. make it generate 30-50 variations scripts, voiceovers, visuals, edits, thumbnails, posting angles 4. package this as "done-for-you content engine" not "AI video generation", businesses don't care about that they care about getting content that looks native, ships daily, and doesn't require hiring a full creative team 5. charge $1,000-3,000/month per client one tool does what used to take a scriptwriter, editor, thumbnail designer, VA, and social media manager this is the whole point, AI content tools were cool but the margin is in orchestration one person can run 5-10 clients with this probably one of the easiest agency plays of 2026

Ronin

41,304 views • 4 months ago

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

tetsuo

18,325 views • 7 months ago