Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

A Hollywood studio would burn $4.5M and three months of VFX coordination to pull this off. A 19-year-old student generated the same 15-second thermodynamic spectacle from her bedroom for just $42 in an evening. 43M views in under 24 hours. Over 180,000 comments fiercely debating whether the colored balls... survived the lava. The anatomy of the clip that broke the algorithm: > The Hook: a woman in a helicopter holding a transparent ice block with red, yellow, blue, and green balls frozen inside. lava glowing through the open door. your brain instantly classifies this as extreme experiment content. > The Drop: she pushes the block out. it tumbles. the colored balls are visible through the ice as it falls. > The Climax: impact. the ice shatters on the lava surface. the colored balls scatter. some melt instantly. some bounce on the hardened crust. each one behaves differently based on its material. The exact workflow behind it: 1. Kimi K3 condensed 187 rounds of science experiment references down to 6 core creative patterns in a single prompt 2. Seedream generated 42 photorealistic reference frames from the source concept 3. Seedance 2.5 brought the 36 approved keyframes to life with seamless thermodynamic animation and authentic helicopter camera drift 4. Cartesia mapped every ice crack, ball bounce, and lava hiss where the pacing demanded it 5. CapCut stitched 11 dynamic takes into one razor-sharp 15-second sequence Traditional production would demand volcanic permits, heat-resistant equipment, and six months of safety clearance. She engineered a global viral phenomenon before her morning coffee even went cold. Full prompt breakdown and step-by-step pipeline pinned below.show more

Neuro

1,424 subscribers

28,053 görüntüleme • 20 gün önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

CLAUDE + SEEDANCE 2.5 CAN REBUILD A VIRAL VIDEO FROM ITS FRAMES IN ONE CONVERSATION (as, for example, with this whale) Did you notice the difference? Prompt in the comments Made with Seedance 2.5 on MakeUGC ▪ STEP ONE: split the original into frames. Claude pulls one frame per second from the source video and reads each one, so the clip becomes a timeline: leap, strike, swallow, giant, final shot. ▪ STEP TWO: Claude writes the prompt in blocks - subjects, location with real numbers, camera, second-by-second timeline, natural sound, continuity - and swaps the cold grey look for warm golden-hour light. ▪ STEP THREE: five of the original frames go into Seedance 2.5 as reference images, in order, each one mapped to its own seconds in the timeline. The point: the structure of the original survives, the look changes, and every swallow is pinned to a real reference shape. 🔖Save this to try later.

CLAUDE + SEEDANCE 2.5 CAN REBUILD A VIRAL VIDEO FROM ITS FRAMES IN ONE CONVERSATION (as, for example, with this whale) Did you notice the difference? Prompt in the comments Made with Seedance 2.5 on MakeUGC ▪ STEP ONE: split the original into frames. Claude pulls one frame per second from the source video and reads each one, so the clip becomes a timeline: leap, strike, swallow, giant, final shot. ▪ STEP TWO: Claude writes the prompt in blocks - subjects, location with real numbers, camera, second-by-second timeline, natural sound, continuity - and swaps the cold grey look for warm golden-hour light. ▪ STEP THREE: five of the original frames go into Seedance 2.5 as reference images, in order, each one mapped to its own seconds in the timeline. The point: the structure of the original survives, the look changes, and every swallow is pinned to a real reference shape. 🔖Save this to try later.

Zentrix⌚️

12,474 görüntüleme • 10 gün önce

A 10-SECOND TITAN CGI SHOT PULLED 51,000,000 VIEWS IN UNDER 24 HOURS a 19-year-old VFX student built a blockbuster-grade shot of a titan walking along a coastline for $42. keeping the scale of a $356M Marvel movie, dropping the production crew the rebuild is where Picsart sits. the stack: 1. Picsart Agents: you hire ai staff to break down reference concepts. Aura builds the environment prompt, Nora fine-tunes the lighting, Reeva cuts the final 10-second sequence 2. AI Playground: runs Seedream and Seedance 2.5 on the same prompt in parallel. two readings of giant-scale movement side by side, you keep the one with correct shadow physics 3. Picsart Flow: takes one real aerial coastline photo to a finished video with giant water displacement. no keyframes, no 3D rendering pipelines 4. Picsart Pro is $15 a month. that’s the whole $356M VFX department on a $42 setup budget 5. Cartesia & CapCut integration: maps footstep impacts and stitches 11 dynamic takes into one razor-sharp clip before your morning coffee gets cold the catch: scale collapses only work when the shadows match the sun angle. check the physics before you hit export the VFX studio was the expensive part. the format was always free

A 10-SECOND TITAN CGI SHOT PULLED 51,000,000 VIEWS IN UNDER 24 HOURS a 19-year-old VFX student built a blockbuster-grade shot of a titan walking along a coastline for $42. keeping the scale of a $356M Marvel movie, dropping the production crew the rebuild is where Picsart sits. the stack: 1. Picsart Agents: you hire ai staff to break down reference concepts. Aura builds the environment prompt, Nora fine-tunes the lighting, Reeva cuts the final 10-second sequence 2. AI Playground: runs Seedream and Seedance 2.5 on the same prompt in parallel. two readings of giant-scale movement side by side, you keep the one with correct shadow physics 3. Picsart Flow: takes one real aerial coastline photo to a finished video with giant water displacement. no keyframes, no 3D rendering pipelines 4. Picsart Pro is $15 a month. that’s the whole $356M VFX department on a $42 setup budget 5. Cartesia & CapCut integration: maps footstep impacts and stitches 11 dynamic takes into one razor-sharp clip before your morning coffee gets cold the catch: scale collapses only work when the shadows match the sun angle. check the physics before you hit export the VFX studio was the expensive part. the format was always free

Ridark

28,448 görüntüleme • 20 gün önce

$What would you do if a monster charged at you in the middle of the street? Made with Nano Banana 2 + Seedance 2.0 4k on TapNow prompt Beat 1 - The Calm Opening The reference image character is a Western woman with long wavy blonde hair casually drinking a Coke in the middle of a chaotic urban street. Her outfit and cap match Image 1 exactly. Energy is calm, unfazed, and confident. Camera: grounded, cinematic, medium shot. Beat 2 - The Monster Charges A terrifying monster bull charges toward her at full speed. It smashes through debris and scatters people in panic. The street erupts into chaos around the character. Camera: dynamic tracking, wide angle to capture scale of monster and chaos. Beat 3 - The Transformation The young woman stays calm and completely unfazed. She lowers the Coke. She raises one hand. Her arm begins transforming into solid ice from the fingertips upward. Frost spreads across her skin, glowing with cold blue-white energy. Vapor rolls off the arm as the ice transformation builds. Camera: close-up on the arm transformation, slow and deliberate. Beat 4 - The Touch - Slow Motion As the monster lunges, she calmly reaches forward. She touches the monster with her frozen hand. DRAMATIC SLOW MOTION at the moment of contact. Ice rapidly spreads from the point of contact across the monster's body. The monster panics - thrashing and roaring as frost crawls over its claws, chest, face, and eyes. The monster's movement slows as the freezing effect takes over. Camera: extreme close-up on contact point, then pulls out to reveal the spreading ice. Beat 5 - Full Freeze The creature becomes completely encased in crystal-clear ice, frozen mid-attack. A tense pause holds on the frozen monster. Deep cracks spread through the frozen monster. Cracks split across its icy body with sharp crystalline sounds. Detailed cracking ice - realistic frost and crystal texture throughout. Camera: wide shot of the frozen monster, locked and still for the pause beat. Beat 6 - The Walk-Off The young woman casually takes another sip of Coke. She turns away without looking back. She walks off calmly as the frozen monster cracks behind her. Confident calm hero energy. No celebration. No reaction. Just casual. Camera: low angle tracking shot as she walks away, monster in background. Visual Effects Realistic ice transformation - frost spreading from fingertips upward. Frost vapor rolling off the arm during transformation. Cold blue-white glowing energy across frozen skin. Ice rapidly spreading across monster body from point of contact. Detailed cracking ice with sharp crystalline fracture lines. Crystal-clear ice encasing the entire monster mid-attack. Realistic freeze physics - movement slowing as ice covers the creature. Camera Style Dynamic cinematic camera movement throughout. High-action monster attack framing during the charge. Dramatic slow motion at the exact moment of hand contact. Close-up on ice transformation - fingertips to shoulder. Pull-back reveal as ice spreads across the monster's full body. Low angle walk-off shot to close the scene. One continuous take. No cuts. Camera never stops. Character appearance: a beautiful Western woman with long wavy blonde hair flowing naturally beneath the cap, maintaining the same calm, confident, and unfazed presence throughout the entire sequence.$

What would you do if a monster charged at you in the middle of the street? Made with Nano Banana 2 + Seedance 2.0 4k on TapNow prompt Beat 1 - The Calm Opening The reference image character is a Western woman with long wavy blonde hair casually drinking a Coke in the middle of a chaotic urban street. Her outfit and cap match Image 1 exactly. Energy is calm, unfazed, and confident. Camera: grounded, cinematic, medium shot. Beat 2 - The Monster Charges A terrifying monster bull charges toward her at full speed. It smashes through debris and scatters people in panic. The street erupts into chaos around the character. Camera: dynamic tracking, wide angle to capture scale of monster and chaos. Beat 3 - The Transformation The young woman stays calm and completely unfazed. She lowers the Coke. She raises one hand. Her arm begins transforming into solid ice from the fingertips upward. Frost spreads across her skin, glowing with cold blue-white energy. Vapor rolls off the arm as the ice transformation builds. Camera: close-up on the arm transformation, slow and deliberate. Beat 4 - The Touch - Slow Motion As the monster lunges, she calmly reaches forward. She touches the monster with her frozen hand. DRAMATIC SLOW MOTION at the moment of contact. Ice rapidly spreads from the point of contact across the monster's body. The monster panics - thrashing and roaring as frost crawls over its claws, chest, face, and eyes. The monster's movement slows as the freezing effect takes over. Camera: extreme close-up on contact point, then pulls out to reveal the spreading ice. Beat 5 - Full Freeze The creature becomes completely encased in crystal-clear ice, frozen mid-attack. A tense pause holds on the frozen monster. Deep cracks spread through the frozen monster. Cracks split across its icy body with sharp crystalline sounds. Detailed cracking ice - realistic frost and crystal texture throughout. Camera: wide shot of the frozen monster, locked and still for the pause beat. Beat 6 - The Walk-Off The young woman casually takes another sip of Coke. She turns away without looking back. She walks off calmly as the frozen monster cracks behind her. Confident calm hero energy. No celebration. No reaction. Just casual. Camera: low angle tracking shot as she walks away, monster in background. Visual Effects Realistic ice transformation - frost spreading from fingertips upward. Frost vapor rolling off the arm during transformation. Cold blue-white glowing energy across frozen skin. Ice rapidly spreading across monster body from point of contact. Detailed cracking ice with sharp crystalline fracture lines. Crystal-clear ice encasing the entire monster mid-attack. Realistic freeze physics - movement slowing as ice covers the creature. Camera Style Dynamic cinematic camera movement throughout. High-action monster attack framing during the charge. Dramatic slow motion at the exact moment of hand contact. Close-up on ice transformation - fingertips to shoulder. Pull-back reveal as ice spreads across the monster's full body. Low angle walk-off shot to close the scene. One continuous take. No cuts. Camera never stops. Character appearance: a beautiful Western woman with long wavy blonde hair flowing naturally beneath the cap, maintaining the same calm, confident, and unfazed presence throughout the entire sequence.

Sharon Riley

58,578 görüntüleme • 3 ay önce

A CARNIVAL GAG LIKE THIS IS THREE TIMED EVENTS, NOT ONE Bank-a-ball booth, plush prizes hanging overhead. She throws from behind camera, the ball bounces off the board and misses. Right as it lands, a guy in a cap pops up from behind the stand trying to catch it. She laughs, fixes her skirt, leans down for the next ball. None of it happened - not the booth, not the throw, not the guy who popped up at exactly the wrong moment. - Three moving things have to land on the same beat The ball needs its own arc, bounce, and miss off the board. Her throw needs the weight shift and follow-through of an actual pitch, not a mimed one. And the guy behind the stand has to time his entire pop-up to the second the ball lands, or the joke reads as staged instead of caught. None of the three gets generated with the other two in mind by default - getting all three to agree on one beat is the actual trick. Landing three unrelated timings on the same beat, on command, is the same process the article below turns into a business - across five different characters, every time.

A CARNIVAL GAG LIKE THIS IS THREE TIMED EVENTS, NOT ONE Bank-a-ball booth, plush prizes hanging overhead. She throws from behind camera, the ball bounces off the board and misses. Right as it lands, a guy in a cap pops up from behind the stand trying to catch it. She laughs, fixes her skirt, leans down for the next ball. None of it happened - not the booth, not the throw, not the guy who popped up at exactly the wrong moment. - Three moving things have to land on the same beat The ball needs its own arc, bounce, and miss off the board. Her throw needs the weight shift and follow-through of an actual pitch, not a mimed one. And the guy behind the stand has to time his entire pop-up to the second the ball lands, or the joke reads as staged instead of caught. None of the three gets generated with the other two in mind by default - getting all three to agree on one beat is the actual trick. Landing three unrelated timings on the same beat, on command, is the same process the article below turns into a business - across five different characters, every time.

capONE 💎

131,978 görüntüleme • 29 gün önce

From the frozen depths to the heart of the flame Watch the ultimate transformation. Made with Seedance 2.0 Prompt: A continuous cinematic fantasy action sequence of a young East Asian warrior woman. She is crawling on a cracked icy battlefield, desperately holding up a glowing teardrop-shaped red crystal amulet set in a gold crescent. Suddenly, a massive surge of fiery energy explodes from the crystal, instantly shattering the ice and turning the entire landscape into a volcanic crater filled with flowing magma and ruined stone pillars. The woman levitates high into the air as intense, swirling vortices of fire wrap around her body. In mid-air, the flames materialize into a highly detailed crimson and gold fantasy dress with metallic arm guards and a flowing cape. A blazing crown of pure fire forms on her forehead, and her eyes snap open, glowing with intense, fiery heart-shaped patterns. She raises her hand to summon an intricate, giant golden magical circle in front of her, unleashing a catastrophic, blinding explosion of fire that obliterates everything in sight. 8K ultra-realism, high-fidelity VFX, dynamic camera angles, cinematic lighting, and epic scale.

From the frozen depths to the heart of the flame Watch the ultimate transformation. Made with Seedance 2.0 Prompt: A continuous cinematic fantasy action sequence of a young East Asian warrior woman. She is crawling on a cracked icy battlefield, desperately holding up a glowing teardrop-shaped red crystal amulet set in a gold crescent. Suddenly, a massive surge of fiery energy explodes from the crystal, instantly shattering the ice and turning the entire landscape into a volcanic crater filled with flowing magma and ruined stone pillars. The woman levitates high into the air as intense, swirling vortices of fire wrap around her body. In mid-air, the flames materialize into a highly detailed crimson and gold fantasy dress with metallic arm guards and a flowing cape. A blazing crown of pure fire forms on her forehead, and her eyes snap open, glowing with intense, fiery heart-shaped patterns. She raises her hand to summon an intricate, giant golden magical circle in front of her, unleashing a catastrophic, blinding explosion of fire that obliterates everything in sight. 8K ultra-realism, high-fidelity VFX, dynamic camera angles, cinematic lighting, and epic scale.

Zyrella

26,053 görüntüleme • 3 ay önce

📖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.

📖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 görüntüleme • 3 ay önce

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:

i just open sourced the workflow behind $2M AI video productions... i built 7 skills that run the pipeline end to end, built for Seedance 2.5 and they work in Claude Code, Codex, Hermes or any harness (works best with 1080p using Higgsfield CLI) here's how to use them, in order: /setup writes which image and video models you run into your project, once, so every skill reads the same stack /studio-init scaffolds the whole studio as a file tree from one question, the project name /film-breakdown walks your script scene by scene and writes a 22-field card for every shot /reference-board locks your references into a visual bible, a caption on every image and a ban list for the rest /asset-passport writes the exhaustive descriptor every later prompt will quote word for word /stress-test combat-tests each asset and flips it to locked only at 10 out of 10 repeatability /shot-prompt refuses to run until everything in frame is locked, then writes the 15-block prompt and logs every attempt get access to the skills and full breakdown of the pipeline in the article below:

Machina

61,554 görüntüleme • 1 ay önce

A 22-year-old photographer from Tromsø borrowed her roommate's mason jar and disappeared into the snow for an hour. She wouldn't say why. By the next morning, her 12-second clip had reached 3 million views. Her plan was simple: capture the northern lights in a glass jar. not a photo of them. the actual aurora. in a jar. held in her hands. glowing. The clip: a snowy forest road at night. tire tracks. footprints. aurora borealis rippling green and purple across the sky. a small flame of aurora light hovers above the path. hands reach out with a mason jar and scoop it up. the aurora ribbon sits inside the glass, swirling. green light reflects off the snow and off her fingers. She didn't invent a new trend. She borrowed the "catch impossible nature in a container" format that was already working and applied it to the one natural phenomenon every traveler wants to hold. The $29 went to a Seedance 2.5 subscription. She typed one sentence, hit generate, and walked outside to watch the real aurora while the fake one rendered. Then she ran the system again: different location, different aurora color, same jar. One character she can keep building around. One format she can reuse every clear night for the rest of winter. Find out how to do it in the article below

A 22-year-old photographer from Tromsø borrowed her roommate's mason jar and disappeared into the snow for an hour. She wouldn't say why. By the next morning, her 12-second clip had reached 3 million views. Her plan was simple: capture the northern lights in a glass jar. not a photo of them. the actual aurora. in a jar. held in her hands. glowing. The clip: a snowy forest road at night. tire tracks. footprints. aurora borealis rippling green and purple across the sky. a small flame of aurora light hovers above the path. hands reach out with a mason jar and scoop it up. the aurora ribbon sits inside the glass, swirling. green light reflects off the snow and off her fingers. She didn't invent a new trend. She borrowed the "catch impossible nature in a container" format that was already working and applied it to the one natural phenomenon every traveler wants to hold. The $29 went to a Seedance 2.5 subscription. She typed one sentence, hit generate, and walked outside to watch the real aurora while the fake one rendered. Then she ran the system again: different location, different aurora color, same jar. One character she can keep building around. One format she can reuse every clear night for the rest of winter. Find out how to do it in the article below

Ridark

27,226 görüntüleme • 22 gün önce

FABLE 5 + HIGGSFIELD TURN A $35,000 ANIMATED SITE INTO A ONE-SESSION, $12 BUILD. HERE'S EXACTLY HOW. a studio runs this across four people and three weeks. you run it across one chat window and one afternoon. THE BUILD, STAGE BY STAGE: STAGE 1 - THE CONCEPT Claude reads your brief and scripts the scroll before a line of code exists - what the visitor feels at second 3, 15, 40. prompt: "read this brief. script the scroll beat by beat, then scaffold the project with GSAP ScrollTrigger + Lenis." STAGE 2 - THE VISUALS (Higgsfield) every hero shot, transition, and ambient loop comes out of 30+ generative models - matched to the story, not pulled from a stock library. prompt: "generate the hero sting and one b-roll clip per section. 3-5s, high-res, cinematic." STAGE 3 - THE MOTION (Claude Code) Claude writes the ScrollTrigger timelines and Lenis smooth-scroll, extracts frames, optimizes every asset. zero hand-coded keyframes. prompt: "wire the scroll: pin the hero, scrub the video, reveal each section on scroll. keep it 60fps on mobile." STAGE 4 - THE POLISH six cinematic effects baked in, no config: film grain, particles, vignette, glass cards, color tints, scroll pacing. prompt: "bake in the cinematic layer, then QA load speed, mobile breakpoints, and whether the scroll actually lands - rewrite what doesn't." 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 pipeline was the moat. it just became four prompts. Follow me, comment "MATH" and I'll send you the full step-by-step Playbook. full breakdown in the article 👇

FABLE 5 + HIGGSFIELD TURN A $35,000 ANIMATED SITE INTO A ONE-SESSION, $12 BUILD. HERE'S EXACTLY HOW. a studio runs this across four people and three weeks. you run it across one chat window and one afternoon. THE BUILD, STAGE BY STAGE: STAGE 1 - THE CONCEPT Claude reads your brief and scripts the scroll before a line of code exists - what the visitor feels at second 3, 15, 40. prompt: "read this brief. script the scroll beat by beat, then scaffold the project with GSAP ScrollTrigger + Lenis." STAGE 2 - THE VISUALS (Higgsfield) every hero shot, transition, and ambient loop comes out of 30+ generative models - matched to the story, not pulled from a stock library. prompt: "generate the hero sting and one b-roll clip per section. 3-5s, high-res, cinematic." STAGE 3 - THE MOTION (Claude Code) Claude writes the ScrollTrigger timelines and Lenis smooth-scroll, extracts frames, optimizes every asset. zero hand-coded keyframes. prompt: "wire the scroll: pin the hero, scrub the video, reveal each section on scroll. keep it 60fps on mobile." STAGE 4 - THE POLISH six cinematic effects baked in, no config: film grain, particles, vignette, glass cards, color tints, scroll pacing. prompt: "bake in the cinematic layer, then QA load speed, mobile breakpoints, and whether the scroll actually lands - rewrite what doesn't." 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 pipeline was the moat. it just became four prompts. Follow me, comment "MATH" and I'll send you the full step-by-step Playbook. full breakdown in the article 👇

ZEUS⚡️

47,174 görüntüleme • 2 ay önce

EVERY CLIP THIS GIRL IN CHINA POSTS GETS 4,600 PEOPLE ASKING HOW SHE MADE IT AND THAT QUESTION PAYS $12,800 A MONTH > 203,000 likes on 6,400 comments. White paper background, she poses beside blueprint-style measurements before Look 1 to Look 4 cycle through, showing each outfit from multiple angles with colour palettes and brand labels. The blueprint is doing more work than the clothes, and that is the whole design: -> Every viewer has seen a fit-check, so the format reads in a second and the measurements in the first frame tell them whether the clothes would sit on their own body. -> The brand names are drawn on the frame in small type, Converse on the sneakers, Demonia on the boots, so half the "where from" questions get answered before they are typed and the other half go to the keyword. -> Front, side and back stand in one frame, so the cut from Look 1 to Look 4 reads as a catalogue and never as 4 separate clips. -> She holds the same pose in every look with the same haircut, so the eye compares the clothes and never the girl. -> The comments are "look 2?", "the bag in look 1?", and with a word per clip the sheet shows which outfit made people ask, by completed runs per 1,000 views and never by views. A spec sheet is a shortcut the brain cannot skip, and 4 outfits on the same body is the cheapest catalogue in short-form. It works on any product with a measurement people care about, a sofa, a backpack, a road bike, a wedding dress. Under it the word is LOOK, and Blotato's DM carries look 1 and look 2 as buttons with the newsletter as the third, behind an email gate. Claude ranks her clips every Monday. $49 a month for both. The outfits got the likes, and the blueprint everyone read first is what got the word typed. Which look made people ask, article below 👇

Fokki

36,877 görüntüleme • 11 gün önce

A 22-YEAR-OLD IN CHINA SOLD HER VIRAL AI REELS TO 6 LOCAL BUSINESSES AND CLEARED $11,900 LAST MONTH She never filmed a thing. She tracked 40 faceless channels in one sheet and scored every clip that beat its own channel. One line ran the sort: views over the channel's median. Anything past 30 was a format she could reskin that week. The AI-video look was blowing up on Douyin, so she took the shape and ran it in english first. For $50 a month in apps she found the format on Monday and shipped by Wednesday. Claude prompted each format into 30 shot lists. CapCut generated the whole clip, a photoreal AI girl in a full scene, with AI voice and captions. Make posted to 3 platforms and fed the numbers back into the same sheet, so her own hits fed the next batch. She walked into a boutique with a phone and a page of outlier scores. She left with a retainer for 20 AI videos a month. A studio needs a model, a crew, and a shoot day for one clip. She generated hers overnight. Every prompt and the scenario are in the article.

A 22-YEAR-OLD IN CHINA SOLD HER VIRAL AI REELS TO 6 LOCAL BUSINESSES AND CLEARED $11,900 LAST MONTH She never filmed a thing. She tracked 40 faceless channels in one sheet and scored every clip that beat its own channel. One line ran the sort: views over the channel's median. Anything past 30 was a format she could reskin that week. The AI-video look was blowing up on Douyin, so she took the shape and ran it in english first. For $50 a month in apps she found the format on Monday and shipped by Wednesday. Claude prompted each format into 30 shot lists. CapCut generated the whole clip, a photoreal AI girl in a full scene, with AI voice and captions. Make posted to 3 platforms and fed the numbers back into the same sheet, so her own hits fed the next batch. She walked into a boutique with a phone and a page of outlier scores. She left with a retainer for 20 AI videos a month. A studio needs a model, a crew, and a shoot day for one clip. She generated hers overnight. Every prompt and the scenario are in the article.

Fokki

82,974 görüntüleme • 3 ay önce

AI JUST GENERATED A MIAMI NIGHTLIFE VIDEO SO REAL THAT INFLUENCERS ARE ASKING WHO SHE IS Looks like a paparazzi clip from outside a luxury hotel. A valet in a vest opens the door of a black Maybach and a blonde in a burgundy chain dress steps out onto the sidewalk in strappy heels. Palm trees, city lights, leather interior glowing through the open door. You'd save this to your "aesthetic" folder without a second thought. 📌But then you start noticing what's actually holding together. She exits the car with correct body mechanics, one leg out first, hand on the frame, weight shift onto the heel. The Maybach badge stays sharp. The reflections on the black paint move correctly with the door angle. The chain details on the dress catch streetlight differently with every step. The valet stands behind her with natural posture and his own shadow on the pavement. 📌SHE WALKS TOWARD THE HOTEL ENTRANCE AND THE CAMERA FOLLOWS FROM BEHIND. Hair bouncing over a backless dress, handbag swinging in her hand, heels hitting pavement with correct stride, people in the background near the door minding their own business. Night lighting on skin, fabric, metal, glass and wet pavement all behaving the way real light does in real darkness. 📌None of it was filmed. Not the car, not the hotel, not the valet, not her. AI just produced a clip so polished that real influencers are getting tagged in the comments asking if this is their content. It's not. It's a prompt.

AI JUST GENERATED A MIAMI NIGHTLIFE VIDEO SO REAL THAT INFLUENCERS ARE ASKING WHO SHE IS Looks like a paparazzi clip from outside a luxury hotel. A valet in a vest opens the door of a black Maybach and a blonde in a burgundy chain dress steps out onto the sidewalk in strappy heels. Palm trees, city lights, leather interior glowing through the open door. You'd save this to your "aesthetic" folder without a second thought. 📌But then you start noticing what's actually holding together. She exits the car with correct body mechanics, one leg out first, hand on the frame, weight shift onto the heel. The Maybach badge stays sharp. The reflections on the black paint move correctly with the door angle. The chain details on the dress catch streetlight differently with every step. The valet stands behind her with natural posture and his own shadow on the pavement. 📌SHE WALKS TOWARD THE HOTEL ENTRANCE AND THE CAMERA FOLLOWS FROM BEHIND. Hair bouncing over a backless dress, handbag swinging in her hand, heels hitting pavement with correct stride, people in the background near the door minding their own business. Night lighting on skin, fabric, metal, glass and wet pavement all behaving the way real light does in real darkness. 📌None of it was filmed. Not the car, not the hotel, not the valet, not her. AI just produced a clip so polished that real influencers are getting tagged in the comments asking if this is their content. It's not. It's a prompt.

Dapper

80,301 görüntüleme • 18 gün önce

A 24-year-old thrift reseller from Shenzhen spent $31 and one evening photographing 12 outfits from her own closet against a plain wall. Tomorrow she had a 40-second lookbook clip with 900,000 views - every outfit turned into a brand's technical spec sheet, three angles, measurements and all. She took one front photo of each outfit. Kimi K3 added the specs and Seedance 2.5 created the other angles and blueprint effect. Her 12 outfits now looked studio-made. The format already had momentum. She took a visual formula that was catching on: a plain backdrop, a girl standing still, technical lines that make an old T-shirt look like it belongs in an archive. 12 looks in one sitting is a record nobody was chasing. Most accounts post 2 or 3. The $31 covered one month of Kimi K3 and Seedance 2.5, combined. By midnight, the clip was live on 3 platforms. Then she kept the blueprint style and swapped the outfit. New pieces, new colorway chips, same three angles. One evening in front of a wall. 12 looks that keep pulling views.

Fokki

97,153 görüntüleme • 1 ay önce

Cirque du Soleil drops $165,000,000 on a single stage show Last night, a college dropout spent $34 on an AI pipeline His 16-second clip hit 2,830,000 views before morning: > A house cat sits in front of an empty gilded mirror. > A full-size lion slowly materializes inside the glass. > The magician throws a blue velvet cloth over the entire frame. > The cloth drops: the mirror has vanished, and the lion is standing onstage. > Final frame: the lion calmly lies down beside the cat. Viewers replayed it frame by frame, searching for cuts, warped edges, or a broken reflection. Nobody found the trick because the mirror, the lion, and the theater never existed. The anatomy of the clip that broke the algorithm: - Google Sheets: Prompt rules, 9:16 aspect ratio, hard 17-second limit. - Google Drive: Theater lighting, lion anatomy, cat movement, and velvet references. - Seedance: One continuous audience-perspective render with a locked camera. - GPT-6 Astra: Automated QC - 1080×1920, 16.2s duration, transformation continuity, and audio sync. - Slack + Calendar: Auto-approved, scheduled, and published autonomously. A live illusion like this would demand animal trainers, hidden machinery, stage permits, and months of rehearsal. He simply described an impossible transformation to a chain of APIs. Cirque du Soleil books a multi-million-dollar theater. He generated the theater, the magician, and the lion before dinner. The full system blueprint is broken down below 👇

Cirque du Soleil drops $165,000,000 on a single stage show Last night, a college dropout spent $34 on an AI pipeline His 16-second clip hit 2,830,000 views before morning: > A house cat sits in front of an empty gilded mirror. > A full-size lion slowly materializes inside the glass. > The magician throws a blue velvet cloth over the entire frame. > The cloth drops: the mirror has vanished, and the lion is standing onstage. > Final frame: the lion calmly lies down beside the cat. Viewers replayed it frame by frame, searching for cuts, warped edges, or a broken reflection. Nobody found the trick because the mirror, the lion, and the theater never existed. The anatomy of the clip that broke the algorithm: - Google Sheets: Prompt rules, 9:16 aspect ratio, hard 17-second limit. - Google Drive: Theater lighting, lion anatomy, cat movement, and velvet references. - Seedance: One continuous audience-perspective render with a locked camera. - GPT-6 Astra: Automated QC - 1080×1920, 16.2s duration, transformation continuity, and audio sync. - Slack + Calendar: Auto-approved, scheduled, and published autonomously. A live illusion like this would demand animal trainers, hidden machinery, stage permits, and months of rehearsal. He simply described an impossible transformation to a chain of APIs. Cirque du Soleil books a multi-million-dollar theater. He generated the theater, the magician, and the lion before dinner. The full system blueprint is broken down below 👇

Auren

499,687 görüntüleme • 1 ay önce

I FOUND A COUPLE FORMAT THAT GETS 7M+ VIEWS WITH ONE HAND AND ONE PAIR OF GLASSES. 12 SECONDS. NO KISS. NO CAPTION. JUST A CAMERA ANGLE THAT MAKES YOUR BRAIN LIE TO ITSELF. Thread. First frame. Girl in black, camera below her chin. A man's hand enters from above and grabs her hair. Pulls. You already know what you think is about to happen and that's why you're still here. 0:01. Hand grips the hair, pulls her head back. Angle is from below looking up. This is the exact POV of every clip on sites you don't talk about. The framing is doing all the work and the video hasn't even started. 0:03. She's wearing glasses. His hand comes down and takes them off. That's it. He removed her glasses. But the way the hand moves from her hair to her face, the way she looks up with her lips parted, none of it reads as "taking off glasses." It reads as what you decided in the first second. 0:07. Hand grabs her chin, tilts her face up. She's looking into the camera from below with his fingers under her jaw. On paper a guy is holding his girlfriend's face. On paper it's nothing. On screen it's everything. The video loops and you're watching the hair grab again, already knowing it's just glasses, and it looks exactly the same. Knowing the punchline doesn't undo the setup. Your brain sees it the same way every time. The format: hand from above, camera from below, one accessory. Glasses, hair tie, necklace, doesn't matter. That geometry is the entire trick. Black top, pearl necklace, white room. If she was in sweats on a couch this would be a vlog. In this outfit with this lighting it's a scene. If you see a hand from above and a camera from below, your brain already finished the video for them. She didn't do anything. He just took off her glasses.

I FOUND A COUPLE FORMAT THAT GETS 7M+ VIEWS WITH ONE HAND AND ONE PAIR OF GLASSES. 12 SECONDS. NO KISS. NO CAPTION. JUST A CAMERA ANGLE THAT MAKES YOUR BRAIN LIE TO ITSELF. Thread. First frame. Girl in black, camera below her chin. A man's hand enters from above and grabs her hair. Pulls. You already know what you think is about to happen and that's why you're still here. 0:01. Hand grips the hair, pulls her head back. Angle is from below looking up. This is the exact POV of every clip on sites you don't talk about. The framing is doing all the work and the video hasn't even started. 0:03. She's wearing glasses. His hand comes down and takes them off. That's it. He removed her glasses. But the way the hand moves from her hair to her face, the way she looks up with her lips parted, none of it reads as "taking off glasses." It reads as what you decided in the first second. 0:07. Hand grabs her chin, tilts her face up. She's looking into the camera from below with his fingers under her jaw. On paper a guy is holding his girlfriend's face. On paper it's nothing. On screen it's everything. The video loops and you're watching the hair grab again, already knowing it's just glasses, and it looks exactly the same. Knowing the punchline doesn't undo the setup. Your brain sees it the same way every time. The format: hand from above, camera from below, one accessory. Glasses, hair tie, necklace, doesn't matter. That geometry is the entire trick. Black top, pearl necklace, white room. If she was in sweats on a couch this would be a vlog. In this outfit with this lighting it's a scene. If you see a hand from above and a camera from below, your brain already finished the video for them. She didn't do anything. He just took off her glasses.

framexin

63,594 görüntüleme • 2 ay önce

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

This guy built a visual scanner that reads 468 points on his face and 42 points on his hands from a regular webcam and turns them into a cloud of thousands of particles right between his palms. Inside, MediaPipe and TouchDesigner are linked: the first captures hands and face from the webcam with high accuracy, the second turns those coordinates into a live plane and feeds it into a POP system that instantly generates a swarm of particles in the shape of a head. No studio, no render farmer, no VR headset. Just a laptop, a webcam, and 1 TouchDesigner session. And traditional VJ studios keep teams of 5 people on a setup with lighting, custom hardware, and commercial plugins, while his expenses are only a TouchDesigner subscription and a regular USB camera. One laptop runs MediaPipe and TouchDesigner simultaneously, holds the camera stream at 60 FPS without drops, and in parallel processes 468 face points + 21 points on each hand. The camera captures frame after frame, MediaPipe in real time sends TouchDesigner the finger coordinates and face geometry, and the POP operator inside the engine translates those numbers into thousands of particle points with colors from bright pink to gold. This setup immediately defines the role of the tool and the limits of its autonomy. It knows where the fingertips are at every moment of the frame. It knows how to read the face geometry at any angle to the camera. It knows how to draw a swarm of particles between them with the right color and contour. → MediaPipe pulls 468 points from the face and 21 points from each hand, 60 times per second → TouchDesigner receives those coordinates, builds a virtual rectangle between the fingertips, and feeds it into the POP system → POP generates thousands of particle points in the shape of a head, coloring them in a gradient from bright pink to gold → The HUD layer adds green corners and a blue neon frame, styling the image like an AR interface → All layers assemble into 1 real-time frame that projects back onto the video in the camera window → The final image is recorded to a file or broadcast to a projector for a live installation And only when the guy spreads his hands wider does the plane between the palms stretch; brings them together, it narrows. Otherwise the system runs on its own. And when he moves from his home room to a concert hall, the same laptop with the same webcam launches the same TouchDesigner session in just 5 minutes, without reconfiguration, without a new team, and without a single line of new code. In his work setup there is no studio of his own and no team for assembly. On the desk sits a laptop with a webcam, on top run MediaPipe and TouchDesigner with POP operators, and the same setup through a USB camera moves to any concert without a new configuration. Out of everything I have seen this year, this is the cleanest Creative Coding setup on 1 laptop: 0 render farms, 0 studio lighting, and between them 3 libraries, thousands of particle points, and 1 webcam.

Blaze

38,242 görüntüleme • 5 ay önce

Beauty ads just changed forever. Free Claude Opus 4.8 + GPT Image 2 + Seedance 2.0 workflow to spin up 100s of video ads. No studio, no model, no macro lens, no shoot day. Here's what nobody in beauty marketing wants to say out loud. That glossy lip shot. The droplet hitting the surface in slow motion. The whip-pan into the next scene. The crystalline product splash. All the stuff that used to need a real set, a real camera op, and a full shoot day. You can generate every frame of it from a text prompt now, and stitch it into a finished ad before your coffee goes cold. The workflow is almost stupidly simple: → Tell Claude Opus 4.8 the beauty shot you want (dewy skin macro, gloss-on-lips contact, ripple transition, the works) → Claude turns it into a shot-by-shot storyboard plus a prompt for every frame → GPT Image 2 generates the photoreal stills, frame by frame → Seedance 2.0 animates each one into a clip with that buttery slow-mo glide → You drop the clips into HeyOz and assemble the full ad in one place The real unlock is volume. This isn't one hero video. Once the workflow is dialed, you spin up hundreds of variations. Different shades, different models, different hooks, different transitions. The exact creative volume Meta rewards, minus the production cost that used to make it impossible. Old way: one shoot, one look, $10k+, weeks of waiting. New way: a hundred angles, any look, a few dollars each, same afternoon. I wrote up the entire workflow. The Claude storyboard prompt, the GPT Image 2 frame prompts, the Seedance motion settings, the full assembly flow. Completely free, no email gate. Want it? Comment "GLOSS" and I'll send it straight over. (make sure you're following so it can actually reach you)

Beauty ads just changed forever. Free Claude Opus 4.8 + GPT Image 2 + Seedance 2.0 workflow to spin up 100s of video ads. No studio, no model, no macro lens, no shoot day. Here's what nobody in beauty marketing wants to say out loud. That glossy lip shot. The droplet hitting the surface in slow motion. The whip-pan into the next scene. The crystalline product splash. All the stuff that used to need a real set, a real camera op, and a full shoot day. You can generate every frame of it from a text prompt now, and stitch it into a finished ad before your coffee goes cold. The workflow is almost stupidly simple: → Tell Claude Opus 4.8 the beauty shot you want (dewy skin macro, gloss-on-lips contact, ripple transition, the works) → Claude turns it into a shot-by-shot storyboard plus a prompt for every frame → GPT Image 2 generates the photoreal stills, frame by frame → Seedance 2.0 animates each one into a clip with that buttery slow-mo glide → You drop the clips into HeyOz and assemble the full ad in one place The real unlock is volume. This isn't one hero video. Once the workflow is dialed, you spin up hundreds of variations. Different shades, different models, different hooks, different transitions. The exact creative volume Meta rewards, minus the production cost that used to make it impossible. Old way: one shoot, one look, $10k+, weeks of waiting. New way: a hundred angles, any look, a few dollars each, same afternoon. I wrote up the entire workflow. The Claude storyboard prompt, the GPT Image 2 frame prompts, the Seedance motion settings, the full assembly flow. Completely free, no email gate. Want it? Comment "GLOSS" and I'll send it straight over. (make sure you're following so it can actually reach you)

Ahad Shams | AI Ads Guy

11,303 görüntüleme • 4 ay önce

This guy pulls $72,000 a month off a network of 12 influencers who do not exist and not one of them lives past his webcam. He got tired of watching brands burn $8,000 a month on castings and influencer contracts and a film crew for a couple of clips. So he built a generative studio and raised a whole roster from scratch not just one face. One of his clips costs $0.40 in compute. One post from a real influencer runs $1,500. He never shows up on camera himself. On camera there is only his motion under someone else's face. No model. No film crew. No casting. Here is the exact breakdown: → First he builds not a face but an operator core: one set of his expressions and one rig and a library of personas that snap onto him → Then he locks each face and only once it holds 98% across 1,000 frames even on a sharp head turn does he push the persona into the feed. Today a blonde from the US tomorrow an Asian girl but the operator behind them all stays one → A real-time rig lays a face over his webcam. Flux and LoRA hold each persona. ElevenLabs gives each one her own voice and accent. Higgsfield and Kling build the clips → TikTok and Reels push the clips into the tags. One clip pulls 200,000 to 1,200,000 views and the face is matched to the market. It reads as a live person not a render The key move that 96% skip: they invest in the face not in the operator behind it. Generate another pretty face and join a line of 800 just like it this week. Put a live operator behind the face with timing and pauses and reactions and the persona lands in 2 seconds. Pull the operator and the face glazes over and the watch time collapses. Here is where the money actually gets pulled: → Affiliate where each persona drives offers matched to her audience at 8-15% on every sale → His own stores where the top personas front his own product at 65% margin on a $52 average order → Face licensing where a brand keeps a persona on retainer at $2,500 a month so that is $7,500 a quarter not one check → Managed network as a service where he runs other people's personas at $1,800 a month each → A network of faces 12 personas across 12 markets off one operator The numbers are silly. A clip costs $0.40 in compute. One clip drives up to 1,200,000 views straight to the offers. At a 0.7% click and a $52 order that is hundreds of sales off one video. And the whole network runs on $120 a month in software and one webcam. The first night a new persona went up her clip pulled 640,000 views in 9 hours. Before an agency would have answered one email the offers cleared 280 sales for $13,700. 3,900 comments under a girl who 72 hours earlier was a prompt and one reference frame. The comments fill with "wait is this all one guy" and that argument is the fuel the algorithm runs on. Real agencies are still casting influencers and clearing contracts for weeks. And he ships a new face before they answer one email. Not a single casting. Not a single shoot. Not a dollar on ads. Just one operator. Twelve faces over him. And the discipline to sell the brain behind the persona not the face itself. Half of you are already typing that this is too much. The other half are already building their first persona. Which half are you in?

Shade

37,090 görüntüleme • 3 ay önce

IF THIS HIT YOUR FEED YOU WOULD NOT CLOCK IT AS AI + TINY TENNIS SKIRT A redhead sits on a patio step in a white ruched sports bra and a micro tennis skirt, gold heart on her chest, one hand buried in her hair, the other planted on the ledge, smiling straight into the lens. Nothing about the pose or the fabric feels generated. This used to be a guaranteed fail. A hand in long hair made strands glue to the fingers. A sitting mini skirt either fused to the thigh or floated like a napkin. Ruched bras flattened into a single white slab, and the midriff lost every shadow the second she leaned. Home patios with tables, tile, and a person in the doorway turned into mush. Now it holds. Individual red strands wrap her fingers instead of melting into them, the skirt keeps a real hem and drape over her hip, the ruching on the bra stays gathered instead of plastic, and the tiled floor and hallway stay sharp behind her. The post that prints reach isn’t a red carpet render. It’s a girl on her own porch touching her hair like the camera just caught her.

IF THIS HIT YOUR FEED YOU WOULD NOT CLOCK IT AS AI + TINY TENNIS SKIRT A redhead sits on a patio step in a white ruched sports bra and a micro tennis skirt, gold heart on her chest, one hand buried in her hair, the other planted on the ledge, smiling straight into the lens. Nothing about the pose or the fabric feels generated. This used to be a guaranteed fail. A hand in long hair made strands glue to the fingers. A sitting mini skirt either fused to the thigh or floated like a napkin. Ruched bras flattened into a single white slab, and the midriff lost every shadow the second she leaned. Home patios with tables, tile, and a person in the doorway turned into mush. Now it holds. Individual red strands wrap her fingers instead of melting into them, the skirt keeps a real hem and drape over her hip, the ruching on the bra stays gathered instead of plastic, and the tiled floor and hallway stay sharp behind her. The post that prints reach isn’t a red carpet render. It’s a girl on her own porch touching her hair like the camera just caught her.

aitifa uncut

19,374 görüntüleme • 20 gün önce

Created with Sedance 2.0 Video Prompt : A cinematic early morning bedroom scene. A beautiful young woman is sleeping peacefully on a soft white bed inside a cozy modern room. The first golden rays of sunrise slowly enter through the curtains, casting warm light across her face. Dust particles gently float in the sunbeams. The camera slowly pushes in as she opens her eyes naturally and takes a calm breath. She sits up on the bed, stretches slightly, and places her feet on the wooden floor. Wearing a light cream-colored morning outfit, she slowly walks toward a large window. The curtains move softly with the breeze. She opens the window, and fresh morning air enters the room. Outside, green trees sway gently, birds fly across the sky, and soft sunlight illuminates the surroundings. The sound of birds singing fills the air. She closes her eyes, takes a deep breath, and smiles peacefully. Her hair moves gently in the breeze as the camera circles around her. The final shot shows her standing by the window, enjoying the quiet morning while sunlight fills the room. Style: Ultra-realistic, cinematic lighting, realistic skin details, soft shadows, shallow depth of field, smooth camera movements, warm color grading, volumetric sunlight, 4K, high detail, natural emotions, movie-quality visuals. --- Camera Shots (10 Seconds) 0–2 sec: Close-up of the sleeping girl as golden sunlight slowly reaches her face. 2–4 sec: She opens her eyes and sits up while the camera gently moves closer. 4–7 sec: She walks to the window and slowly opens it. 7–10 sec: Fresh air enters, birds sing, and she smiles peacefully while enjoying the morning. --- Voice Over "As the sun gently touches her face, a new day begins. The songs of the morning birds fill the air, and in this quiet moment, she finds peace."

Created with Sedance 2.0 Video Prompt : A cinematic early morning bedroom scene. A beautiful young woman is sleeping peacefully on a soft white bed inside a cozy modern room. The first golden rays of sunrise slowly enter through the curtains, casting warm light across her face. Dust particles gently float in the sunbeams. The camera slowly pushes in as she opens her eyes naturally and takes a calm breath. She sits up on the bed, stretches slightly, and places her feet on the wooden floor. Wearing a light cream-colored morning outfit, she slowly walks toward a large window. The curtains move softly with the breeze. She opens the window, and fresh morning air enters the room. Outside, green trees sway gently, birds fly across the sky, and soft sunlight illuminates the surroundings. The sound of birds singing fills the air. She closes her eyes, takes a deep breath, and smiles peacefully. Her hair moves gently in the breeze as the camera circles around her. The final shot shows her standing by the window, enjoying the quiet morning while sunlight fills the room. Style: Ultra-realistic, cinematic lighting, realistic skin details, soft shadows, shallow depth of field, smooth camera movements, warm color grading, volumetric sunlight, 4K, high detail, natural emotions, movie-quality visuals. --- Camera Shots (10 Seconds) 0–2 sec: Close-up of the sleeping girl as golden sunlight slowly reaches her face. 2–4 sec: She opens her eyes and sits up while the camera gently moves closer. 4–7 sec: She walks to the window and slowly opens it. 7–10 sec: Fresh air enters, birds sing, and she smiles peacefully while enjoying the morning. --- Voice Over "As the sun gently touches her face, a new day begins. The songs of the morning birds fill the air, and in this quiet moment, she finds peace."

Yashal Ai

11,454 görüntüleme • 3 ay önce