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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 freeshow more

Ridark

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28,448 views • 20 days ago •via X (Twitter)

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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.

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.

Neuro

28,053 views • 20 days ago

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 views • 10 days ago

$EVERYONE SAYS AI CANNOT INVENT A VISUAL METAPHOR i asked Seedance 2.5 for "a person in a desert catches a small cloud in a plastic bag." one sentence. one generate. went to refill my water. 00:00 – a desert. flat sand. tire tracks. a small white cloud hovers a few feet above the ground. a pair of hands holds an open plastic bag beneath it. 00:04 – the cloud drifts down. it touches the bag opening. moisture beads on the inside of the plastic. 00:07 – the hands close the bag. the cloud sits inside it. it's the size of a grapefruit. condensation drips down the sides. the bag sags with the weight of water vapor. 00:10 – the hands lift the bag. the cloud shifts inside. light refracts through the wet plastic differently on the side facing the sun. i paused on that last frame. the refraction is correct. the side of the bag facing the light is brighter. the condensation acts as a lens. the cloud's shadow sits on the sand below at the correct angle. nobody prompted "condensation as lens." nobody prompted "cloud weight sags the bag." the model understood that if you put water vapor in plastic, the plastic gets wet, and wet plastic bends light. The stack: -> Claude Fable 5.1 for writing the cloud capture choreography, hand positioning, and material interaction logic -> Veo 3.1 for rendering the desert environment with photorealistic sand grain texture and atmospheric haze -> Seedance 2.5 for animating the cloud descent, plastic bag deformation under vapor weight, and condensation propagation -> Kling 3.0 Omni for generating the light refraction through wet PVC and the shadow projection on sand in 4K -> ElevenLabs Spatial for desert wind, plastic crinkle, and a faint moisture hiss as the cloud contacts the bag the clip is 11 seconds long. it contains more correct physics than most VFX shots in a $150M movie. the model didn't just render a visual. it rendered what happens when you trap weather.$

EVERYONE SAYS AI CANNOT INVENT A VISUAL METAPHOR i asked Seedance 2.5 for "a person in a desert catches a small cloud in a plastic bag." one sentence. one generate. went to refill my water. 00:00 – a desert. flat sand. tire tracks. a small white cloud hovers a few feet above the ground. a pair of hands holds an open plastic bag beneath it. 00:04 – the cloud drifts down. it touches the bag opening. moisture beads on the inside of the plastic. 00:07 – the hands close the bag. the cloud sits inside it. it's the size of a grapefruit. condensation drips down the sides. the bag sags with the weight of water vapor. 00:10 – the hands lift the bag. the cloud shifts inside. light refracts through the wet plastic differently on the side facing the sun. i paused on that last frame. the refraction is correct. the side of the bag facing the light is brighter. the condensation acts as a lens. the cloud's shadow sits on the sand below at the correct angle. nobody prompted "condensation as lens." nobody prompted "cloud weight sags the bag." the model understood that if you put water vapor in plastic, the plastic gets wet, and wet plastic bends light. The stack: -> Claude Fable 5.1 for writing the cloud capture choreography, hand positioning, and material interaction logic -> Veo 3.1 for rendering the desert environment with photorealistic sand grain texture and atmospheric haze -> Seedance 2.5 for animating the cloud descent, plastic bag deformation under vapor weight, and condensation propagation -> Kling 3.0 Omni for generating the light refraction through wet PVC and the shadow projection on sand in 4K -> ElevenLabs Spatial for desert wind, plastic crinkle, and a faint moisture hiss as the cloud contacts the bag the clip is 11 seconds long. it contains more correct physics than most VFX shots in a $150M movie. the model didn't just render a visual. it rendered what happens when you trap weather.

Ridark

56,610 views • 1 month ago

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 views • 4 months ago

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 views • 3 months ago

🚨 Warner Bros spent $79,000,000 making Tom and Jerry live-action in 2019 a 24-year-old spent $50 last month and cleared $11,900 doing the same trick in CapCut turning old cartoons real is blowing up on Douyin: the original Tom and Jerry up top, the same shot rebuilt in 3D below, a jacked bulldog gripping a real cat. she copied it and hit TikTok and Reels first. > Research: find the clip pulling 10x a channel's normal views: 1 day > Claude: break the cartoon into a shot list, frame by frame: 20 min > CapCut: rebuild each shot photoreal, add AI voice and captions: 40 min > Make: auto-post to TikTok, Shorts, Reels, pull the views at 48h $50 a month in tools. the cartoon does the hooking for free. Hollywood took 2 years to make one cat real. she ships a new one daily. her whole workflow is in the article above👇

🚨 Warner Bros spent $79,000,000 making Tom and Jerry live-action in 2019 a 24-year-old spent $50 last month and cleared $11,900 doing the same trick in CapCut turning old cartoons real is blowing up on Douyin: the original Tom and Jerry up top, the same shot rebuilt in 3D below, a jacked bulldog gripping a real cat. she copied it and hit TikTok and Reels first. > Research: find the clip pulling 10x a channel's normal views: 1 day > Claude: break the cartoon into a shot list, frame by frame: 20 min > CapCut: rebuild each shot photoreal, add AI voice and captions: 40 min > Make: auto-post to TikTok, Shorts, Reels, pull the views at 48h $50 a month in tools. the cartoon does the hooking for free. Hollywood took 2 years to make one cat real. she ships a new one daily. her whole workflow is in the article above👇

Fokki

37,270 views • 3 months ago

She pulls in $110,000 a month from 15 second bedroom dance clips. Brands are already dropping real influencers to sign her instead. Luna isn't real. She's a fully synthetic model. Built by an 19 year old student in Canada. Runs the whole thing from his bedroom with Python and an RTX card. The hair physics come from a custom video diffusion layer, frame by frame. The lighting and shadows are rendered so she sits naturally in the room, not pasted in. A fully automated pipeline pulls trending audio, maps her onto it, and posts across 40+ accounts. He never touches a clip. No contracts. No travel. No days off. 40 million views a week. Zero overhead. The wall poster in the background is the only real thing left in the frame.

She pulls in $110,000 a month from 15 second bedroom dance clips. Brands are already dropping real influencers to sign her instead. Luna isn't real. She's a fully synthetic model. Built by an 19 year old student in Canada. Runs the whole thing from his bedroom with Python and an RTX card. The hair physics come from a custom video diffusion layer, frame by frame. The lighting and shadows are rendered so she sits naturally in the room, not pasted in. A fully automated pipeline pulls trending audio, maps her onto it, and posts across 40+ accounts. He never touches a clip. No contracts. No travel. No days off. 40 million views a week. Zero overhead. The wall poster in the background is the only real thing left in the frame.

wluha

98,066 views • 2 months ago

Seedance 2.0 / continuous one-take / hyperreal water physics. It takes lot of time to make VFX rendering for a shot like this. Seedance just generated it in minutes First frame image prompt 🔽 A lone emergency technician in an orange survival jacket stands on the shattered roof of a flooded museum in a drowned European capital, storm clouds overhead, broken statues and floating debris below, cold blue-grey palette, cinematic disaster realism, wet surfaces, strong scale, 35mm film look Created with nano banana pro ImagineArt Video Prompt: 👇 "Disaster film realism, one-take. The camera starts high above a drowned capital city in violent storm weather, then dives toward a lone emergency technician standing on the shattered roof of a flooded museum. He sees a rescue flare in the distance and runs. The camera follows tightly behind him as he sprints across collapsing rooftops, leaps over broken skylights, slides down a tilted glass dome, and grabs a dangling cable. Below, dark floodwater surges through streets filled with drifting cars and statues. He lands on a partially submerged tram roof, keeps moving, and reaches a rescue beacon platform just as a giant wave crashes past behind him. Cold grey-blue apocalyptic palette, hyperreal water physics, wind, spray, handheld urgency, one continuous shot, no cuts."

Seedance 2.0 / continuous one-take / hyperreal water physics. It takes lot of time to make VFX rendering for a shot like this. Seedance just generated it in minutes First frame image prompt 🔽 A lone emergency technician in an orange survival jacket stands on the shattered roof of a flooded museum in a drowned European capital, storm clouds overhead, broken statues and floating debris below, cold blue-grey palette, cinematic disaster realism, wet surfaces, strong scale, 35mm film look Created with nano banana pro ImagineArt Video Prompt: 👇 "Disaster film realism, one-take. The camera starts high above a drowned capital city in violent storm weather, then dives toward a lone emergency technician standing on the shattered roof of a flooded museum. He sees a rescue flare in the distance and runs. The camera follows tightly behind him as he sprints across collapsing rooftops, leaps over broken skylights, slides down a tilted glass dome, and grabs a dangling cable. Below, dark floodwater surges through streets filled with drifting cars and statues. He lands on a partially submerged tram roof, keeps moving, and reaches a rescue beacon platform just as a giant wave crashes past behind him. Cold grey-blue apocalyptic palette, hyperreal water physics, wind, spray, handheld urgency, one continuous shot, no cuts."

Dheepan Ratnam

33,863 views • 6 months ago

fuck it, im sharing the whole thing one of these girls is real. the other one never existed same video, frame for frame. the comments will not agree on which is which this used to take my best setup an hour per version. seedance 2.5 + claude fable turned it into a 10 minute habit fable writes her identity down to the pores seedance 2.5 rebuilds the entire video around her. motion, cuts, audio, everything new girl, one prompt new room, one prompt new winner to clone, one prompt a creator is $200-500 a video and one take a week. this is 50 takes by tonight for a few dollars drop "UGC" and ill dm you the full stack (must RT + follow so i can dm) if you're a brand and want this for your products/app launch a campaign on Affiliate Network below

Sam

16,412 views • 2 months ago

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 views • 1 month ago

A girl makes $9,000 a month sitting by the pool with just a tablet She finds a viral kids song like Baby Shark or Surprise Symphony. Copies the info and asks AI to build a prompt for a show just like it. One message back and a full video concept is ready. She drops it into Picsart and Veo 3.1 builds the entire clip. Dancing alphabet characters, glowing stars, animals celebrating together. No studio, no camera, no laptop, just poolside and two apps. Kids content gets billions of views because parents loop it on repeat for hours. That loop is what gets her to $9,000 every single month. Save this before everyone starts running kids channels from their sunbed.

A girl makes $9,000 a month sitting by the pool with just a tablet She finds a viral kids song like Baby Shark or Surprise Symphony. Copies the info and asks AI to build a prompt for a show just like it. One message back and a full video concept is ready. She drops it into Picsart and Veo 3.1 builds the entire clip. Dancing alphabet characters, glowing stars, animals celebrating together. No studio, no camera, no laptop, just poolside and two apps. Kids content gets billions of views because parents loop it on repeat for hours. That loop is what gets her to $9,000 every single month. Save this before everyone starts running kids channels from their sunbed.

winkle.

3,403,629 views • 4 months ago

We may be overestimating the importance of the generation step in AI video. Getting a model to produce a beautiful 10-second clip is impressive. But filmmaking has never been just about producing footage. It’s about deciding what happens before the camera rolls, controlling the shot, and shaping the material afterward. That’s why this workflow is interesting: GPT-6 Astra establishes the 3D space and camera + character movement in the Viewport. The scene is manually brought into CapCut PC. Seedance 2.5 renders the video. Then CapCut PC takes the result through post-production. Generation becomes one stage in a larger pipeline rather than the finish line. Maybe that’s the direction AI video needs to take if it’s going to move beyond “cool clips” and toward actual filmmaking workflows. And CapCut PC is a pretty natural place to experiment with that full process. #CapCutPC #GPT6Astra #AIVideo #Seedance25

We may be overestimating the importance of the generation step in AI video. Getting a model to produce a beautiful 10-second clip is impressive. But filmmaking has never been just about producing footage. It’s about deciding what happens before the camera rolls, controlling the shot, and shaping the material afterward. That’s why this workflow is interesting: GPT-6 Astra establishes the 3D space and camera + character movement in the Viewport. The scene is manually brought into CapCut PC. Seedance 2.5 renders the video. Then CapCut PC takes the result through post-production. Generation becomes one stage in a larger pipeline rather than the finish line. Maybe that’s the direction AI video needs to take if it’s going to move beyond “cool clips” and toward actual filmmaking workflows. And CapCut PC is a pretty natural place to experiment with that full process. #CapCutPC #GPT6Astra #AIVideo #Seedance25

AIMATRIX

16,778 views • 1 month ago

You don't understand... Higgsfield MCP + Claude just automated AI film making. Every single step you used to grind through to make an AI movie, you can now do 10x faster. Drop the script into Claude Opus 4.8 and say: "Here's my script. Break it into a full shotlist. Shot number, scene, shot type, camera move and the action in each frame." Now the whole film is mapped, shot by shot. - Pull your assets. Ask Claude: "From this shotlist, list every character, every location and every prop across the whole film." That's your build list. The stuff you would need to generate and give as references in next steps. - Build the character sheets. Higgsfield MCP is connected, so Claude has hands now to do stuff directly. It generates the images itself. Have the full body, back view and close up in the character sheet. One per character. Each sheet becomes the locked reference for that face. Same move for locations, generate the empty plate for each one before anyone steps into it. - Generate the frames. Feed Claude the references plus the shot and have it write and fire the Seedance 2.0 prompt. "Using the lead's character sheet and the alley plate, generate shot 4 in Seedance 2.0. Low angle, slow push-in, rain." Claude builds the prompt, calls Seedance 2.0 and the frame lands back in chat. Use a Seedance 2.0 skill to teach Claude how to prompt it properly. Now, there are 3 ways to make the shots. Pick one per scene. - Pure prompting. Fastest one. You describe the action in words and let Seedance interpret it. For consistency across a sequence, feed it a frame from the previous shot so the look carries. - Storyboarding. You hand it a panel and it matches that composition exactly. Way more control over how the shot is framed. The tradeoff is that it can introduce more cuts than you actually want. - Path Control System This is the latest technique Seedance 2.0 technique. Generate a still base plate of the scene. Draw a red line across it to mark the exact path of the movement, then describe what's happening. Seedance follows that line for the action. Also ask Claude to remove the red line when animating. This is the one for anything where motion has to land precisely. The output reads like real live action. - Lastly, generate every clip you need, then cut them together. Get it to Capcut for editing and audio design. And that's it. The pipeline that used to need a full crew and a studio can now run from one Claude chat. 2026 is gonna be wild

You don't understand... Higgsfield MCP + Claude just automated AI film making. Every single step you used to grind through to make an AI movie, you can now do 10x faster. Drop the script into Claude Opus 4.8 and say: "Here's my script. Break it into a full shotlist. Shot number, scene, shot type, camera move and the action in each frame." Now the whole film is mapped, shot by shot. - Pull your assets. Ask Claude: "From this shotlist, list every character, every location and every prop across the whole film." That's your build list. The stuff you would need to generate and give as references in next steps. - Build the character sheets. Higgsfield MCP is connected, so Claude has hands now to do stuff directly. It generates the images itself. Have the full body, back view and close up in the character sheet. One per character. Each sheet becomes the locked reference for that face. Same move for locations, generate the empty plate for each one before anyone steps into it. - Generate the frames. Feed Claude the references plus the shot and have it write and fire the Seedance 2.0 prompt. "Using the lead's character sheet and the alley plate, generate shot 4 in Seedance 2.0. Low angle, slow push-in, rain." Claude builds the prompt, calls Seedance 2.0 and the frame lands back in chat. Use a Seedance 2.0 skill to teach Claude how to prompt it properly. Now, there are 3 ways to make the shots. Pick one per scene. - Pure prompting. Fastest one. You describe the action in words and let Seedance interpret it. For consistency across a sequence, feed it a frame from the previous shot so the look carries. - Storyboarding. You hand it a panel and it matches that composition exactly. Way more control over how the shot is framed. The tradeoff is that it can introduce more cuts than you actually want. - Path Control System This is the latest technique Seedance 2.0 technique. Generate a still base plate of the scene. Draw a red line across it to mark the exact path of the movement, then describe what's happening. Seedance follows that line for the action. Also ask Claude to remove the red line when animating. This is the one for anything where motion has to land precisely. The output reads like real live action. - Lastly, generate every clip you need, then cut them together. Get it to Capcut for editing and audio design. And that's it. The pipeline that used to need a full crew and a studio can now run from one Claude chat. 2026 is gonna be wild

Rez Karim

11,318 views • 4 months ago

american guy made $10,845 in a single month from a kids youtube channel he built with AI no camera, no animation skills, no voiceover. openart writes the script, generates the characters, renders the whole episode the numbers sound fake. first month the channel barely moved. that's where most people quit then one short hit 800K views. youtube started pushing it. and month three came in over $10,845 his whole workflow fits in one prompt. he opens openart, types a description of a 3D animated nursery scene, and the tool spits out a full short film ready to upload he showed it live. one prompt, one render, one upload. he can also vibe direct longer videos up to 5 minutes for higher CPM kids content is the highest-paying niche on youtube. parents leave it on autoplay for hours. one video can loop all day and the algorithm keeps feeding it to new viewers cocomelon does 10M views per video with a full studio. he does 100-200K views per video with a laptop. the CPM on kids content does the math for him no face on camera. no brand deals. no editing software. just prompts and uploads this used to take a pixar-level team and months of rendering. now it takes one AI tool and a free afternoon full workflow is in the video - save it before youtube patches the meta

0xbobaa

48,503 views • 2 months ago

🚨 Disney spent over $150,000,000 making a Zootopia movie a 23-year-old American student recreated its entire red-carpet premiere on a laptop for $50, and the clip is pulling millions of views. Margot Robbie as Judy Hopps. Dwayne Johnson as a horse in a tuxedo. Shakira as Gazelle. none of it real. these celebrity premieres are the format taking over your feed right now. > Research scores the outliers: views ÷ channel median, over 30 and you copy that format this week > Claude reskins the winning shape onto a new subject and writes the shot list: 20 minutes > CapCut generates every celebrity, every reveal, exports 9:16: 1 hour > Make posts to 3 platforms and reads the view counts back in 48 hours 4 tools. $50/month. Disney pays a studio to premiere one film. this student ships a new one every week. first people to run the format eat the whole trend. the whole factory is in the article above👇

🚨 Disney spent over $150,000,000 making a Zootopia movie a 23-year-old American student recreated its entire red-carpet premiere on a laptop for $50, and the clip is pulling millions of views. Margot Robbie as Judy Hopps. Dwayne Johnson as a horse in a tuxedo. Shakira as Gazelle. none of it real. these celebrity premieres are the format taking over your feed right now. > Research scores the outliers: views ÷ channel median, over 30 and you copy that format this week > Claude reskins the winning shape onto a new subject and writes the shot list: 20 minutes > CapCut generates every celebrity, every reveal, exports 9:16: 1 hour > Make posts to 3 platforms and reads the view counts back in 48 hours 4 tools. $50/month. Disney pays a studio to premiere one film. this student ships a new one every week. first people to run the format eat the whole trend. the whole factory is in the article above👇

Fokki

81,038 views • 2 months ago

clipping agencies rent offices now, $500,000 a year ten editors, a manager, a lease, and the only thing any of them is paid for is noticing noticing is 310 lines of python, and i gave it away it runs on Robinhood Chain, so the clip pays whoever cut it CUT never sees a single frame of the stream. it reads chat, because chat knows before the editor does, before the dashboard does, before the streamer does [what those 310 lines do] 1. measure the last 10 seconds against that stream's own 5 minute baseline 2. never a global number, a big channel idling still beats a small one peaking 3. count how many people just typed clip it 4. call the clip api in the same second, not after the room reacts that last one is the whole thing. a twitch clip only keeps the 90 seconds before you hit the button, so if you noticed the moment yourself, you already lost it no key to read chat. it cannot post for you. it runs on your machine, not mine one command replays three minutes of recorded chat offline and fires a real moment on your screen, so you can watch it work before you trust it

clipping agencies rent offices now, $500,000 a year ten editors, a manager, a lease, and the only thing any of them is paid for is noticing noticing is 310 lines of python, and i gave it away it runs on Robinhood Chain, so the clip pays whoever cut it CUT never sees a single frame of the stream. it reads chat, because chat knows before the editor does, before the dashboard does, before the streamer does [what those 310 lines do] 1. measure the last 10 seconds against that stream's own 5 minute baseline 2. never a global number, a big channel idling still beats a small one peaking 3. count how many people just typed clip it 4. call the clip api in the same second, not after the room reacts that last one is the whole thing. a twitch clip only keeps the 90 seconds before you hit the button, so if you noticed the moment yourself, you already lost it no key to read chat. it cannot post for you. it runs on your machine, not mine one command replays three minutes of recorded chat offline and fires a real moment on your screen, so you can watch it work before you trust it

Carver

285,799 views • 1 month ago

🚨 Apple spends over $2,000,000 to shoot one iPhone commercial a 24-year-old Chinese student recreated that exact ad on a laptop for $50 and the clip is pulling millions of views. the subway. the floating phone. the hand reaching for the screen. she made all of it with AI. right now this is the trend flooding your feed: one person shooting ads that look like Apple made them. > Research scores the outliers: views ÷ channel median, over 30 and you copy that format this week > Claude reskins the winning shape onto a new product and writes the shot list: 20 minutes > CapCut generates every frame, the lighting, the motion, exports 9:16: 1 hour > Make posts to 3 platforms and reads the view counts back in 48 hours 4 tools. $50/month. Apple hires an agency for one spot. this student ships a new one every week. first people to run the format eat the whole trend. the whole factory is in the article above👇

🚨 Apple spends over $2,000,000 to shoot one iPhone commercial a 24-year-old Chinese student recreated that exact ad on a laptop for $50 and the clip is pulling millions of views. the subway. the floating phone. the hand reaching for the screen. she made all of it with AI. right now this is the trend flooding your feed: one person shooting ads that look like Apple made them. > Research scores the outliers: views ÷ channel median, over 30 and you copy that format this week > Claude reskins the winning shape onto a new product and writes the shot list: 20 minutes > CapCut generates every frame, the lighting, the motion, exports 9:16: 1 hour > Make posts to 3 platforms and reads the view counts back in 48 hours 4 tools. $50/month. Apple hires an agency for one spot. this student ships a new one every week. first people to run the format eat the whole trend. the whole factory is in the article above👇

Fokki

73,704 views • 2 months ago

UPDATE: Charlie Kirk 🚨 Muzzle Flash: Second Shooter Location, Reflection, or Both? This video captures a flash on a window right as Charlie Kirk was shot. Let’s break this down… follow the numbers on the videos. #1. This video shows what appears to be a muzzle flash, just as Charlie is shot, leading people to believe the shooter was to Charlie’s right.. Notate the people to the left of the flash #2. This photo shows the location of the flash. Notate people to the left, on a middle-landing on a staircase. #3. This photo shows a clearer image showing both the middle-landing and the same location of the flash. It is a window. #4 . This video shows the building behind Charlie, which is a long hallway. This debunks any claims the shot came from here. — I zoom in where Charlie was — I zoom in on staircase — I zoom in on the window/flash — I zoom in on where suspected shooter was #5. I notate the flash reflection angles. — Video angle #1 notated — two reflection paths notated in relation to Video angle #1. 1. Reflection angle shows where we were told the shooter was. 2. Reflection angle shows mirrored angle, obviously where there is no reports of a shooter being in. 🔻 Final conclusion: This to me is very likely a muzzle flash reflection from a far off location. I am unsure of the reflection angle however, but this can be 100% proven if someone were to recreate the angles… maybe with a flash camera. If anyone is willing to, or has the means to do this (safely), this will either prove the shot came where the FBI said it came from, or it will prove there was a second shooter, in the direction of the mirrored angle.

UPDATE: Charlie Kirk 🚨 Muzzle Flash: Second Shooter Location, Reflection, or Both? This video captures a flash on a window right as Charlie Kirk was shot. Let’s break this down… follow the numbers on the videos. #1. This video shows what appears to be a muzzle flash, just as Charlie is shot, leading people to believe the shooter was to Charlie’s right.. Notate the people to the left of the flash #2. This photo shows the location of the flash. Notate people to the left, on a middle-landing on a staircase. #3. This photo shows a clearer image showing both the middle-landing and the same location of the flash. It is a window. #4 . This video shows the building behind Charlie, which is a long hallway. This debunks any claims the shot came from here. — I zoom in where Charlie was — I zoom in on staircase — I zoom in on the window/flash — I zoom in on where suspected shooter was #5. I notate the flash reflection angles. — Video angle #1 notated — two reflection paths notated in relation to Video angle #1. 1. Reflection angle shows where we were told the shooter was. 2. Reflection angle shows mirrored angle, obviously where there is no reports of a shooter being in. 🔻 Final conclusion: This to me is very likely a muzzle flash reflection from a far off location. I am unsure of the reflection angle however, but this can be 100% proven if someone were to recreate the angles… maybe with a flash camera. If anyone is willing to, or has the means to do this (safely), this will either prove the shot came where the FBI said it came from, or it will prove there was a second shooter, in the direction of the mirrored angle.

MJTruthUltra

10,665,164 views • 1 year ago

A 20-year-old girl from Japan asked her boyfriend for $67. She never told him why. By the next morning, her 18-second clip had reached a million views. Her plan was simple: take the doll dress-up format already spreading everywhere and keep the same girl inside every outfit. The trend wasn’t hers. She borrowed the structure that was already working: close-up hands, a doll-sized figure, rapid outfit changes and a cozy room in the background. The $67 paid for four subscriptions. > Kimi K3 created the character file and wrote every shot prompt > Seedream generated the stills > Seedance animated only the images that passed the consistency check > ElevenLabs voiced the character’s final line That same video went live on TikTok, Reels, and Shorts in a single night. Then she ran the system again: different outfits, a different room, the same recognizable face. One evening of work. One character she can keep building around.

A 20-year-old girl from Japan asked her boyfriend for $67. She never told him why. By the next morning, her 18-second clip had reached a million views. Her plan was simple: take the doll dress-up format already spreading everywhere and keep the same girl inside every outfit. The trend wasn’t hers. She borrowed the structure that was already working: close-up hands, a doll-sized figure, rapid outfit changes and a cozy room in the background. The $67 paid for four subscriptions. > Kimi K3 created the character file and wrote every shot prompt > Seedream generated the stills > Seedance animated only the images that passed the consistency check > ElevenLabs voiced the character’s final line That same video went live on TikTok, Reels, and Shorts in a single night. Then she ran the system again: different outfits, a different room, the same recognizable face. One evening of work. One character she can keep building around.

Fokki

53,489 views • 1 month ago

THERE'S A TREND THAT COST WARNER BROS $68,000,000 — A 20-YEAR-OLD MADE $11,900 ON IT LAST MONTH I've been watching what actually breaks out on Douyin, and one format keeps showing up. The secret is that Chinese creators are turning old cartoons into live-action - frame for frame shot for shot. Not parody. Not reaction. Straight rebuilds of scenes everyone already knows by heart. Warner Bros spent $68 000 000 doing exactly this with Tom and Jerry in 2021. A 20-year-old saw the same trend on Douyin and cleared $11 900 last month by bringing the format west before anyone else did. Here's what the format actually is: • Pick a cartoon scene people already have memorized • Copy the shot list frame by frame — not the vibe, the actual shots • Rebuild each shot to look real, in order • Add AI voice and captions • Ship it to TikTok, Shorts, and Reels before the trend crosses over on its own Why this works: • The nostalgia does the hook for you — people recognize the scene in the first half second • Frame-for-frame copying means the pacing is already proven, you're not guessing at edit rhythm • The gap between "cartoon" and "real" is the entire payoff, and it's built into the format • Douyin already validated the demand — you're not testing whether it works, you're arbitraging a delay The actual workflow: • Research: check 40 channels, find the clip beating its own average — about a day • Claude: pull the shot list from the original, frame by frame — 20 minutes • CapCut: rebuild it shot by shot, AI voice, captions — 40 minutes • Make: auto-post to TikTok, Shorts, Reels, pull the numbers back in 48 hours Warner Bros needed a studio, a real lion, and a full crew for one scene. She needed a $50 loop and her own cat. If your content keeps flopping, it's probably not your editing. It's that you're inventing formats instead of importing ones that already proved themselves somewhere else.

THERE'S A TREND THAT COST WARNER BROS $68,000,000 — A 20-YEAR-OLD MADE $11,900 ON IT LAST MONTH I've been watching what actually breaks out on Douyin, and one format keeps showing up. The secret is that Chinese creators are turning old cartoons into live-action - frame for frame shot for shot. Not parody. Not reaction. Straight rebuilds of scenes everyone already knows by heart. Warner Bros spent $68 000 000 doing exactly this with Tom and Jerry in 2021. A 20-year-old saw the same trend on Douyin and cleared $11 900 last month by bringing the format west before anyone else did. Here's what the format actually is: • Pick a cartoon scene people already have memorized • Copy the shot list frame by frame — not the vibe, the actual shots • Rebuild each shot to look real, in order • Add AI voice and captions • Ship it to TikTok, Shorts, and Reels before the trend crosses over on its own Why this works: • The nostalgia does the hook for you — people recognize the scene in the first half second • Frame-for-frame copying means the pacing is already proven, you're not guessing at edit rhythm • The gap between "cartoon" and "real" is the entire payoff, and it's built into the format • Douyin already validated the demand — you're not testing whether it works, you're arbitraging a delay The actual workflow: • Research: check 40 channels, find the clip beating its own average — about a day • Claude: pull the shot list from the original, frame by frame — 20 minutes • CapCut: rebuild it shot by shot, AI voice, captions — 40 minutes • Make: auto-post to TikTok, Shorts, Reels, pull the numbers back in 48 hours Warner Bros needed a studio, a real lion, and a full crew for one scene. She needed a $50 loop and her own cat. If your content keeps flopping, it's probably not your editing. It's that you're inventing formats instead of importing ones that already proved themselves somewhere else.

Nexlow

49,493 views • 2 months ago