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Seedance 2.0 Parameter Based Prompts I've been experimenting with variable-based prompting in Seedance 2.0 and built a modular template for these bullet-time selfie sequences. The main video was made with a different prompt. I used it as a base to build this template. It won't always be perfect depending...

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Kōda

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14,985 views • 3 months ago •via X (Twitter)

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

Zentrix⌚️

12,846 views • 27 days ago

I just dropped myself into a Taylor Swift-style music video without writing a single prompt, timeline, or storyboard. I uploaded one photo and the song. That's it. Atlabs AI took over from there: • Built the character sheet • Planned the scenes • Generated the prompts • Synced every cut to the beat • Delivered a finished edit Most AI video tools promise automation, but the tradeoff is usually creative control. This was the opposite. The agents handled the production work while I focused on direction. Every scene, transition, framing choice, and creative decision stayed in my hands. When the edit was ready, I could jump in, swap shots, rework sequences, change the mood, and fine-tune the story. It felt less like using a tool and more like working with an AI production crew. We're moving beyond prompting. The next wave is directing autonomous creative workflows that understand the music, build the narrative, and still leave the final call to you. Character: ChatGPT Image Video: Seedance This is the most fun I've had making a music video in a long time.
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I just dropped myself into a Taylor Swift-style music video without writing a single prompt, timeline, or storyboard. I uploaded one photo and the song. That's it. Atlabs AI took over from there: • Built the character sheet • Planned the scenes • Generated the prompts • Synced every cut to the beat • Delivered a finished edit Most AI video tools promise automation, but the tradeoff is usually creative control. This was the opposite. The agents handled the production work while I focused on direction. Every scene, transition, framing choice, and creative decision stayed in my hands. When the edit was ready, I could jump in, swap shots, rework sequences, change the mood, and fine-tune the story. It felt less like using a tool and more like working with an AI production crew. We're moving beyond prompting. The next wave is directing autonomous creative workflows that understand the music, build the narrative, and still leave the final call to you. Character: ChatGPT Image Video: Seedance This is the most fun I've had making a music video in a long time.

Sharon Riley

36,280 views • 1 month ago

This AI UGC workflow is f*cking nuts 🤯 One prompt -> five completely different characters + five full ad variations, all generated automatically in a single run. Perfect for DTC brands and creative agencies who need volume but don't have time to build each variation from scratch. Most people making AI UGC are doing it one video at a time. New character, new prompt, new script, new render. Repeat. It works, but it doesn't scale. By the time you've built 5 variations to test, you've burned half a day. This workflow solves it: → Enter one initial prompt with your product and angle → Auto-generates 5 unique AI characters → Builds hook scripts for each variation → Writes the bridge with your actual product image → Creates the CTA — all 5 versions in one shot No building each video manually. No copy-pasting prompts over and over. No bottleneck between idea and creative testing. What you get: > 5 unique character variations from a single prompt > Hook, bridge, and CTA scripts tailored to each character > Product image integration baked in > A repeatable system you can run every time you need fresh creative Built 100% with AI. Want a copy of the full workflow for free? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)
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This AI UGC workflow is f*cking nuts 🤯 One prompt -> five completely different characters + five full ad variations, all generated automatically in a single run. Perfect for DTC brands and creative agencies who need volume but don't have time to build each variation from scratch. Most people making AI UGC are doing it one video at a time. New character, new prompt, new script, new render. Repeat. It works, but it doesn't scale. By the time you've built 5 variations to test, you've burned half a day. This workflow solves it: → Enter one initial prompt with your product and angle → Auto-generates 5 unique AI characters → Builds hook scripts for each variation → Writes the bridge with your actual product image → Creates the CTA — all 5 versions in one shot No building each video manually. No copy-pasting prompts over and over. No bottleneck between idea and creative testing. What you get: > 5 unique character variations from a single prompt > Hook, bridge, and CTA scripts tailored to each character > Product image integration baked in > A repeatable system you can run every time you need fresh creative Built 100% with AI. Want a copy of the full workflow for free? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)

Mike Futia

15,225 views • 5 months ago

Seedance 2.0 + Claude Code is f*cking insane 🤯 I built a Claude skill that creates UGC ads on demand. One product + one prompt = the AI creator, the script, the scene-by-scene shot list, and the finished video. All inside Claude Code. Perfect for DTC brands and agencies who can't afford to keep paying $500-$1,500 per UGC video and waiting 2 weeks for revisions. This skill eliminates the entire loop: → Tell Claude the product, ad angle, and length → Skill writes the GPT Image 2.0 prompt to generate the AI creator from scratch → Skill writes every scene prompt, dialogue line, and delivery direction → Pipes it into Seedance 2.0 with character + product + voice locked → Speed up + caption in CapCut → Ship the ad in 20 minutes No more paying $11 per video on Arcads. No more 2-week revision cycles. No more PR boxes to creators who ghost you. What you get: → Perfect character consistency across every scene → Voice consistency that holds clip-to-clip → Real product fidelity using your actual product photo as a reference → Multi-scene day-in-life, testimonial, and action-shot formats out of the box Built 100% with a Claude skill + Seedance 2.0. I recorded a full step-by-step tutorial showing the exact workflow so you can build these AI UGC ads yourself. Want the full breakdown? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)
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Seedance 2.0 + Claude Code is f*cking insane 🤯 I built a Claude skill that creates UGC ads on demand. One product + one prompt = the AI creator, the script, the scene-by-scene shot list, and the finished video. All inside Claude Code. Perfect for DTC brands and agencies who can't afford to keep paying $500-$1,500 per UGC video and waiting 2 weeks for revisions. This skill eliminates the entire loop: → Tell Claude the product, ad angle, and length → Skill writes the GPT Image 2.0 prompt to generate the AI creator from scratch → Skill writes every scene prompt, dialogue line, and delivery direction → Pipes it into Seedance 2.0 with character + product + voice locked → Speed up + caption in CapCut → Ship the ad in 20 minutes No more paying $11 per video on Arcads. No more 2-week revision cycles. No more PR boxes to creators who ghost you. What you get: → Perfect character consistency across every scene → Voice consistency that holds clip-to-clip → Real product fidelity using your actual product photo as a reference → Multi-scene day-in-life, testimonial, and action-shot formats out of the box Built 100% with a Claude skill + Seedance 2.0. I recorded a full step-by-step tutorial showing the exact workflow so you can build these AI UGC ads yourself. Want the full breakdown? > Like this post > Comment "UGC" And I'll send it over (must be following so I can DM)

Mike Futia

39,006 views • 2 months ago

Gemini Omni's motion control is f*cking cracked i just figured out how to turn 1 reference video into 50+ AI videos with the exact same movements... you have a video of someone eating, dancing, using a product, doing whatever complex motion you need. you feed it to Gemini Omni and it recreates that exact motion with a completely new AI character in literally one prompt i've tested this against Kling motion control and it's not even close. Kling falls apart the moment you try anything complex. eating scenes look weird, hand movements get mangled, anything multi-step breaks down completely. Gemini Omni handles all of it if you're still using kling motion control or paying creators to split test your videos, this replaces that entire workflow here's the thing though. you can't just prompt this out of the box. if you try to do motion transfer with default prompting you're going to get errors or the motion won't transfer properly. there's a specific prompting method that makes it work every time so i packaged up the whole system.. here's what you're getting: > full step by step video breakdown > how to find the best reference videos to use > the exact prompting system that allows for motion control transfer so you never get errors > the workflow for batching this out at scale (1 video → 50+) RT + reply "MOTION" and i'll send it over (must follow so i can dm)
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Gemini Omni's motion control is f*cking cracked i just figured out how to turn 1 reference video into 50+ AI videos with the exact same movements... you have a video of someone eating, dancing, using a product, doing whatever complex motion you need. you feed it to Gemini Omni and it recreates that exact motion with a completely new AI character in literally one prompt i've tested this against Kling motion control and it's not even close. Kling falls apart the moment you try anything complex. eating scenes look weird, hand movements get mangled, anything multi-step breaks down completely. Gemini Omni handles all of it if you're still using kling motion control or paying creators to split test your videos, this replaces that entire workflow here's the thing though. you can't just prompt this out of the box. if you try to do motion transfer with default prompting you're going to get errors or the motion won't transfer properly. there's a specific prompting method that makes it work every time so i packaged up the whole system.. here's what you're getting: > full step by step video breakdown > how to find the best reference videos to use > the exact prompting system that allows for motion control transfer so you never get errors > the workflow for batching this out at scale (1 video → 50+) RT + reply "MOTION" and i'll send it over (must follow so i can dm)

Miko

57,481 views • 15 days ago

Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!
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Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it matters: Most vision models treat documents as massive sequences of tokens, making long-context processing expensive and slow. DeepSeek-OCR uses context optical compression to convert 2D layouts into vision tokens, enabling efficient processing of complex documents. The best part? You can easily fine-tune it for your specific use case on a single GPU. I used Unsloth to run this experiment on Persian text and saw an 88.26% improvement in character error rate. ↳ Base model: 149% character error rate (CER) ↳ Fine-tuned model: 60% CER (57% more accurate) ↳ Training time: 60 steps on a single GPU Persian was just the test case. You can swap in your own dataset for any language, document type, or specific domain you're working with. I've shared the complete guide in the next tweet - all the code, notebooks, and environment setup ready to run with a single click. Everything is 100% open-source!

Akshay 🚀

126,122 views • 8 months ago

POV: You came to vlog the matcc, and captured Arsenal’s goal live on camera. Would you survive this atmosphere? Comment your favorite football club below! Made with GPT Image 2 + Seedance on LovartAI Prompt: Create a 15-second ultra-realistic cinematic influencer vlog video. Use the same consistent character throughout all shots. Authentic iPhone 14 Pro TikTok vlog realism, handheld camera imperfections, front-camera selfies mixed with back-camera stadium footage, natural motion blur, autofocus breathing, slight rolling-shutter wobble, realistic HDR, and loud crowd audio distortion. 24 fps, 26 mm lens equivalent. Scene 1 (0–3s) — Stadium Intro Front-facing selfie outside Emirates Stadiumbefore kickoff. Fans stream behind her. She says: “Guys, I’m at Arsenal vs Burnley and the atmosphere is absolutely insane!” Scene 2 (3–6s) — In the Stands Selfie from her seat with the pitch glowing behind her. She says: “We’ve got such a good view. Arsenal look really sharp already!” Scene 3 (6–9s) — Match Action Back camera shows Arsenal F.C.attacking Burnley F.C.. She shouts: “Come on Arsenal… shoot! SHOOT!” Scene 4 (9–12s) — Goal Moment Back camera captures Arsenal scoring. She screams: “GOAL! Oh my God, I got it!” Scene 5 (12–15s) — Celebration Selfie Front-facing selfie as she jumps and laughs with celebrating fans behind her. She says: “I actually caught the goal on camera! Best moment ever! Come on Arsenal!” Final Tone: Raw, emotional, high-energy football vlog with authentic stadium atmosphere and a euphoric goal reaction. #Lovart, #LovartPartner
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POV: You came to vlog the matcc, and captured Arsenal’s goal live on camera. Would you survive this atmosphere? Comment your favorite football club below! Made with GPT Image 2 + Seedance on LovartAI Prompt: Create a 15-second ultra-realistic cinematic influencer vlog video. Use the same consistent character throughout all shots. Authentic iPhone 14 Pro TikTok vlog realism, handheld camera imperfections, front-camera selfies mixed with back-camera stadium footage, natural motion blur, autofocus breathing, slight rolling-shutter wobble, realistic HDR, and loud crowd audio distortion. 24 fps, 26 mm lens equivalent. Scene 1 (0–3s) — Stadium Intro Front-facing selfie outside Emirates Stadiumbefore kickoff. Fans stream behind her. She says: “Guys, I’m at Arsenal vs Burnley and the atmosphere is absolutely insane!” Scene 2 (3–6s) — In the Stands Selfie from her seat with the pitch glowing behind her. She says: “We’ve got such a good view. Arsenal look really sharp already!” Scene 3 (6–9s) — Match Action Back camera shows Arsenal F.C.attacking Burnley F.C.. She shouts: “Come on Arsenal… shoot! SHOOT!” Scene 4 (9–12s) — Goal Moment Back camera captures Arsenal scoring. She screams: “GOAL! Oh my God, I got it!” Scene 5 (12–15s) — Celebration Selfie Front-facing selfie as she jumps and laughs with celebrating fans behind her. She says: “I actually caught the goal on camera! Best moment ever! Come on Arsenal!” Final Tone: Raw, emotional, high-energy football vlog with authentic stadium atmosphere and a euphoric goal reaction. #Lovart, #LovartPartner

Shami

29,564 views • 2 months ago

This week is already so hot. 🔥 Massive release from Decart : Lucy 2.0 a World Editing Model running at 1080p, 30FPS in realtime. This is truly exciting, the era of real-time generative reality is here. We are moving from watching AI video to living inside AI video. A breakthrough model capable of transforming the visual world in real-time. Moving beyond offline rendering, Lucy 2.0 delivers high-fidelity 1080p video generation with near-zero latency. Lucy 2.0 literally "redraws" the entire world pixel-by-pixel, while you are watching it. e.g. If you want to be an anime character, it doesn't just put a mask on you. It turns your skin into anime skin, your hair into anime hair, and the lighting in your room into anime lighting. Lucy 2.0 is also trained to stop the generated video from slowly falling apart over time, so the same stream can run much longer without faces and details drifting. So why is this a "Massive Deal"? Traditional AI video-generation model takes a prompt, you wait 10–20 minutes, and the computer "bakes" a video for you. You couldn't touch it or change it while it was happening. But Lucy 2.0 works like a mirror. It happens in real-time (30 frames per second). There is no waiting. You move your hand, the AI character moves its hand instantly. The craziest part isn't the visuals; it's the physics. Usually, AI hallucinations are glitchy—hands merge into faces, walls melt. Lucy 2.0 understands how the world works without being told. It knows that if you take off a helmet, there is hair underneath. It knows that if you splash water, droplets fly. It learned "physics" just by watching millions of videos. The physical behavior you see emerges from learned visual dynamics, not from engineered geometry or explicit physics engines. Their official technical report explicitly states that the model does not use traditional 3D engines, depth maps, or wireframes. It is a "pure diffusion model."
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This week is already so hot. 🔥 Massive release from Decart : Lucy 2.0 a World Editing Model running at 1080p, 30FPS in realtime. This is truly exciting, the era of real-time generative reality is here. We are moving from watching AI video to living inside AI video. A breakthrough model capable of transforming the visual world in real-time. Moving beyond offline rendering, Lucy 2.0 delivers high-fidelity 1080p video generation with near-zero latency. Lucy 2.0 literally "redraws" the entire world pixel-by-pixel, while you are watching it. e.g. If you want to be an anime character, it doesn't just put a mask on you. It turns your skin into anime skin, your hair into anime hair, and the lighting in your room into anime lighting. Lucy 2.0 is also trained to stop the generated video from slowly falling apart over time, so the same stream can run much longer without faces and details drifting. So why is this a "Massive Deal"? Traditional AI video-generation model takes a prompt, you wait 10–20 minutes, and the computer "bakes" a video for you. You couldn't touch it or change it while it was happening. But Lucy 2.0 works like a mirror. It happens in real-time (30 frames per second). There is no waiting. You move your hand, the AI character moves its hand instantly. The craziest part isn't the visuals; it's the physics. Usually, AI hallucinations are glitchy—hands merge into faces, walls melt. Lucy 2.0 understands how the world works without being told. It knows that if you take off a helmet, there is hair underneath. It knows that if you splash water, droplets fly. It learned "physics" just by watching millions of videos. The physical behavior you see emerges from learned visual dynamics, not from engineered geometry or explicit physics engines. Their official technical report explicitly states that the model does not use traditional 3D engines, depth maps, or wireframes. It is a "pure diffusion model."

Rohan Paul

12,761 views • 6 months ago

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.
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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 views • 26 days ago

GPT-Image-2 + Seedance 2.0目前已成AI视频标配 甚至可以根据给定图片推导过去和未来，制作storyboard，然后生成视频 使用方法： 1️⃣ 随便找一张图 2️⃣ 给以下提示词，然后制作storyboard 用以下提示词👇： Create a 3×3 cinematic storyboard grid based on the uploaded reference image. Use the uploaded image as the central moment of the story: Frame 5 must represent the exact “t” moment, matching the subject, scene, mood, composition, costume, environment, lighting style, and emotional tone of the reference image. The storyboard must show what happened before and after this moment as a time-based visual timeline. FRAME STRUCTURE: Frame 1: t-30: Establishing shot, the wider environment before the main event begins. Frame 2: t-10: The subject approaches or prepares for the key moment. Frame 3: t-5: Tension builds, body language and atmosphere lead toward the reference image. Frame 4: t-1: Final instant before the reference image, close emotional or action transition. Frame 5: t: Recreate the uploaded reference image as the central key frame. Frame 6: t+1: Immediate reaction or continuation right after the key moment. Frame 7: t+5: Alternate angle showing the consequence of the moment. Frame 8: t+15: Candid transition frame, natural movement, emotional aftermath. Frame 9: t+30: Strong final cinematic frame that clearly resolves the scene. STYLE: Ultra-realistic cinematic storyboard, 3×3 grid layout, cohesive visual tone across all frames, consistent character identity, consistent costume, consistent environment, cinematic lighting, shallow depth of field, realistic camera angles, natural motion continuity, no text labels, no numbers, no arrows, no captions inside the image. 3️⃣ seedance2.0 一键成片
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GPT-Image-2 + Seedance 2.0目前已成AI视频标配 甚至可以根据给定图片推导过去和未来，制作storyboard，然后生成视频 使用方法： 1️⃣ 随便找一张图 2️⃣ 给以下提示词，然后制作storyboard 用以下提示词👇： Create a 3×3 cinematic storyboard grid based on the uploaded reference image. Use the uploaded image as the central moment of the story: Frame 5 must represent the exact “t” moment, matching the subject, scene, mood, composition, costume, environment, lighting style, and emotional tone of the reference image. The storyboard must show what happened before and after this moment as a time-based visual timeline. FRAME STRUCTURE: Frame 1: t-30: Establishing shot, the wider environment before the main event begins. Frame 2: t-10: The subject approaches or prepares for the key moment. Frame 3: t-5: Tension builds, body language and atmosphere lead toward the reference image. Frame 4: t-1: Final instant before the reference image, close emotional or action transition. Frame 5: t: Recreate the uploaded reference image as the central key frame. Frame 6: t+1: Immediate reaction or continuation right after the key moment. Frame 7: t+5: Alternate angle showing the consequence of the moment. Frame 8: t+15: Candid transition frame, natural movement, emotional aftermath. Frame 9: t+30: Strong final cinematic frame that clearly resolves the scene. STYLE: Ultra-realistic cinematic storyboard, 3×3 grid layout, cohesive visual tone across all frames, consistent character identity, consistent costume, consistent environment, cinematic lighting, shallow depth of field, realistic camera angles, natural motion continuity, no text labels, no numbers, no arrows, no captions inside the image. 3️⃣ seedance2.0 一键成片

Jason Zhu

34,160 views • 2 months ago

Would you underestimate her just because she wears a school uniform? GPT Image 2 + Seedance 2.0 on Sjolt Try Canvas: prompt Character Identity Lock (Highest Priority): Use the exact same young East Asian woman from the provided reference character sheet. Preserve 100% identical facial features, face shape, eye shape, nose, lips, skin tone, hairstyle, hair color, proportions, and overall identity throughout the entire video. Do not redesign, reinterpret, or substitute the character. She must remain instantly recognizable as the same person from the reference image. She has shoulder-length wavy silver-gray hair with subtle blue undertones, bright expressive eyes, fair skin, and a confident slight smile that naturally transitions into a focused, determined combat expression. She wears the identical navy blue Korean high school uniform blazer over a gray sweater vest, white collared shirt, striped tie, and matching school skirt from the reference character sheet. Video Prompt: A cinematic, hyper-realistic action sequence inside a chaotic South Korean high school classroom. The classroom is filled with overturned desks, scattered chairs, flying notebooks, broken pencils, and papers drifting through the air. Bright natural daylight streams through large classroom windows, creating realistic highlights, soft shadows, and cinematic contrast. The young female student moves with incredible speed, confidence, and precision as she expertly defends herself against multiple aggressive male students wearing matching Korean school uniforms. Every movement is fluid, athletic, and grounded in realistic martial arts choreography. The camera remains highly dynamic, featuring cinematic handheld tracking shots, fast push-ins, orbit shots, dramatic slow-motion moments, whip pans, low-angle hero shots, and close-up impact shots. Capture rapid combinations of punches, clean high kicks, evasive footwork, parries, elbow strikes, blocks, and throws. Desks slide across the floor, chairs topple over, and dust particles catch the sunlight, emphasizing the intensity of the action. Maintain a high shutter-speed action-photography aesthetic with crisp motion detail, subtle motion blur only during extremely fast movements, physically accurate body mechanics, realistic cloth simulation, natural hair physics, authentic facial expressions, and believable impact reactions. Keep the camera frequently returning to sharp close-ups of her face to reinforce character continuity and emotional intensity. Her silver-gray hair flows naturally with every movement while her determined eyes remain locked on her opponents. Photorealistic cinematic quality, 4K HDR, ultra-detailed skin textures, realistic lighting, volumetric daylight, physically based rendering, shallow depth of field during close-ups, blockbuster Korean action film aesthetic, empowering heroine energy, consistent facial identity throughout every frame, no face drift, no character variation, no animation-style exaggeration.
0:13

Would you underestimate her just because she wears a school uniform? GPT Image 2 + Seedance 2.0 on Sjolt Try Canvas: prompt Character Identity Lock (Highest Priority): Use the exact same young East Asian woman from the provided reference character sheet. Preserve 100% identical facial features, face shape, eye shape, nose, lips, skin tone, hairstyle, hair color, proportions, and overall identity throughout the entire video. Do not redesign, reinterpret, or substitute the character. She must remain instantly recognizable as the same person from the reference image. She has shoulder-length wavy silver-gray hair with subtle blue undertones, bright expressive eyes, fair skin, and a confident slight smile that naturally transitions into a focused, determined combat expression. She wears the identical navy blue Korean high school uniform blazer over a gray sweater vest, white collared shirt, striped tie, and matching school skirt from the reference character sheet. Video Prompt: A cinematic, hyper-realistic action sequence inside a chaotic South Korean high school classroom. The classroom is filled with overturned desks, scattered chairs, flying notebooks, broken pencils, and papers drifting through the air. Bright natural daylight streams through large classroom windows, creating realistic highlights, soft shadows, and cinematic contrast. The young female student moves with incredible speed, confidence, and precision as she expertly defends herself against multiple aggressive male students wearing matching Korean school uniforms. Every movement is fluid, athletic, and grounded in realistic martial arts choreography. The camera remains highly dynamic, featuring cinematic handheld tracking shots, fast push-ins, orbit shots, dramatic slow-motion moments, whip pans, low-angle hero shots, and close-up impact shots. Capture rapid combinations of punches, clean high kicks, evasive footwork, parries, elbow strikes, blocks, and throws. Desks slide across the floor, chairs topple over, and dust particles catch the sunlight, emphasizing the intensity of the action. Maintain a high shutter-speed action-photography aesthetic with crisp motion detail, subtle motion blur only during extremely fast movements, physically accurate body mechanics, realistic cloth simulation, natural hair physics, authentic facial expressions, and believable impact reactions. Keep the camera frequently returning to sharp close-ups of her face to reinforce character continuity and emotional intensity. Her silver-gray hair flows naturally with every movement while her determined eyes remain locked on her opponents. Photorealistic cinematic quality, 4K HDR, ultra-detailed skin textures, realistic lighting, volumetric daylight, physically based rendering, shallow depth of field during close-ups, blockbuster Korean action film aesthetic, empowering heroine energy, consistent facial identity throughout every frame, no face drift, no character variation, no animation-style exaggeration.

Sharon Riley

26,184 views • 9 days ago

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.
0:10

The architecture of this new world model is one of the most interesting things I've seen lately: Let me first explain how most world models work: They predict and render one frame at a time. If you are navigating in one of these worlds, and you look left, the model draws whatever looks right in the moment. Every time you change your viewpoint, the model has to imagine what should be there again, so it's very common for these models to "forget" what's in the world. For example, if you put a toy on the table, look away, then look back, the toy might not be there anymore. Tripo AI is releasing its Project Eden model, which works very differently: The model builds the world first, and then renders it based on that map. That map holds the real state of the world: the geometry, every object, where things are, what's already happened. The picture you see on screen gets generated from the map. This architecture flips the whole thing. Now, you get the following: 1. The world stops forgetting. Leave, come back, and the toy is still on the table because it lives in the map, not in the last frame you saw. 2. You can edit the world, and those changes persist for anyone who enters later. 3. Multiple people and AI agents can coexist in the world and see it from different perspectives. This is early research, but it's looking really promising. They just raised nearly $200M across two rounds to build it out. Tripo will be at SIGGRAPH 2026 (July 19–23, Los Angeles Convention Center). If you work in 3D, embodied AI, simulation, or anything spatial, go connect with them there.

Santiago

30,189 views • 1 month ago

Contact sheet prompting is the hottest AI video technique right now 🤯 If you've seen this technique blowing up, here's why it works: You feed AI one image, and it generates a grid of consistent shots—same face, same outfit, different angles and poses. Instant storyboarding. Full creative control. No reshoots. But doing it manually is brutal: → Write the prompt from scratch → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one at a time → Repeat for every single product That's hours of work per campaign. This n8n automation handles everything: → Upload a character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 creates smooth transitions between frames → 5 video clips land in Airtable ready to use No manual cropping. No frame-by-frame prompting. No tedious busywork. What you get in Airtable: - AI-generated creative prompt - Hero image (model + product) - Full 6-frame contact sheet - 5 cinematic video clips - Approval gates before each step All inside n8n + Airtable. Contact sheet prompting on complete autopilot. I recorded a 20-minute Loom showing exactly how I built this. Want the walkthrough + the full n8n workflow + Airtable base? > Like this post > Comment "CONTACT" And I'll send it over (must be following so I can DM)
0:13

Contact sheet prompting is the hottest AI video technique right now 🤯 If you've seen this technique blowing up, here's why it works: You feed AI one image, and it generates a grid of consistent shots—same face, same outfit, different angles and poses. Instant storyboarding. Full creative control. No reshoots. But doing it manually is brutal: → Write the prompt from scratch → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one at a time → Repeat for every single product That's hours of work per campaign. This n8n automation handles everything: → Upload a character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 creates smooth transitions between frames → 5 video clips land in Airtable ready to use No manual cropping. No frame-by-frame prompting. No tedious busywork. What you get in Airtable: - AI-generated creative prompt - Hero image (model + product) - Full 6-frame contact sheet - 5 cinematic video clips - Approval gates before each step All inside n8n + Airtable. Contact sheet prompting on complete autopilot. I recorded a 20-minute Loom showing exactly how I built this. Want the walkthrough + the full n8n workflow + Airtable base? > Like this post > Comment "CONTACT" And I'll send it over (must be following so I can DM)

Mike Futia

24,559 views • 6 months ago

THE CLIMAX EVERYONE REMEMBERS IS BUILT FROM THE SECOND WHERE NOTHING HAPPENS A ronin. An army. One continuous shot. The frame most people miss is the one that makes everything land: a beat of pure black right before the explosion. Here’s what that sequence actually teaches: 1. Contrast is something you spend, not a setting you turn on. Stay bright the whole time and you’ve got nowhere left to go when it counts. Hold the darkness long enough and a single bright frame feels blinding. 2. One accent color in a monochrome world hits harder than a full palette. Charcoal, ash, pewter… and exactly one slash of violet neon. Your eye goes straight to it every time. Add a second accent and you halve the power of both. 3. The blackout isn’t just a transition — it’s the turning point. Everything before it is descent. Everything after is release. The structure is disguised as lighting. 4. Flat, faceless enemies aren’t lazy. They’re deliberate hierarchy. Identical grey soldiers and helmets make the ronin pop. Give them personality and you split the audience’s attention for nothing. 5. One continuous shot forces every decision to matter. No cuts to hide behind. Framing, movement, and light have to carry the whole thing — and that’s exactly why it holds up. 6. Quiet frames buy the loud ones. There’s a moment with zero neon — just black and white, hair streaming across the frame like spilled ink. It gives you nothing… which is why the next frame hits so hard. 7. End by taking the light away. Katana lowered, tip toward the ground, no glow left on the steel. The brightest thing in the entire piece disappears. That’s what makes it feel like an ending instead of just a stop. Why this matters: Most people build climaxes by adding more — more light, more motion, more color. This one does it by subtracting first. A dead beat costs nothing and pays off everything that follows. Restraint reads as confidence. Overloading reads as insecurity. Audiences feel it before they can explain it. You don’t need a bigger budget or a better model. You just need the discipline to hold back. The real lesson isn’t “make it dark.” It’s that impact is relative. You can’t have a true peak without spending time in the valley first — and most creators rush straight to the peak, then wonder why nothing lands. This version keeps all your original insights, tightens the flow, and sounds like a thoughtful filmmaker or editor sharing something they noticed — not like generated content. Ready to post.
0:17

THE CLIMAX EVERYONE REMEMBERS IS BUILT FROM THE SECOND WHERE NOTHING HAPPENS A ronin. An army. One continuous shot. The frame most people miss is the one that makes everything land: a beat of pure black right before the explosion. Here’s what that sequence actually teaches: 1. Contrast is something you spend, not a setting you turn on. Stay bright the whole time and you’ve got nowhere left to go when it counts. Hold the darkness long enough and a single bright frame feels blinding. 2. One accent color in a monochrome world hits harder than a full palette. Charcoal, ash, pewter… and exactly one slash of violet neon. Your eye goes straight to it every time. Add a second accent and you halve the power of both. 3. The blackout isn’t just a transition — it’s the turning point. Everything before it is descent. Everything after is release. The structure is disguised as lighting. 4. Flat, faceless enemies aren’t lazy. They’re deliberate hierarchy. Identical grey soldiers and helmets make the ronin pop. Give them personality and you split the audience’s attention for nothing. 5. One continuous shot forces every decision to matter. No cuts to hide behind. Framing, movement, and light have to carry the whole thing — and that’s exactly why it holds up. 6. Quiet frames buy the loud ones. There’s a moment with zero neon — just black and white, hair streaming across the frame like spilled ink. It gives you nothing… which is why the next frame hits so hard. 7. End by taking the light away. Katana lowered, tip toward the ground, no glow left on the steel. The brightest thing in the entire piece disappears. That’s what makes it feel like an ending instead of just a stop. Why this matters: Most people build climaxes by adding more — more light, more motion, more color. This one does it by subtracting first. A dead beat costs nothing and pays off everything that follows. Restraint reads as confidence. Overloading reads as insecurity. Audiences feel it before they can explain it. You don’t need a bigger budget or a better model. You just need the discipline to hold back. The real lesson isn’t “make it dark.” It’s that impact is relative. You can’t have a true peak without spending time in the valley first — and most creators rush straight to the peak, then wonder why nothing lands. This version keeps all your original insights, tightens the flow, and sounds like a thoughtful filmmaker or editor sharing something they noticed — not like generated content. Ready to post.

Nexlow

12,037 views • 10 days ago

Sora 2 + n8n is absolutely insane 🤯 This n8n automation generates entire UGC campaigns with the same AI creator across unlimited videos. All from one Airtable form. Perfect for DTC brands & agencies who need brand consistency in their AI ads without hiring real creators. Why this matters: Every AI video tool gives you a random person each time. You can't build multi-video campaigns because your "creator" changes in every clip. Sora 2 consistent characters solves this: Same AI creator → Different scenes → Unlimited videos The n8n workflow: → Fill out Airtable form once (select your character, describe scenes, choose quantity) → Claude AI generates professional Sora 2 prompts automatically → Sora 2 renders videos with your consistent character → Videos auto-upload to ImageKit CDN → Everything tracked in Airtable with shareable URLs No manual prompting. No file management. No different people in every video. What you can create: → 3-part testimonial series with the same person → Before/during/after transformation campaigns → Product tutorial sequences that feel cohesive → Entire ad creative libraries with your "brand ambassador" Track everything in Airtable: → Video status (queued → generating → complete) → Shareable URLs for each clip → Scene descriptions and prompts → Production-ready in 5-10 minutes Built 100% in n8n + Airtable. Want the complete template? > Comment "SORA" > Like this post And I'll send it over (must be following so I can DM)
0:19

Sora 2 + n8n is absolutely insane 🤯 This n8n automation generates entire UGC campaigns with the same AI creator across unlimited videos. All from one Airtable form. Perfect for DTC brands & agencies who need brand consistency in their AI ads without hiring real creators. Why this matters: Every AI video tool gives you a random person each time. You can't build multi-video campaigns because your "creator" changes in every clip. Sora 2 consistent characters solves this: Same AI creator → Different scenes → Unlimited videos The n8n workflow: → Fill out Airtable form once (select your character, describe scenes, choose quantity) → Claude AI generates professional Sora 2 prompts automatically → Sora 2 renders videos with your consistent character → Videos auto-upload to ImageKit CDN → Everything tracked in Airtable with shareable URLs No manual prompting. No file management. No different people in every video. What you can create: → 3-part testimonial series with the same person → Before/during/after transformation campaigns → Product tutorial sequences that feel cohesive → Entire ad creative libraries with your "brand ambassador" Track everything in Airtable: → Video status (queued → generating → complete) → Shareable URLs for each clip → Scene descriptions and prompts → Production-ready in 5-10 minutes Built 100% in n8n + Airtable. Want the complete template? > Comment "SORA" > Like this post And I'll send it over (must be following so I can DM)

Mike Futia

18,978 views • 8 months ago

Made with Seedance 2.0 by Yapper Prompt: MASTER CINEMATIC PROMPT — ROOFTOP CHASE (INTENSE VERSION) SUBJECT: image1 Use the first image as the main subject. Maintain consistent face, body shape, hairstyle, clothing, and proportions throughout the entire video. Use the image2 as the primary storyboard reference. The second image strictly defines scene order, framing, and timing. Prioritize matching the second image over any creative interpretation. ⸻ FACE LOCK The face must remain sharp at all times. No blur, no distortion, no flickering. Expression progression: focused → tense → survival instinct → aggressive. ⸻ OUTFIT LOCK (STRICT) White undershirt (lightweight, slightly sweat-soaked, visible fabric texture, natural wrinkles) Red shorts (knee-length, soft fabric, natural folds, slightly loose fit) Barefoot (no footwear, visible natural foot movement and contact with surfaces) Rules: * Outfit must remain identical in all frames * No color change, no design change, no wardrobe switching * Clothing must stay consistent even when wet * Fabric reacts naturally to wind, movement, and water * Feet must remain barefoot at all times (no shoes appearing) ⸻ ENVIRONMENT Jakarta dense urban rooftop (corrugated metal roofs, rough concrete, tightly packed buildings) Golden hour lighting with strong backlight Hazy atmosphere with airborne dust particles Environment feels hot, dense, and visually chaotic ⸻ STYLE CORE Live-action, ultra-realistic, AAA cinematic quality High contrast, gritty, intense tone Natural motion blur (strong during fast movement) Heavy debris interaction and environmental destruction emphasis ⸻ CAMERA SYSTEM Handheld tracking, very close to the subject Micro-shake increases slightly on impact (controlled, not chaotic) Dynamic continuous movement following subject momentum Rule: Camera must feel physically present in the action No teleporting, no glitching Subject remains dominant in frame ⸻ TIMELINE (STRICT — HARD ACTION) 0.0 – 1.2s Wide rooftop view of Jakarta. Subject sprinting. A loud CRACK — bullet hits metal very close. Large sparks burst, slight camera shock reaction. ⸻ 1.2 – 2.5s Tight rear tracking shot. Heavy barefoot footsteps on metal roof (visible contact and impact). Bullet nearly hits the foot — debris flies toward camera. Clothesline hits his face; he forcefully pushes through without slowing. ⸻ 2.5 – 4.0s Fast slide under water tank. Bullet pierces the tank — heavy water burst crashes down. Clothing becomes wetter, sticks slightly to body. Camera partially passes through the water splash. He rolls hard and drops to a lower rooftop with impact weight. ⸻ 4.0 – 5.5s Running along a narrow ledge. Two rapid shots — concrete explodes beside his shoulder. Debris flies past camera. He nearly loses balance but recovers instantly. ⸻ 5.5 – 7.0s Full sprint into a large building gap jump. Slow motion mid-air. Bullet hits the edge behind him — fragments scatter in the air. Landing is unstable but controlled (barefoot impact visible). ⸻ 7.0 – 8.5s Grabs fire escape railing aggressively. Bullet slams into metal right beside his face — intense sparks. Camera swings with the momentum. He pulls himself up with force. ⸻ 8.5 – 9.5s Fast aggressive climb using windows and AC units. Bullet shatters glass right beside his head. Glass shards fall downward. Movement is fast, urgent, controlled panic. ⸻ 9.5 – 10.0s Reaches rooftop. Bullet hits near his feet. He pauses briefly, spots a hidden sniper suitcase under a water tank. Immediately sprints toward it. ⸻ PHYSICS & EFFECTS Bullet impacts create strong sparks, debris bursts, and visible force Water hits with weight and affects clothing behavior Barefoot contact interacts realistically with surfaces Camera reacts subtly to shock impacts Environment responds dynamically ⸻ CONSTRAINT No cuts No gore No additional scenes No timeline changes No mirrored movement No face distortion
0:10

Made with Seedance 2.0 by Yapper Prompt: MASTER CINEMATIC PROMPT — ROOFTOP CHASE (INTENSE VERSION) SUBJECT: image1 Use the first image as the main subject. Maintain consistent face, body shape, hairstyle, clothing, and proportions throughout the entire video. Use the image2 as the primary storyboard reference. The second image strictly defines scene order, framing, and timing. Prioritize matching the second image over any creative interpretation. ⸻ FACE LOCK The face must remain sharp at all times. No blur, no distortion, no flickering. Expression progression: focused → tense → survival instinct → aggressive. ⸻ OUTFIT LOCK (STRICT) White undershirt (lightweight, slightly sweat-soaked, visible fabric texture, natural wrinkles) Red shorts (knee-length, soft fabric, natural folds, slightly loose fit) Barefoot (no footwear, visible natural foot movement and contact with surfaces) Rules: * Outfit must remain identical in all frames * No color change, no design change, no wardrobe switching * Clothing must stay consistent even when wet * Fabric reacts naturally to wind, movement, and water * Feet must remain barefoot at all times (no shoes appearing) ⸻ ENVIRONMENT Jakarta dense urban rooftop (corrugated metal roofs, rough concrete, tightly packed buildings) Golden hour lighting with strong backlight Hazy atmosphere with airborne dust particles Environment feels hot, dense, and visually chaotic ⸻ STYLE CORE Live-action, ultra-realistic, AAA cinematic quality High contrast, gritty, intense tone Natural motion blur (strong during fast movement) Heavy debris interaction and environmental destruction emphasis ⸻ CAMERA SYSTEM Handheld tracking, very close to the subject Micro-shake increases slightly on impact (controlled, not chaotic) Dynamic continuous movement following subject momentum Rule: Camera must feel physically present in the action No teleporting, no glitching Subject remains dominant in frame ⸻ TIMELINE (STRICT — HARD ACTION) 0.0 – 1.2s Wide rooftop view of Jakarta. Subject sprinting. A loud CRACK — bullet hits metal very close. Large sparks burst, slight camera shock reaction. ⸻ 1.2 – 2.5s Tight rear tracking shot. Heavy barefoot footsteps on metal roof (visible contact and impact). Bullet nearly hits the foot — debris flies toward camera. Clothesline hits his face; he forcefully pushes through without slowing. ⸻ 2.5 – 4.0s Fast slide under water tank. Bullet pierces the tank — heavy water burst crashes down. Clothing becomes wetter, sticks slightly to body. Camera partially passes through the water splash. He rolls hard and drops to a lower rooftop with impact weight. ⸻ 4.0 – 5.5s Running along a narrow ledge. Two rapid shots — concrete explodes beside his shoulder. Debris flies past camera. He nearly loses balance but recovers instantly. ⸻ 5.5 – 7.0s Full sprint into a large building gap jump. Slow motion mid-air. Bullet hits the edge behind him — fragments scatter in the air. Landing is unstable but controlled (barefoot impact visible). ⸻ 7.0 – 8.5s Grabs fire escape railing aggressively. Bullet slams into metal right beside his face — intense sparks. Camera swings with the momentum. He pulls himself up with force. ⸻ 8.5 – 9.5s Fast aggressive climb using windows and AC units. Bullet shatters glass right beside his head. Glass shards fall downward. Movement is fast, urgent, controlled panic. ⸻ 9.5 – 10.0s Reaches rooftop. Bullet hits near his feet. He pauses briefly, spots a hidden sniper suitcase under a water tank. Immediately sprints toward it. ⸻ PHYSICS & EFFECTS Bullet impacts create strong sparks, debris bursts, and visible force Water hits with weight and affects clothing behavior Barefoot contact interacts realistically with surfaces Camera reacts subtly to shock impacts Environment responds dynamically ⸻ CONSTRAINT No cuts No gore No additional scenes No timeline changes No mirrored movement No face distortion

Zar⭕on

11,116 views • 2 months ago

Coffee thoughts - I’m not sure Candace is coming back. “I want to thank Baron for telling me it was time to do this”. “Thank you to everyone that’s been on this journey it’s been a heavy one.” “Today went a lot different than I thought it was going to be” Just for the record the court filing I posted last night was to get more time to respond and to go from 25 pages to 35 pages on why the court case with Harpole should be dismissed for “Failure to state a claim”. She’s trying to get it dismissed before it goes to discovery. Put the paperwork in AI it will give you the specifics. We all knew it was coming. The money it takes to fight these suits is insane. She’d be stupid to not try to get it dismissed. And Tennessee has more laws protecting public figures so it would be easier to get dismissed than in Delaware (that doesn’t) with the Macrons. I still think more happened yesterday. And the way she was acting just gives me this maybe it for a bit. Maybe I’m wrong but I knew yesterday something was up. Her video seemed more directed at making her last claims on everyone than continuing the attack. There was nothing there for an emergency video. She’s heavily pregnant, she’s run out of material, she’s being sued and the cases are coming up, she has 4 kids about to be 5 and you can only attack people so long with the same accusations. The trial is coming up that will disprove the conspiracies. Or maybe she just wanted one last show until she gets back. I still question if maybe another lawsuit dropped. We shall see. Off to vacation myself. Apparently we are going to Spain. (Joking).
0:09

Coffee thoughts - I’m not sure Candace is coming back. “I want to thank Baron for telling me it was time to do this”. “Thank you to everyone that’s been on this journey it’s been a heavy one.” “Today went a lot different than I thought it was going to be” Just for the record the court filing I posted last night was to get more time to respond and to go from 25 pages to 35 pages on why the court case with Harpole should be dismissed for “Failure to state a claim”. She’s trying to get it dismissed before it goes to discovery. Put the paperwork in AI it will give you the specifics. We all knew it was coming. The money it takes to fight these suits is insane. She’d be stupid to not try to get it dismissed. And Tennessee has more laws protecting public figures so it would be easier to get dismissed than in Delaware (that doesn’t) with the Macrons. I still think more happened yesterday. And the way she was acting just gives me this maybe it for a bit. Maybe I’m wrong but I knew yesterday something was up. Her video seemed more directed at making her last claims on everyone than continuing the attack. There was nothing there for an emergency video. She’s heavily pregnant, she’s run out of material, she’s being sued and the cases are coming up, she has 4 kids about to be 5 and you can only attack people so long with the same accusations. The trial is coming up that will disprove the conspiracies. Or maybe she just wanted one last show until she gets back. I still question if maybe another lawsuit dropped. We shall see. Off to vacation myself. Apparently we are going to Spain. (Joking).

Raven Grace 🇺🇸🇺🇸🇺🇸

23,705 views • 1 month ago

Made with kling 3.0 on Yapper How I made this video full tutorial in the comments Prompt Shot on ALEXA 65mm anamorphic lens. Photorealistic cinematic quality. Aspect ratio 2.39:1 widescreen. Teal shadows, warm amber highlights. Film grain. Rain-soaked New York street at night. Neon signs, streetlights reflecting on wet asphalt. Steam rising from manholes. Lens flares, motion blur. Dolby Vision HDR. 0.0s–2.5s: Extreme low-angle tracking shot — a lone female fighter strides down a narrow NYC street, rain pouring heavily. Leather jacket soaked, hair slicked back and dripping. Heels echo faintly on wet pavement. Camera tracks backward with subtle shake. Yellow taxi lights streak across puddles. Figures step out from alleyways and fire escapes, slowly surrounding her. She tilts her head, cracks her knuckles — calm, fearless expression. 2.6s–5.0s: Whip-pan — first attacker lunges. TIME REMAP: slow-motion as she pivots smoothly, dodging and delivering a sharp elbow strike. Water sprays on impact. Her jacket snaps with the motion. Another attacker crashes into a stack of trash bags and metal bins. Sparks flicker from a flickering streetlight overhead. 5.1s–7.5s: Drone shot — overhead view as she moves fluidly through multiple opponents. SLOW MOTION: precise kicks and spins land cleanly, bodies sliding across rain-slick asphalt. Steam swirls under golden streetlights. One attacker swings a bat — she catches it mid-swing, twists, and disarms them effortlessly. 7.6s–10.0s: 360° orbital shot — she leaps into a spinning kick, taking down two attackers at once. Camera circles her as another rushes from behind. Without turning, she blocks and counters instantly. Breath visible in the cold night air. Each strike hits in sync with a rising cinematic score. 10.1s–13.0s: First-person POV — the final opponent charges. SMASH CUT: rapid, close-range exchange in slow motion. Her final punch lands clean. Silence falls. Rain continues to pour. Slow push-in — she stands alone in the empty street, adjusts her jacket sleeve, exhales steadily. Low-angle shot. Eyes locked forward. Unshaken.
0:13

Made with kling 3.0 on Yapper How I made this video full tutorial in the comments Prompt Shot on ALEXA 65mm anamorphic lens. Photorealistic cinematic quality. Aspect ratio 2.39:1 widescreen. Teal shadows, warm amber highlights. Film grain. Rain-soaked New York street at night. Neon signs, streetlights reflecting on wet asphalt. Steam rising from manholes. Lens flares, motion blur. Dolby Vision HDR. 0.0s–2.5s: Extreme low-angle tracking shot — a lone female fighter strides down a narrow NYC street, rain pouring heavily. Leather jacket soaked, hair slicked back and dripping. Heels echo faintly on wet pavement. Camera tracks backward with subtle shake. Yellow taxi lights streak across puddles. Figures step out from alleyways and fire escapes, slowly surrounding her. She tilts her head, cracks her knuckles — calm, fearless expression. 2.6s–5.0s: Whip-pan — first attacker lunges. TIME REMAP: slow-motion as she pivots smoothly, dodging and delivering a sharp elbow strike. Water sprays on impact. Her jacket snaps with the motion. Another attacker crashes into a stack of trash bags and metal bins. Sparks flicker from a flickering streetlight overhead. 5.1s–7.5s: Drone shot — overhead view as she moves fluidly through multiple opponents. SLOW MOTION: precise kicks and spins land cleanly, bodies sliding across rain-slick asphalt. Steam swirls under golden streetlights. One attacker swings a bat — she catches it mid-swing, twists, and disarms them effortlessly. 7.6s–10.0s: 360° orbital shot — she leaps into a spinning kick, taking down two attackers at once. Camera circles her as another rushes from behind. Without turning, she blocks and counters instantly. Breath visible in the cold night air. Each strike hits in sync with a rising cinematic score. 10.1s–13.0s: First-person POV — the final opponent charges. SMASH CUT: rapid, close-range exchange in slow motion. Her final punch lands clean. Silence falls. Rain continues to pour. Slow push-in — she stands alone in the empty street, adjusts her jacket sleeve, exhales steadily. Low-angle shot. Eyes locked forward. Unshaken.

𝐍𝐚𝐯𝐞𝐞 𝐀𝐢

57,152 views • 3 months ago

Sorry if I did not answer many of you. I’ve never been a fan of the online eulogy. The immediate fallout is always about loved ones. And we should leave those closest be. And then I realised of course I was just incredibly upset, and a large digital outpouring is inevitable and testament to his character. My devastation came from having to watch it all unfold. From spending years trying to help and actually getting him close to a point where he almost had a normal life again - then being powerless to stop him doing things he should not have. Powerless in every sense as it also meant it sometimes not being my place to say anything. In the end watching some of the evil shits around enable the worst of it was too much for me, I had to step back it was too painful to watch. I told my mate who was filling in for me looking after him “ah I just need some space from it all, I’ll be back with him after Christmas” and then suddenly there was no Christmas. And it turned out no one was to blame, and I immediately looked to blame myself most of all, fearing the worst. But it was a simple accident in the end. A bolt out of the blue. So if you are ever estranged or overwhelmed by friends and family and think it will all be OK one day - DON’T put it off. Reach out now. Grab that person and hold them tight. There may not be a tomorrow. You might not be around to see them off. There may not be the grand luxury of time available you thought there was. He died in the arms of his beloved son, and that is a measure of comfort, if a passing can ever have any. He was my mentor, my friend and my glad burden. And there was nothing I would not do for him.
0:11

Sorry if I did not answer many of you. I’ve never been a fan of the online eulogy. The immediate fallout is always about loved ones. And we should leave those closest be. And then I realised of course I was just incredibly upset, and a large digital outpouring is inevitable and testament to his character. My devastation came from having to watch it all unfold. From spending years trying to help and actually getting him close to a point where he almost had a normal life again - then being powerless to stop him doing things he should not have. Powerless in every sense as it also meant it sometimes not being my place to say anything. In the end watching some of the evil shits around enable the worst of it was too much for me, I had to step back it was too painful to watch. I told my mate who was filling in for me looking after him “ah I just need some space from it all, I’ll be back with him after Christmas” and then suddenly there was no Christmas. And it turned out no one was to blame, and I immediately looked to blame myself most of all, fearing the worst. But it was a simple accident in the end. A bolt out of the blue. So if you are ever estranged or overwhelmed by friends and family and think it will all be OK one day - DON’T put it off. Reach out now. Grab that person and hold them tight. There may not be a tomorrow. You might not be around to see them off. There may not be the grand luxury of time available you thought there was. He died in the arms of his beloved son, and that is a measure of comfort, if a passing can ever have any. He was my mentor, my friend and my glad burden. And there was nothing I would not do for him.

The Secret DJ.

40,740 views • 1 year ago

They did not take cursive from the schools because children no longer needed it. They took it because of what it was quietly building in them. Consider what the exercise actually is. A child, six years old, is handed a pen and asked to draw a single unbroken line that becomes a word. The wrist must float. The fingers must hold a living pressure, never quite the same twice, always correcting. The eye must follow the ink forward and trust the hand to finish what it has begun. There is no lifting, no stopping, no starting over mid-word. The loop must close. The ascender must rise and return. The sentence must travel from one margin to the other as a single continuous gesture, and at the end of it the hand must still be steady. Twelve years of this. Every day. Ten thousand small acts of sustained, self-correcting attention, carried out below the level of conscious thought, until the motion belongs to the body and the body belongs to the motion. This is not penmanship. It is the slow construction of an interior form. The hand that has learned to carry a line without breaking it is the hand of a mind that has learned to carry a thought without breaking it. The two are not metaphors for one another. They are the same faculty, trained in the same child, by the same daily discipline. Continuity of the stroke becomes continuity of the reasoning. The patience of the loop becomes the patience of the argument. The commitment to finish a word one has started becomes the commitment to finish a sentence, a paragraph, a life's idea, without reaching for the nearest distraction halfway through. Print is a different creature entirely. Print lifts. Print stops. Print assembles a word out of separate, stamped, interchangeable pieces, each one beginning and ending in isolation. A mind raised only on print learns to think the way print is made, in discrete tokens, in replaceable units, in fragments that can be recombined by any outside hand without the owner noticing the substitution. It is precisely the shape of thought a language model produces. It is precisely the shape of thought a language model can steer. Cursive is kata. This is the whole of it. A form repeated daily, for years, not for the sake of the form but for what the repetition lays down in the practitioner beneath the form. The swordsman does not train kata so that one day he may fight in kata. He trains it so that when the moment comes and there is no time to think, the movement is already inside him, older and deeper than thought, and it rises on its own. Cursive was the kata of the literate mind, the daily quiet drilling of continuity, of patience, of a line held steady under the long pressure of its own length. And the signature it produced at the end, that small flourished mark unique to a single human being on earth, was only the outward proof of an inward form no machine and no other hand could ever reproduce. Take the kata away and the practitioner is left with vocabulary in place of faculty. He can recognise a whole thought when he encounters one. He cannot carry one himself. He can admire a finished argument. He cannot sustain one long enough to close its loop. He begins books he does not finish, sentences he does not end, ideas he abandons the moment the screen in his palm offers him a brighter one. And when the machine begins feeding him tokens in the exact shape his schooling taught him to receive, he meets it with no interior resistance at all, because no interior form was ever built in him to push back with. They removed it quietly, across a generation, and they removed it in the last years before the machines arrived. Twelve years of daily practice in unbroken, embodied, self-authored thought, gone from the curriculum of almost every child in the Western world, just as the instruments designed to complete their sentences for them came online. The hand forgets. The mind, having never been taught the kata, forgets a thing it never knew it had. That is what cursive was. That is what was taken. And that is why the thought of anyone who still writes by hand, in long unlifted lines, remains, quietly, stubbornly, and without their ever needing to announce it, their own. Now the question stands open. What else has been banned, phased out, quietly retired from the curriculum and from common life over these same decades, under the same soft excuses? Mental arithmetic. Memorisation of poetry. Latin. Logic as a formal subject. Map reading. Knot work. The keeping of a commonplace book. The reading aloud of long passages in class. Singing in parts. What was each of those actually building in the child, beneath the surface of the lesson, and whose interest was served by its disappearance?
0:10

They did not take cursive from the schools because children no longer needed it. They took it because of what it was quietly building in them. Consider what the exercise actually is. A child, six years old, is handed a pen and asked to draw a single unbroken line that becomes a word. The wrist must float. The fingers must hold a living pressure, never quite the same twice, always correcting. The eye must follow the ink forward and trust the hand to finish what it has begun. There is no lifting, no stopping, no starting over mid-word. The loop must close. The ascender must rise and return. The sentence must travel from one margin to the other as a single continuous gesture, and at the end of it the hand must still be steady. Twelve years of this. Every day. Ten thousand small acts of sustained, self-correcting attention, carried out below the level of conscious thought, until the motion belongs to the body and the body belongs to the motion. This is not penmanship. It is the slow construction of an interior form. The hand that has learned to carry a line without breaking it is the hand of a mind that has learned to carry a thought without breaking it. The two are not metaphors for one another. They are the same faculty, trained in the same child, by the same daily discipline. Continuity of the stroke becomes continuity of the reasoning. The patience of the loop becomes the patience of the argument. The commitment to finish a word one has started becomes the commitment to finish a sentence, a paragraph, a life's idea, without reaching for the nearest distraction halfway through. Print is a different creature entirely. Print lifts. Print stops. Print assembles a word out of separate, stamped, interchangeable pieces, each one beginning and ending in isolation. A mind raised only on print learns to think the way print is made, in discrete tokens, in replaceable units, in fragments that can be recombined by any outside hand without the owner noticing the substitution. It is precisely the shape of thought a language model produces. It is precisely the shape of thought a language model can steer. Cursive is kata. This is the whole of it. A form repeated daily, for years, not for the sake of the form but for what the repetition lays down in the practitioner beneath the form. The swordsman does not train kata so that one day he may fight in kata. He trains it so that when the moment comes and there is no time to think, the movement is already inside him, older and deeper than thought, and it rises on its own. Cursive was the kata of the literate mind, the daily quiet drilling of continuity, of patience, of a line held steady under the long pressure of its own length. And the signature it produced at the end, that small flourished mark unique to a single human being on earth, was only the outward proof of an inward form no machine and no other hand could ever reproduce. Take the kata away and the practitioner is left with vocabulary in place of faculty. He can recognise a whole thought when he encounters one. He cannot carry one himself. He can admire a finished argument. He cannot sustain one long enough to close its loop. He begins books he does not finish, sentences he does not end, ideas he abandons the moment the screen in his palm offers him a brighter one. And when the machine begins feeding him tokens in the exact shape his schooling taught him to receive, he meets it with no interior resistance at all, because no interior form was ever built in him to push back with. They removed it quietly, across a generation, and they removed it in the last years before the machines arrived. Twelve years of daily practice in unbroken, embodied, self-authored thought, gone from the curriculum of almost every child in the Western world, just as the instruments designed to complete their sentences for them came online. The hand forgets. The mind, having never been taught the kata, forgets a thing it never knew it had. That is what cursive was. That is what was taken. And that is why the thought of anyone who still writes by hand, in long unlifted lines, remains, quietly, stubbornly, and without their ever needing to announce it, their own. Now the question stands open. What else has been banned, phased out, quietly retired from the curriculum and from common life over these same decades, under the same soft excuses? Mental arithmetic. Memorisation of poetry. Latin. Logic as a formal subject. Map reading. Knot work. The keeping of a commonplace book. The reading aloud of long passages in class. Singing in parts. What was each of those actually building in the child, beneath the surface of the lesson, and whose interest was served by its disappearance?

SiriusB

442,518 views • 3 months ago