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this guy turned a raw 10-second phone clip into a multi-character media engine and pulled $19,400 in agency retainers this month he didn't rent a studio, buy expensive lighting, or hire actors → original clip: record yourself in a regular alleyway wearing black clothing → google flow upload: drop...

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Ridark

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46,302 views • 1 month ago •via X (Twitter)

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This guy is turning every frame of his bedroom into a high-end commercial set and printed $28,700 in commissions this month by selling these "live-edit" assets to digital stores. The workflow that prints money from a single bedroom cam: > raw footage: record 10 seconds of you holding a plain steel tumbler > Gemini Omni prompt: "transform steel tumbler to glass bottle with glowing orange liquid, match physics and hand-grip" > environment swap: "turn toy shelf into a functioning aquarium with floating goldfish" > lighting pass: "open window curtains, cast realistic sunlight across the desk, add lamp glow" The results are indistinguishable from professional VFX work that usually requires a 10-person crew and weeks of post-production. Earnings breakout: > 5 custom ad assets for a beverage brand: $12,500 > 4 interactive shop interior renders: $9,200 > direct licensing of "live-aquarium" loop: $7,000 Most product photographers are still fighting with studio lights, reflection management, and expensive glass props. He bypassed the physical studio setup for the cost of a Google AI Pro subscription.
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This guy is turning every frame of his bedroom into a high-end commercial set and printed $28,700 in commissions this month by selling these "live-edit" assets to digital stores. The workflow that prints money from a single bedroom cam: > raw footage: record 10 seconds of you holding a plain steel tumbler > Gemini Omni prompt: "transform steel tumbler to glass bottle with glowing orange liquid, match physics and hand-grip" > environment swap: "turn toy shelf into a functioning aquarium with floating goldfish" > lighting pass: "open window curtains, cast realistic sunlight across the desk, add lamp glow" The results are indistinguishable from professional VFX work that usually requires a 10-person crew and weeks of post-production. Earnings breakout: > 5 custom ad assets for a beverage brand: $12,500 > 4 interactive shop interior renders: $9,200 > direct licensing of "live-aquarium" loop: $7,000 Most product photographers are still fighting with studio lights, reflection management, and expensive glass props. He bypassed the physical studio setup for the cost of a Google AI Pro subscription.

Gipp 🦅

17,793 views • 1 month ago

A 23-year-old game modder from Prague uploaded one image of a battle axe into Claude Opus 4.8 and built a $6,200/month 3D asset factory without opening a single modeling tab he let the model write the entire geometry script for Blender from scratch the workflow that prints ready-to-sell assets: > reference upload: drop a high-res weapon concept into the chat window > reasoning layer: Claude Opus 4.8 analyzes the edges, weight distribution, and scale > code generation: the model spits out a flawless python script in 13 minutes using 5,000 tokens > render loop: the code executes inside Blender, auto-generating complex 3D meshes with surface imperfections he found a minor shading bug, fixed it manually in 40 seconds, and uploaded the finished axe to TurboSquid and Sketchfab Earnings breakout: Week 1 > $1,120 Week 2 > $1,450 Week 3 > $1,780 Week 4 > $1,850 1 month > $6,200 net profit > most 3D artists are still spending 14 hours extruding vertices manually and crying about industry layoffs he bypassed the entire pipeline for the price of an API key
0:49

A 23-year-old game modder from Prague uploaded one image of a battle axe into Claude Opus 4.8 and built a $6,200/month 3D asset factory without opening a single modeling tab he let the model write the entire geometry script for Blender from scratch the workflow that prints ready-to-sell assets: > reference upload: drop a high-res weapon concept into the chat window > reasoning layer: Claude Opus 4.8 analyzes the edges, weight distribution, and scale > code generation: the model spits out a flawless python script in 13 minutes using 5,000 tokens > render loop: the code executes inside Blender, auto-generating complex 3D meshes with surface imperfections he found a minor shading bug, fixed it manually in 40 seconds, and uploaded the finished axe to TurboSquid and Sketchfab Earnings breakout: Week 1 > $1,120 Week 2 > $1,450 Week 3 > $1,780 Week 4 > $1,850 1 month > $6,200 net profit > most 3D artists are still spending 14 hours extruding vertices manually and crying about industry layoffs he bypassed the entire pipeline for the price of an API key

Mr. Buzzoni

20,877 views • 1 month ago

Higgsfield MCP + Codex is f*cking wild 🤯 Here's how you can generate 17 on-brand Amazon listing images by uploading one product photo. One plain-English prompt, zero manual generation. All inside the Codex app. Perfect for DTC brands and agencies who need production-quality product shots without booking a shoot or briefing a designer. If you're prompting image generators one shot at a time: Tweaking the lighting, adjusting the angle, re-running generations until something usable comes out. This combination eliminates the entire loop: → Install the Higgsfield CLI and add the skills to Codex in 5 minutes → Drop one product photo into your project folder → Type one prompt: "make me Amazon listing images — hero, lifestyle, detail, angles" → Codex interprets it, Higgsfield skills fire automatically → Finished images land in an organized folder on your machine No manual prompt tweaking. No re-running generations. No briefing a designer. What you get: → Production-quality listing images from a single product photo → Lighting, angles, and reflections handled automatically → Everything organized into folders locally on your machine → A pipeline that runs in minutes, not days Setup takes five minutes. I put together a full guide showing the exact install, the skills setup, and the prompt to run it yourself. Want it for free? > Like this post > Comment "CODEX" And I'll send it over (must be following so I can DM)
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Higgsfield MCP + Codex is f*cking wild 🤯 Here's how you can generate 17 on-brand Amazon listing images by uploading one product photo. One plain-English prompt, zero manual generation. All inside the Codex app. Perfect for DTC brands and agencies who need production-quality product shots without booking a shoot or briefing a designer. If you're prompting image generators one shot at a time: Tweaking the lighting, adjusting the angle, re-running generations until something usable comes out. This combination eliminates the entire loop: → Install the Higgsfield CLI and add the skills to Codex in 5 minutes → Drop one product photo into your project folder → Type one prompt: "make me Amazon listing images — hero, lifestyle, detail, angles" → Codex interprets it, Higgsfield skills fire automatically → Finished images land in an organized folder on your machine No manual prompt tweaking. No re-running generations. No briefing a designer. What you get: → Production-quality listing images from a single product photo → Lighting, angles, and reflections handled automatically → Everything organized into folders locally on your machine → A pipeline that runs in minutes, not days Setup takes five minutes. I put together a full guide showing the exact install, the skills setup, and the prompt to run it yourself. Want it for free? > Like this post > Comment "CODEX" And I'll send it over (must be following so I can DM)

Mike Futia

12,816 views • 2 months ago

Why the character movement in my custom game engine felt janky and how I fixed it. In a game engine, most often, a character moves using the physics engine. Meaning, the player is not just a coordinate in space but a physical body. It has velocity, it handles collisions, and it interacts with the world. Now, as you might know, physics engines need stability. If you run them at variable framerates, things start breaking. Objects phase through walls or fly off into space because the math becomes unpredictable. This is why most game engines lock their physics loop to a 60Hz fixed rate. But here’s the problem: If you have a high-end system, you don't want to limit it at 60 FPS. That's a waste of good hardware. Now, that said, if the GPU is rendering at 144 FPS but the player's position (physics driven) only updates 60 times a second, it creates a micro-stutter that ruins the "smooth" feel of the game. A good way to fix this is to treat the character as two separate things: 1. The Physics Body (Invisible part): This is the "real" character. It lives in the 60Hz physics world, it moves the player and handles collisions. 2. The Visual Model and Camera (Visible part): This is what the player actually sees. It doesn't care about collisions, its only job is to look nice and smooth at whatever framerate the GPU is pushing. Once you have this separation, you can use interpolation to keep them in sync. Every time the physics clock ticks, you save the previous position of the invisible body before moving it to the new one. Between those ticks, calculate how far we are between the last physics update and the next one. By using this to drive the visible parts of the game, the stutters disappear. The physics loop stays fixed behind the scenes, while the visuals slide smoothly between the snapshots. Example: - Right after a tick: blend_weight= 0.0 (The visual model stays at the old physics position). - Halfway to the next: blend_weight= 0.5 (The visual model slides to the middle point). - Just before the next: blend_weight= 0.9 (The visual model is almost at the new physics position). Pro-Tip A critical mistake I made initially, and one many devs make, is parenting the camera and visible parts directly to the player body. If you do this, the camera inherits the discrete 60Hz physics movement by default. In that setup, interpolation won't work because the camera is "stuck" to the physics clock. For this fix to work you must decouple the camera and visuals from the body and move them separately. Player movement processing in Detis Engine: - fixed_process: Physics runs at 60Hz. Handles collisions and raw movement. - process: Variable rate. Mainly used for player input caching in the player case. - late_process: Variable rate. Handles interpolated camera movement after physics and everything else is done being processed. - render. Submits the final interpolated transforms to the GPU. The test environment in the video is running on an old 2070-based laptop. Hopefully the video compression won't introduce any stutter... I’m sharing this in hopes it helps a fellow dev. Cheers.
0:23

Why the character movement in my custom game engine felt janky and how I fixed it. In a game engine, most often, a character moves using the physics engine. Meaning, the player is not just a coordinate in space but a physical body. It has velocity, it handles collisions, and it interacts with the world. Now, as you might know, physics engines need stability. If you run them at variable framerates, things start breaking. Objects phase through walls or fly off into space because the math becomes unpredictable. This is why most game engines lock their physics loop to a 60Hz fixed rate. But here’s the problem: If you have a high-end system, you don't want to limit it at 60 FPS. That's a waste of good hardware. Now, that said, if the GPU is rendering at 144 FPS but the player's position (physics driven) only updates 60 times a second, it creates a micro-stutter that ruins the "smooth" feel of the game. A good way to fix this is to treat the character as two separate things: 1. The Physics Body (Invisible part): This is the "real" character. It lives in the 60Hz physics world, it moves the player and handles collisions. 2. The Visual Model and Camera (Visible part): This is what the player actually sees. It doesn't care about collisions, its only job is to look nice and smooth at whatever framerate the GPU is pushing. Once you have this separation, you can use interpolation to keep them in sync. Every time the physics clock ticks, you save the previous position of the invisible body before moving it to the new one. Between those ticks, calculate how far we are between the last physics update and the next one. By using this to drive the visible parts of the game, the stutters disappear. The physics loop stays fixed behind the scenes, while the visuals slide smoothly between the snapshots. Example: - Right after a tick: blend_weight= 0.0 (The visual model stays at the old physics position). - Halfway to the next: blend_weight= 0.5 (The visual model slides to the middle point). - Just before the next: blend_weight= 0.9 (The visual model is almost at the new physics position). Pro-Tip A critical mistake I made initially, and one many devs make, is parenting the camera and visible parts directly to the player body. If you do this, the camera inherits the discrete 60Hz physics movement by default. In that setup, interpolation won't work because the camera is "stuck" to the physics clock. For this fix to work you must decouple the camera and visuals from the body and move them separately. Player movement processing in Detis Engine: - fixed_process: Physics runs at 60Hz. Handles collisions and raw movement. - process: Variable rate. Mainly used for player input caching in the player case. - late_process: Variable rate. Handles interpolated camera movement after physics and everything else is done being processed. - render. Submits the final interpolated transforms to the GPU. The test environment in the video is running on an old 2070-based laptop. Hopefully the video compression won't introduce any stutter... I’m sharing this in hopes it helps a fellow dev. Cheers.

Ioannis Koukourakis

48,636 views • 6 months ago

📖SEEDANCE 2.0 JUST MADE EVERY FILM SCHOOL IRRELEVANT FOR SOLO CREATORS Solo creators with the right workflow are closing clients that used to require a full production studio. Seedance 2.0 inside Dreamina holds character consistency across scenes in a way no other tool at this price point comes close to. Same face, same costume, same lighting logic — frame after frame after frame. That's the feature that turns a single prompt session into a short film. The lava demon materializing inside a gothic cathedral. The girl in black holding her ground while everything burns around her. Two characters with completely different visual languages sharing the same atmospheric world — and Seedance holds both of them consistent across every cut. That's not a generation. That's a production. Here's the 7-step workflow that produced this: • Step 1 — Define the character before you define the scene. Write a complete physical description — face structure, hair, clothing, skin, posture. This becomes the anchor every future generation references. • Step 2 — Build the world separately from the character. Gothic cathedral, candlelight, fog, cracked stone, scattered bodies. Define the atmosphere as its own entity before you place anyone inside it. • Step 3 — Generate the reference frame. One image that establishes the visual language, the color grade, the lighting temperature. Lock this as your style reference before generating any video. • Step 4 — Feed the reference into Seedance's image-to-video pipeline with a motion prompt. Camera behavior only — slow push, hold, circle. The image handles the subject. The prompt handles the direction. • Step 5 — Generate four variations per scene. Delete the two that look generated. Keep the one where the character's face holds and the atmosphere feels physical rather than rendered. • Step 6 — Edit in CapCut or Premiere Pro. Add music that matches the emotional temperature of the grade — the visual already tells you what the sound should feel like. Dark orchestral, slow tempo, single instrument carrying the melody. • Step 7 — Save the character description and reference frame as a template. The next episode starts from the same character in the same world. Series content becomes a system, not a restart. How a freelancer sells this: Dark fantasy content for game studios, music artists, and fantasy brands is a real market with real budgets. A musician dropping an album needs a visual world. A game studio needs promotional cinematics. A fantasy brand needs a story. Where to find clients: • Music artists on SoundCloud and Spotify releasing dark, gothic, or cinematic albums — search by genre, find artists with 1k–50k listeners who have no visual content. They have the audience and the need but no production budget for traditional video. • Indie game studios on Itch and Steam launching fantasy or horror titles — they need promotional cinematics and trailers but can't afford a production company. A single free scene built from their game's character art opens every conversation. • Dark fantasy and gothic brands on Instagram and TikTok with strong photo content but zero video presence — jewelry brands, clothing labels, occult lifestyle brands. They have the aesthetic already built. You just add motion to it. • Fantasy and horror fiction authors on Instagram and Substack launching new books — they need visual teasers, trailers, and world-building content to build pre-launch audiences. Most have no idea this kind of production is accessible at this price point. • Tabletop RPG creators and Dungeon Masters on Patreon and Kickstarter — they build entire fantasy universes and need cinematic content for campaigns, promotional videos, and subscriber rewards. The niche is underserved and the creators inside it spend consistently on content tools and services. 📥Tomorrow I'll show you what's sitting right next to this opportunity. 🔖Save this if you are looking for practical AI methods that actually pay.
0:36

📖SEEDANCE 2.0 JUST MADE EVERY FILM SCHOOL IRRELEVANT FOR SOLO CREATORS Solo creators with the right workflow are closing clients that used to require a full production studio. Seedance 2.0 inside Dreamina holds character consistency across scenes in a way no other tool at this price point comes close to. Same face, same costume, same lighting logic — frame after frame after frame. That's the feature that turns a single prompt session into a short film. The lava demon materializing inside a gothic cathedral. The girl in black holding her ground while everything burns around her. Two characters with completely different visual languages sharing the same atmospheric world — and Seedance holds both of them consistent across every cut. That's not a generation. That's a production. Here's the 7-step workflow that produced this: • Step 1 — Define the character before you define the scene. Write a complete physical description — face structure, hair, clothing, skin, posture. This becomes the anchor every future generation references. • Step 2 — Build the world separately from the character. Gothic cathedral, candlelight, fog, cracked stone, scattered bodies. Define the atmosphere as its own entity before you place anyone inside it. • Step 3 — Generate the reference frame. One image that establishes the visual language, the color grade, the lighting temperature. Lock this as your style reference before generating any video. • Step 4 — Feed the reference into Seedance's image-to-video pipeline with a motion prompt. Camera behavior only — slow push, hold, circle. The image handles the subject. The prompt handles the direction. • Step 5 — Generate four variations per scene. Delete the two that look generated. Keep the one where the character's face holds and the atmosphere feels physical rather than rendered. • Step 6 — Edit in CapCut or Premiere Pro. Add music that matches the emotional temperature of the grade — the visual already tells you what the sound should feel like. Dark orchestral, slow tempo, single instrument carrying the melody. • Step 7 — Save the character description and reference frame as a template. The next episode starts from the same character in the same world. Series content becomes a system, not a restart. How a freelancer sells this: Dark fantasy content for game studios, music artists, and fantasy brands is a real market with real budgets. A musician dropping an album needs a visual world. A game studio needs promotional cinematics. A fantasy brand needs a story. Where to find clients: • Music artists on SoundCloud and Spotify releasing dark, gothic, or cinematic albums — search by genre, find artists with 1k–50k listeners who have no visual content. They have the audience and the need but no production budget for traditional video. • Indie game studios on Itch and Steam launching fantasy or horror titles — they need promotional cinematics and trailers but can't afford a production company. A single free scene built from their game's character art opens every conversation. • Dark fantasy and gothic brands on Instagram and TikTok with strong photo content but zero video presence — jewelry brands, clothing labels, occult lifestyle brands. They have the aesthetic already built. You just add motion to it. • Fantasy and horror fiction authors on Instagram and Substack launching new books — they need visual teasers, trailers, and world-building content to build pre-launch audiences. Most have no idea this kind of production is accessible at this price point. • Tabletop RPG creators and Dungeon Masters on Patreon and Kickstarter — they build entire fantasy universes and need cinematic content for campaigns, promotional videos, and subscriber rewards. The niche is underserved and the creators inside it spend consistently on content tools and services. 📥Tomorrow I'll show you what's sitting right next to this opportunity. 🔖Save this if you are looking for practical AI methods that actually pay.

Zentrix⌚️

50,098 views • 1 month ago

DRONE VIDEOGRAPHERS CHARGE $10K FOR THIS SHOT. HE PULLS IT FROM GOOGLE EARTH AND A PROMPT You never buy a drone, book a pilot, or leave the house. You pick any city on Earth, trace the flight path you want, and let Gemini render it as real-looking FPV footage. Clients pay thousands for this shot. You make it from a screenshot Here is the exact process: 1. Open Google Earth. Find the city or building you want. Frame the angle you'd want a drone to start from and take a screenshot 2. Draw the path. On that screenshot, draw a red line showing exactly where the drone should fly through the scene. This line is what the AI follows 3. Open Gemini and drop in the screenshot. Use the video generation in the Gemini app, the part that animates a still image into motion. Nano Banana handles images, the video engine is what turns your shot into footage 4. Paste the prompt. Tell it to follow the red flight path through the city, fast smooth motion, banking around buildings, golden-hour light, motion blur, 9:16 vertical, real FPV drone look. Full prompt is in the comments 5. Generate and clean it up. One clip is a few seconds. Stitch a couple together for a full flythrough and you have a reel Set the prompt once and you can re-run it for any location on the planet Who pays for this: Real estate agents, hotels, restaurants and event venues all need aerial b-roll and almost none can afford a real drone shoot Pull listings or venues with flat, ground-level photos and zero aerial footage. Send a free sample flythrough of their own location, then charge per clip or a monthly rate for ongoing reels One agent with ten listings is a recurring client, fully online Full prompt in the comments Bookmark this
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DRONE VIDEOGRAPHERS CHARGE $10K FOR THIS SHOT. HE PULLS IT FROM GOOGLE EARTH AND A PROMPT You never buy a drone, book a pilot, or leave the house. You pick any city on Earth, trace the flight path you want, and let Gemini render it as real-looking FPV footage. Clients pay thousands for this shot. You make it from a screenshot Here is the exact process: 1. Open Google Earth. Find the city or building you want. Frame the angle you'd want a drone to start from and take a screenshot 2. Draw the path. On that screenshot, draw a red line showing exactly where the drone should fly through the scene. This line is what the AI follows 3. Open Gemini and drop in the screenshot. Use the video generation in the Gemini app, the part that animates a still image into motion. Nano Banana handles images, the video engine is what turns your shot into footage 4. Paste the prompt. Tell it to follow the red flight path through the city, fast smooth motion, banking around buildings, golden-hour light, motion blur, 9:16 vertical, real FPV drone look. Full prompt is in the comments 5. Generate and clean it up. One clip is a few seconds. Stitch a couple together for a full flythrough and you have a reel Set the prompt once and you can re-run it for any location on the planet Who pays for this: Real estate agents, hotels, restaurants and event venues all need aerial b-roll and almost none can afford a real drone shoot Pull listings or venues with flat, ground-level photos and zero aerial footage. Send a free sample flythrough of their own location, then charge per clip or a monthly rate for ongoing reels One agent with ten listings is a recurring client, fully online Full prompt in the comments Bookmark this

Yarchi

53,000 views • 1 month ago

You’ve been lied to about what “sugar” actually is your entire life. Watch this 53-second clip and try not to drop your phone Dr. Mark Hyman revealed: - The entire Glycemic Index (the scale that measures how fast food turns into blood sugar) sets plain white bread at 100. - Pure table sugar? Only 65. Meaning: a sandwich can spike your blood sugar HARDER and FASTER than spooning straight sugar. He explains it perfectly: “Below the neck, your body literally cannot tell the difference between a bowl of breakfast cereal and a bowl of table sugar… or a loaf of bread.” He then drops the wild (public record) story of how, years ago, the World Health Organization wanted to cut recommended sugar from 10 % to 5 % of calories — and a high-level U.S. official flew to Geneva threatening to pull hundreds of millions in funding if they did. The guidelines stayed at 10 %. 53 seconds that will change how you look at every aisle in the supermarket forever. Watch till the end — the last 10 seconds are the biggest jaw-drop. Which part shocked you the most? Tell me in the replies, I read every single one 👇
0:53

You’ve been lied to about what “sugar” actually is your entire life. Watch this 53-second clip and try not to drop your phone Dr. Mark Hyman revealed: - The entire Glycemic Index (the scale that measures how fast food turns into blood sugar) sets plain white bread at 100. - Pure table sugar? Only 65. Meaning: a sandwich can spike your blood sugar HARDER and FASTER than spooning straight sugar. He explains it perfectly: “Below the neck, your body literally cannot tell the difference between a bowl of breakfast cereal and a bowl of table sugar… or a loaf of bread.” He then drops the wild (public record) story of how, years ago, the World Health Organization wanted to cut recommended sugar from 10 % to 5 % of calories — and a high-level U.S. official flew to Geneva threatening to pull hundreds of millions in funding if they did. The guidelines stayed at 10 %. 53 seconds that will change how you look at every aisle in the supermarket forever. Watch till the end — the last 10 seconds are the biggest jaw-drop. Which part shocked you the most? Tell me in the replies, I read every single one 👇

Camus

127,185 views • 7 months ago

This guy got Claude to take control of Arcads and generate hyperrealistic UGC ads with a consistent AI actor, from a 7-word prompt, and now e-com brands pay him $1,500 per video to clone the setup. He got tired of watching DTC brands burn $4K on a photoshoot that dies the second a product angle changes, so he built a 2-prompt workflow that turns one product photo into scroll-stopping UGC without a single model, camera, or casting call. Here's the exact breakdown: → Claude is the director, Arcads is the studio. You never write a real prompt, you write one sentence → Type 7 words: "create a character sheet of a UGC actress on Arcads." Claude expands it into a 40-line spec: warm skin tone, high ponytail, gold hoops, white AirPods, athletic build, then takes control of Arcads itself → Arcads renders a 6-angle character sheet: front, back, profile, 3/4, two portraits, one consistent face locked across all of them → You download the grid and drop it back into Claude with one product photo → Second prompt, 8 words: "use Seedance 2.0 on Arcads to create natural UGC" → Claude writes the full shot list: timecodes, "1:03 AM clock zoom," the trackpad scroll, the arm pull that drags the product into frame, "delivery: casual, energetic," "ends on a wink + air kiss" → Arcads cuts the yellow Vans print onto an actor who was wearing all black in the grid. Real fabric folds, real light, zero warping → Final render: lip-sync locked to consonants, head not glued to the camera, a girl filming at 1am on her bed The key move 96% of people skip: you can't put the product on the actor before you lock the character sheet. If you drop a product photo onto a face that isn't locked across angles, the identity drifts frame to frame. The jaw resets. The skin tone shifts. The print slides off the fabric. The whole thing screams "AI" and your CTR dies in the first 2 seconds. His system locks the 6-view sheet first, so Arcads has one real human to dress, and the top lands with natural folds even though the grid never had it. One apparel brand ran 20 variants off a single product photo and found a winner in 36 hours, because the clips read like organic UGC, not a studio ad. Brands now pay him $1,500 per avatar build + $340/month to keep dropping fresh video batches on every new product. The entire thing runs on two prompts and one laptop. No photographer. No model agency. No product samples on set. Just two sentences, one product photo, and the discipline to lock the character before you render a single second of movement.
1:05

This guy got Claude to take control of Arcads and generate hyperrealistic UGC ads with a consistent AI actor, from a 7-word prompt, and now e-com brands pay him $1,500 per video to clone the setup. He got tired of watching DTC brands burn $4K on a photoshoot that dies the second a product angle changes, so he built a 2-prompt workflow that turns one product photo into scroll-stopping UGC without a single model, camera, or casting call. Here's the exact breakdown: → Claude is the director, Arcads is the studio. You never write a real prompt, you write one sentence → Type 7 words: "create a character sheet of a UGC actress on Arcads." Claude expands it into a 40-line spec: warm skin tone, high ponytail, gold hoops, white AirPods, athletic build, then takes control of Arcads itself → Arcads renders a 6-angle character sheet: front, back, profile, 3/4, two portraits, one consistent face locked across all of them → You download the grid and drop it back into Claude with one product photo → Second prompt, 8 words: "use Seedance 2.0 on Arcads to create natural UGC" → Claude writes the full shot list: timecodes, "1:03 AM clock zoom," the trackpad scroll, the arm pull that drags the product into frame, "delivery: casual, energetic," "ends on a wink + air kiss" → Arcads cuts the yellow Vans print onto an actor who was wearing all black in the grid. Real fabric folds, real light, zero warping → Final render: lip-sync locked to consonants, head not glued to the camera, a girl filming at 1am on her bed The key move 96% of people skip: you can't put the product on the actor before you lock the character sheet. If you drop a product photo onto a face that isn't locked across angles, the identity drifts frame to frame. The jaw resets. The skin tone shifts. The print slides off the fabric. The whole thing screams "AI" and your CTR dies in the first 2 seconds. His system locks the 6-view sheet first, so Arcads has one real human to dress, and the top lands with natural folds even though the grid never had it. One apparel brand ran 20 variants off a single product photo and found a winner in 36 hours, because the clips read like organic UGC, not a studio ad. Brands now pay him $1,500 per avatar build + $340/month to keep dropping fresh video batches on every new product. The entire thing runs on two prompts and one laptop. No photographer. No model agency. No product samples on set. Just two sentences, one product photo, and the discipline to lock the character before you render a single second of movement.

Shade

15,227 views • 1 month ago

Gemini 2.5 Flash demolishes my Galton Board test, I could not get 4omini, 4o mini high, or 03 to produce this. I found that Gemini 2.5 Flash understands my intents almost instantly, code produced is tight and neat. The prompt is a merging of various steps. It took me 5 steps to achieve this in Gemini 2.5 Flash, I gave up on OpenAI models after about half an hour. My iterations are obviously not exact. But people can test with this one prompt for more objective comparison. Please try this prompt on your end to confirm: -------------------------------------------------- Create a self-contained HTML file for a Galton board simulation using client-side JavaScript and a 2D physics engine (like Matter.js, included via CDN). The simulation should be rendered on an HTML5 canvas and meet the following criteria: 1. **Single File:** All necessary HTML, CSS, and JavaScript code must be within this single `.html` file. 2. **Canvas Size:** The overall simulation area (canvas) should be reasonably sized to fit on a standard screen without requiring extensive scrolling or zooming (e.g., around 500x700 pixels). 3. **Physics:** Utilize a 2D rigid body physics engine for realistic ball-peg and ball-wall interactions. 4. **Obstacles (Pegs):** Create static, circular pegs arranged in full-width horizontal rows extending across the usable width of the board (not just a triangle). The pegs should be small enough and spaced appropriately for balls to navigate and bounce between them. 5. **Containment:** * Include static, sufficiently thick side walls and a ground at the bottom to contain the balls within the board. * Implement *physical* static dividers between the collection bins at the bottom. These dividers must be thick enough to prevent balls from passing through them, ensuring accurate accumulation in each bin. 6. **Ball Dropping:** Balls should be dropped from a controlled, narrow area near the horizontal center at the top of the board to ensure they enter the peg field consistently. 7. **Bins:** The collection area at the bottom should be divided into distinct bins by the physical dividers. The height of the bins should be sufficient to clearly visualize the accumulation of balls. 8. **Visualization:** Use a high-contrast color scheme to clearly distinguish between elements. Specifically, use yellow for the structural elements (walls, top guides, physical bin dividers, ground), a contrasting color (like red) for the pegs, and a highly contrasting color (like dark grey or black) for the balls. 9. **Demonstration:** The simulation should visually demonstrate the formation of the normal (or binomial) distribution as multiple balls fall through the pegs and collect in the bins. Ensure the physics parameters (restitution, friction, density) and ball drop rate are tuned for a smooth and clear demonstration of the distribution. #OpenAI Sam Altman Greg Brockman AshutoshShrivastava Aidan McLaughlin
0:44

Gemini 2.5 Flash demolishes my Galton Board test, I could not get 4omini, 4o mini high, or 03 to produce this. I found that Gemini 2.5 Flash understands my intents almost instantly, code produced is tight and neat. The prompt is a merging of various steps. It took me 5 steps to achieve this in Gemini 2.5 Flash, I gave up on OpenAI models after about half an hour. My iterations are obviously not exact. But people can test with this one prompt for more objective comparison. Please try this prompt on your end to confirm: -------------------------------------------------- Create a self-contained HTML file for a Galton board simulation using client-side JavaScript and a 2D physics engine (like Matter.js, included via CDN). The simulation should be rendered on an HTML5 canvas and meet the following criteria: 1. **Single File:** All necessary HTML, CSS, and JavaScript code must be within this single `.html` file. 2. **Canvas Size:** The overall simulation area (canvas) should be reasonably sized to fit on a standard screen without requiring extensive scrolling or zooming (e.g., around 500x700 pixels). 3. **Physics:** Utilize a 2D rigid body physics engine for realistic ball-peg and ball-wall interactions. 4. **Obstacles (Pegs):** Create static, circular pegs arranged in full-width horizontal rows extending across the usable width of the board (not just a triangle). The pegs should be small enough and spaced appropriately for balls to navigate and bounce between them. 5. **Containment:** * Include static, sufficiently thick side walls and a ground at the bottom to contain the balls within the board. * Implement *physical* static dividers between the collection bins at the bottom. These dividers must be thick enough to prevent balls from passing through them, ensuring accurate accumulation in each bin. 6. **Ball Dropping:** Balls should be dropped from a controlled, narrow area near the horizontal center at the top of the board to ensure they enter the peg field consistently. 7. **Bins:** The collection area at the bottom should be divided into distinct bins by the physical dividers. The height of the bins should be sufficient to clearly visualize the accumulation of balls. 8. **Visualization:** Use a high-contrast color scheme to clearly distinguish between elements. Specifically, use yellow for the structural elements (walls, top guides, physical bin dividers, ground), a contrasting color (like red) for the pegs, and a highly contrasting color (like dark grey or black) for the balls. 9. **Demonstration:** The simulation should visually demonstrate the formation of the normal (or binomial) distribution as multiple balls fall through the pegs and collect in the bins. Ensure the physics parameters (restitution, friction, density) and ball drop rate are tuned for a smooth and clear demonstration of the distribution. #OpenAI Sam Altman Greg Brockman AshutoshShrivastava Aidan McLaughlin

RameshR

247,923 views • 1 year ago

The simplest hustle I've seen this year. He pulled $1,800 in 5 minutes using Claude Meet Gianni. A regular dude with a laptop, sitting in his bedroom. No courses to sell, no team behind him, no fancy setup. What he does is honestly stupid simple. He opens Google Maps in his city. Scrolls around. Looks for one specific thing. Local businesses with great reviews but no website. Roofers. Plumbers. Landscapers. HVAC guys. Tree services. Half of them are still running their entire operation off a phone number and word of mouth. In the video he finds Aspen Roofing in Colorado Springs. 4.5 stars, 8 reviews, zero web presence. That's his target. He copies the company name. Pulls a few of their best Google reviews. Pastes everything into Claude with one prompt. «Build me a sexy, luxurious, high-converting website for this business. Use these reviews to understand their strengths.» Claude writes the entire site from scratch. He drops the code into Lovable, clicks Publish, and a real working website is live in one click. Hero section reads «Colorado's Premier Roofing Experience.» CTA button says «Get Your Free Roof Inspection.» Now the fun part. He emails or DMs the owner with the link. Says «I built you something, take a look.» The owner sees a professional site that already represents his brand. Buys it on the spot for $1,000 to $2,000. Plugs in his domain. Done. One website. 5 minutes of work. $1,800 in the pocket. And there are millions of local businesses in the US still running without a site. He's just stamping them out one after another.
0:56

The simplest hustle I've seen this year. He pulled $1,800 in 5 minutes using Claude Meet Gianni. A regular dude with a laptop, sitting in his bedroom. No courses to sell, no team behind him, no fancy setup. What he does is honestly stupid simple. He opens Google Maps in his city. Scrolls around. Looks for one specific thing. Local businesses with great reviews but no website. Roofers. Plumbers. Landscapers. HVAC guys. Tree services. Half of them are still running their entire operation off a phone number and word of mouth. In the video he finds Aspen Roofing in Colorado Springs. 4.5 stars, 8 reviews, zero web presence. That's his target. He copies the company name. Pulls a few of their best Google reviews. Pastes everything into Claude with one prompt. «Build me a sexy, luxurious, high-converting website for this business. Use these reviews to understand their strengths.» Claude writes the entire site from scratch. He drops the code into Lovable, clicks Publish, and a real working website is live in one click. Hero section reads «Colorado's Premier Roofing Experience.» CTA button says «Get Your Free Roof Inspection.» Now the fun part. He emails or DMs the owner with the link. Says «I built you something, take a look.» The owner sees a professional site that already represents his brand. Buys it on the spot for $1,000 to $2,000. Plugs in his domain. Done. One website. 5 minutes of work. $1,800 in the pocket. And there are millions of local businesses in the US still running without a site. He's just stamping them out one after another.

winkle.

112,420 views • 2 months ago

This Chinese guy created agents in Claude Code for MCP servers and single-handedly serves 6 marketing agencies a month from one iPhone, earning $5,000 from each. Inside he runs a pipeline of 7 agents on Claude Sonnet 4.6 that every Monday pulls a scan of the tech stack from a selected agency, develops an MCP server for its ad accounts, and over the course of a week brings it to production code ready to connect to Claude Desktop. No DevOps, no senior developer, no project manager. Just a Mac Mini in a work corner, an iPhone in the pocket, and a single API key. And traditional dev shops keep 5 people on project rates for the same contract, while his entire P&L is tokens, dirt-cheap hosting on Cloudflare, and Calendly. 7 agents run under a shared orchestrator-router and burn about 5 million tokens a day, which in the API bill comes out to $540 a month. The Mac Mini itself sits at home and keeps the entire orchestrator running 24/7, and from the iPhone the owner connects to it through a secure remote terminal and sees the output of any session right on the smartphone screen, wherever he happens to be. His starting system prompt looks like this: "you run a solo shop for custom MCP servers for marketing agencies. you hand out read-only tasks to 6 sub-agents and own all commits and shipping yourself. sub-agents: // Hunter (finds marketing agencies of 15 to 60 people that have no MCP access to Google Ads, Meta Ads, TikTok Ads, and HubSpot) // Mapper (pulls their tech stack, identifies 3 to 5 integration pains, and simultaneously writes the technical spec for the server: which tools, resources, and prompts to export through MCP, which auth flow and rate limit) // Coder (generates an MCP server in Python through the MCP SDK, deploys 8 to 15 tools for ad accounts and CRM) // Validator (connects the server to Claude Desktop, runs real client API keys in a sandbox, and checks for compliance with the MCP spec) // Shipper (writes a README, integration guide, deployment manual, packages the server, and hosts it on Cloudflare Workers or pushes to the GitHub of the client) // Mobile (always online on the iPhone, books demo calls in Calendly, picks up hot fixes, and confirms contracts through a secure remote terminal to the Mac Mini). only 1 owner agent works on 1 contract, no overlaps. you pull the owner out of observation mode only when a deal goes above $7,500 or the test coverage of the server drops below 85%." This prompt gives the system an understanding of its role and the limits of intervention from the very first line. It knows it is supposed to find agencies on its own. It knows it is supposed to bring every MCP server to production on its own. It knows it connects the live owner only on large deals or when the tests do not converge. → The pipeline runs without breaks, day or night → Hunter goes through about 130 marketing agencies on LinkedIn and Clutch per day → Mapper rolls out 4 audit reports with the tech stack and a final spec for each → Coder writes 1 to 2 MCP servers per week in Python with 8 to 15 tools → Validator validates every server through Claude Desktop with real client API keys → Shipper rolls out the full documentation package and pushes the finished product to Cloudflare Workers or the GitHub of the client And only when a contract breaks $7,500 or test coverage drops below 85% does the orchestrator pull the owner from whatever he is doing. And when the owner at that moment is behind the wheel or at a meeting in a coworking space, the Mobile agent in his iPhone picks up 1 contract in progress: confirms a meeting with the agency CMO in Calendly, opens a live demo of the MCP server through a secure terminal to the Mac Mini, and writes the test result to the shared state. The owner just swipes "approve" and in 15 minutes joins the Zoom demo. The fresh system log from last Wednesday looks like this: "hunter report: 132 agencies checked on LinkedIn and Clutch, 19 without MCP integrations, 8 with active requests for AI tooling in job posts, 4 with an open Q4 budget. passing to mapper." "coder: MCP server for Northwave Performance Marketing built in Python, 11 tools for Google Ads, Meta Ads, and GA4, 320 lines of code. exported to /Users/dev/mcp-shop/clients/northwave/server.py. validator connecting to Claude Desktop." "validator: 11 tools passed validation through Claude Desktop, test coverage 92%, average latency 380 ms. passing to shipper." "eval flag: contract with Pacific Reach Agency at $8,200 exceeds the approved limit of $7,500. sending for manual review." In his work setup there is no cloud server, no external team, and not even a separate office. At home sits a Mac Mini with a sandbox at /Users/dev/mcp-shop, on top runs an MCP router with a single API key to Claude, and the same key is forwarded to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo shop for custom MCP servers for marketing agencies: $540 a month on the API, about $30,000 into the account, and between them 7 system prompts, 1 Mac Mini in a work corner, and 1 iPhone that never leaves the pocket.
0:33

This Chinese guy created agents in Claude Code for MCP servers and single-handedly serves 6 marketing agencies a month from one iPhone, earning $5,000 from each. Inside he runs a pipeline of 7 agents on Claude Sonnet 4.6 that every Monday pulls a scan of the tech stack from a selected agency, develops an MCP server for its ad accounts, and over the course of a week brings it to production code ready to connect to Claude Desktop. No DevOps, no senior developer, no project manager. Just a Mac Mini in a work corner, an iPhone in the pocket, and a single API key. And traditional dev shops keep 5 people on project rates for the same contract, while his entire P&L is tokens, dirt-cheap hosting on Cloudflare, and Calendly. 7 agents run under a shared orchestrator-router and burn about 5 million tokens a day, which in the API bill comes out to $540 a month. The Mac Mini itself sits at home and keeps the entire orchestrator running 24/7, and from the iPhone the owner connects to it through a secure remote terminal and sees the output of any session right on the smartphone screen, wherever he happens to be. His starting system prompt looks like this: "you run a solo shop for custom MCP servers for marketing agencies. you hand out read-only tasks to 6 sub-agents and own all commits and shipping yourself. sub-agents: // Hunter (finds marketing agencies of 15 to 60 people that have no MCP access to Google Ads, Meta Ads, TikTok Ads, and HubSpot) // Mapper (pulls their tech stack, identifies 3 to 5 integration pains, and simultaneously writes the technical spec for the server: which tools, resources, and prompts to export through MCP, which auth flow and rate limit) // Coder (generates an MCP server in Python through the MCP SDK, deploys 8 to 15 tools for ad accounts and CRM) // Validator (connects the server to Claude Desktop, runs real client API keys in a sandbox, and checks for compliance with the MCP spec) // Shipper (writes a README, integration guide, deployment manual, packages the server, and hosts it on Cloudflare Workers or pushes to the GitHub of the client) // Mobile (always online on the iPhone, books demo calls in Calendly, picks up hot fixes, and confirms contracts through a secure remote terminal to the Mac Mini). only 1 owner agent works on 1 contract, no overlaps. you pull the owner out of observation mode only when a deal goes above $7,500 or the test coverage of the server drops below 85%." This prompt gives the system an understanding of its role and the limits of intervention from the very first line. It knows it is supposed to find agencies on its own. It knows it is supposed to bring every MCP server to production on its own. It knows it connects the live owner only on large deals or when the tests do not converge. → The pipeline runs without breaks, day or night → Hunter goes through about 130 marketing agencies on LinkedIn and Clutch per day → Mapper rolls out 4 audit reports with the tech stack and a final spec for each → Coder writes 1 to 2 MCP servers per week in Python with 8 to 15 tools → Validator validates every server through Claude Desktop with real client API keys → Shipper rolls out the full documentation package and pushes the finished product to Cloudflare Workers or the GitHub of the client And only when a contract breaks $7,500 or test coverage drops below 85% does the orchestrator pull the owner from whatever he is doing. And when the owner at that moment is behind the wheel or at a meeting in a coworking space, the Mobile agent in his iPhone picks up 1 contract in progress: confirms a meeting with the agency CMO in Calendly, opens a live demo of the MCP server through a secure terminal to the Mac Mini, and writes the test result to the shared state. The owner just swipes "approve" and in 15 minutes joins the Zoom demo. The fresh system log from last Wednesday looks like this: "hunter report: 132 agencies checked on LinkedIn and Clutch, 19 without MCP integrations, 8 with active requests for AI tooling in job posts, 4 with an open Q4 budget. passing to mapper." "coder: MCP server for Northwave Performance Marketing built in Python, 11 tools for Google Ads, Meta Ads, and GA4, 320 lines of code. exported to /Users/dev/mcp-shop/clients/northwave/server.py. validator connecting to Claude Desktop." "validator: 11 tools passed validation through Claude Desktop, test coverage 92%, average latency 380 ms. passing to shipper." "eval flag: contract with Pacific Reach Agency at $8,200 exceeds the approved limit of $7,500. sending for manual review." In his work setup there is no cloud server, no external team, and not even a separate office. At home sits a Mac Mini with a sandbox at /Users/dev/mcp-shop, on top runs an MCP router with a single API key to Claude, and the same key is forwarded to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo shop for custom MCP servers for marketing agencies: $540 a month on the API, about $30,000 into the account, and between them 7 system prompts, 1 Mac Mini in a work corner, and 1 iPhone that never leaves the pocket.

Blaze

55,926 views • 2 months ago

I just built an AI-powered creative search engine with Gemini Embedding 2 + Claude Code 🤯 Drop in your UGC clips, product shots, and ad variations — then search through everything in plain English. "Show me all the unboxing clips." "Find product shots with natural lighting." "Which creator talked about sensitive skin?" All inside Claude Code. Perfect for DTC brands and agencies sitting on hundreds of creative files they can never find when they actually need them. If you're digging through a folder of random file names, scrubbing through raw footage to find that one clip, and relying on memory to track down what's already been shot... This system eliminates the entire loop: → Drop your videos, images, and docs into a project folder → One prompt to Claude Code — it builds the entire search app for you → Google's new Gemini Embedding 2 model actually watches your videos and looks at your images → It understands what's inside each file — not just the file name → Search in plain English and get back the actual assets with confidence scores No scrolling through folders. No relying on file names to find anything. No re-shooting footage you already have. What you get: → A searchable library of every creative asset your brand has ever produced → Natural language search across video, images, and documents at the same time → Results that show the actual files inline — play videos, view images, read docs → A system that gets smarter every time you add richer descriptions to your assets One free API key. No monthly subscriptions. Runs on your machine. I put together a full playbook with the exact build prompt, the setup process, and DTC/agency use cases to get this running in under 30 minutes. Want the full playbook? > Like this post > Comment "SEARCH" And I'll send it over (must be following so I can DM)
0:22

I just built an AI-powered creative search engine with Gemini Embedding 2 + Claude Code 🤯 Drop in your UGC clips, product shots, and ad variations — then search through everything in plain English. "Show me all the unboxing clips." "Find product shots with natural lighting." "Which creator talked about sensitive skin?" All inside Claude Code. Perfect for DTC brands and agencies sitting on hundreds of creative files they can never find when they actually need them. If you're digging through a folder of random file names, scrubbing through raw footage to find that one clip, and relying on memory to track down what's already been shot... This system eliminates the entire loop: → Drop your videos, images, and docs into a project folder → One prompt to Claude Code — it builds the entire search app for you → Google's new Gemini Embedding 2 model actually watches your videos and looks at your images → It understands what's inside each file — not just the file name → Search in plain English and get back the actual assets with confidence scores No scrolling through folders. No relying on file names to find anything. No re-shooting footage you already have. What you get: → A searchable library of every creative asset your brand has ever produced → Natural language search across video, images, and documents at the same time → Results that show the actual files inline — play videos, view images, read docs → A system that gets smarter every time you add richer descriptions to your assets One free API key. No monthly subscriptions. Runs on your machine. I put together a full playbook with the exact build prompt, the setup process, and DTC/agency use cases to get this running in under 30 minutes. Want the full playbook? > Like this post > Comment "SEARCH" And I'll send it over (must be following so I can DM)

Mike Futia

12,260 views • 4 months ago

These Claude Code Skills are f*cking insane 🤯 A complete brand-to-ad pipeline that builds a permanent brand brain and ships hooks, briefs, scripts, and ad variations on command. All inside Claude Code. A system perfect for DTC brands and agencies who are burning hours every week on creative production that should take minutes. If you're still copy-pasting brand context into every Claude session, briefing hooks in Slack, writing ad scripts from scratch, and hand-building variations in Canva... This system eliminates the entire loop: → Brand DNA Builder scrapes any brand and outputs a full positioning file → Brand Voice Profiler extracts voice rules from the brand's actual copy → ICP Deep Dive runs autonomous research and pulls real customer language → Hook Writer generates 20 hooks across 10 DR frameworks → Brief Generator writes full creative briefs in your brand voice → Ad Script Writer produces UGC and produced video scripts → Variation Engine takes a winning ad and generates copy + image variants No Google Doc brand briefs. No copy-pasting context every session. No starting from a blank page. What you get: → A permanent brand brain Claude reads every time → Hooks, briefs, scripts, and variations that sound like your brand — not generic AI → A continuous test loop feeding directly into Meta Ads → One workflow that scales across every client or product Built 100% in Claude Code. I'm giving away the 3 foundational skills pack that every other skill in the system reads from. Want access for free? > Like this post > Comment "SKILLS" And I'll send it over (must be following so I can DM)
0:24

These Claude Code Skills are f*cking insane 🤯 A complete brand-to-ad pipeline that builds a permanent brand brain and ships hooks, briefs, scripts, and ad variations on command. All inside Claude Code. A system perfect for DTC brands and agencies who are burning hours every week on creative production that should take minutes. If you're still copy-pasting brand context into every Claude session, briefing hooks in Slack, writing ad scripts from scratch, and hand-building variations in Canva... This system eliminates the entire loop: → Brand DNA Builder scrapes any brand and outputs a full positioning file → Brand Voice Profiler extracts voice rules from the brand's actual copy → ICP Deep Dive runs autonomous research and pulls real customer language → Hook Writer generates 20 hooks across 10 DR frameworks → Brief Generator writes full creative briefs in your brand voice → Ad Script Writer produces UGC and produced video scripts → Variation Engine takes a winning ad and generates copy + image variants No Google Doc brand briefs. No copy-pasting context every session. No starting from a blank page. What you get: → A permanent brand brain Claude reads every time → Hooks, briefs, scripts, and variations that sound like your brand — not generic AI → A continuous test loop feeding directly into Meta Ads → One workflow that scales across every client or product Built 100% in Claude Code. I'm giving away the 3 foundational skills pack that every other skill in the system reads from. Want access for free? > Like this post > Comment "SKILLS" And I'll send it over (must be following so I can DM)

Mike Futia

25,558 views • 2 months ago

REAL ESTATE PEOPLE WILL HATE HIM FOR THIS. HE BUILT A CLAUDE AGENT THAT TURNS ANY LISTING INTO A SELLABLE VIDEO ON ITS OWN Playbook: connect Claude to a video generator, paste a listing, get a cinematic tour of every room, sell it to the agent But typing the prompt for every listing doesn't scale. He turned it into a skill his Claude runs on its own Here's how to build the automated version: 1. Connect the video engine once. In Claude, go to Customize, Connectors, Add Custom Connector, name it Higgsfield, and paste the server URL from higgsfield. ai/mcp. Authenticate through your account. No API keys. Now Claude can generate video straight from chat 2. Turn the workflow into a skill. Instead of pasting the same prompt every time, have Claude build a skill. Tell it: "Create a skill called listing-to-video. When I give it a listing URL, scrape the room photos, generate a cinematic clip of each room with Higgsfield, and save them to a folder." Now the whole process is one command, not a wall of text 3. Let the agent run the listing. Hand it a URL and say "run listing-to-video on this." It pulls the photos, fires each room through the video model, and brings the clips back. You wrote the prompt once, inside the skill. You never write it again 4. Stitch and deliver. Drop the clips together into one tour. Send a free sample to the listing's agent, then charge per video or a monthly rate for ongoing listings 5. Scale it with your team. Add a skill that drafts the outreach email and one that builds a simple landing page for the agent. Now one operator runs sourcing, production, and pitching from a single Claude session The edge isn't generating one video. It's building the skill once so every future listing runs itself Bookmark this
0:42

REAL ESTATE PEOPLE WILL HATE HIM FOR THIS. HE BUILT A CLAUDE AGENT THAT TURNS ANY LISTING INTO A SELLABLE VIDEO ON ITS OWN Playbook: connect Claude to a video generator, paste a listing, get a cinematic tour of every room, sell it to the agent But typing the prompt for every listing doesn't scale. He turned it into a skill his Claude runs on its own Here's how to build the automated version: 1. Connect the video engine once. In Claude, go to Customize, Connectors, Add Custom Connector, name it Higgsfield, and paste the server URL from higgsfield. ai/mcp. Authenticate through your account. No API keys. Now Claude can generate video straight from chat 2. Turn the workflow into a skill. Instead of pasting the same prompt every time, have Claude build a skill. Tell it: "Create a skill called listing-to-video. When I give it a listing URL, scrape the room photos, generate a cinematic clip of each room with Higgsfield, and save them to a folder." Now the whole process is one command, not a wall of text 3. Let the agent run the listing. Hand it a URL and say "run listing-to-video on this." It pulls the photos, fires each room through the video model, and brings the clips back. You wrote the prompt once, inside the skill. You never write it again 4. Stitch and deliver. Drop the clips together into one tour. Send a free sample to the listing's agent, then charge per video or a monthly rate for ongoing listings 5. Scale it with your team. Add a skill that drafts the outreach email and one that builds a simple landing page for the agent. Now one operator runs sourcing, production, and pitching from a single Claude session The edge isn't generating one video. It's building the skill once so every future listing runs itself Bookmark this

Yarchi

54,840 views • 1 month ago

Claude Design is f*cking ridiculous 🤯 Claude Design now lets DTC brands and agencies rebuild any high-performing email — logo, hero, headline, CTA button, comparison table, brand colors — in 20 minutes. One reference email + a pre-loaded brand design system + a structured prompt = a finished, on-brand email you can preview as HTML. All inside Claude Design. Perfect for DTC brands and agencies who are still paying email agencies $3-5K/month to design flows that take 2 weeks to ship. If you're sitting on a welcome series, abandoned cart, and post-purchase flow that hasn't been touched in 6 months because the design lift is too painful... This workflow eliminates the entire bottleneck: → Build a design system in Claude Design once (brand colors, fonts, logo, button styling) → Upload a screenshot of any email you want to rebuild as your reference → Use Claude to write a structured prompt that maps every section top-to-bottom (promo bar, logo, headline, CTA, hero, body, table, footer) → Drop the reference image + the prompt into Claude Design at high fidelity → Iterate inline — swap the hero image, fix button styling, color-pick brand colors directly from the original No briefing a designer. No waiting 2 weeks for V1. No paying an agency $4K/month for 4 emails. What you get: → Win-back, welcome, abandoned cart, and post-purchase emails designed in under an hour each → A reusable brand design system that every new email pulls from automatically → Full inline editing — fonts, colors, buttons, images all editable in the canvas → HTML preview ready to hand off to your ESP Built 100% in with Claude Design. I put together a full playbook showing the design system setup, the exact structured prompt format, and the inline editing workflow. Want it for free? > Like this post > Comment "DESIGN" And I'll send it over (must be following so I can DM)
0:36

Claude Design is f*cking ridiculous 🤯 Claude Design now lets DTC brands and agencies rebuild any high-performing email — logo, hero, headline, CTA button, comparison table, brand colors — in 20 minutes. One reference email + a pre-loaded brand design system + a structured prompt = a finished, on-brand email you can preview as HTML. All inside Claude Design. Perfect for DTC brands and agencies who are still paying email agencies $3-5K/month to design flows that take 2 weeks to ship. If you're sitting on a welcome series, abandoned cart, and post-purchase flow that hasn't been touched in 6 months because the design lift is too painful... This workflow eliminates the entire bottleneck: → Build a design system in Claude Design once (brand colors, fonts, logo, button styling) → Upload a screenshot of any email you want to rebuild as your reference → Use Claude to write a structured prompt that maps every section top-to-bottom (promo bar, logo, headline, CTA, hero, body, table, footer) → Drop the reference image + the prompt into Claude Design at high fidelity → Iterate inline — swap the hero image, fix button styling, color-pick brand colors directly from the original No briefing a designer. No waiting 2 weeks for V1. No paying an agency $4K/month for 4 emails. What you get: → Win-back, welcome, abandoned cart, and post-purchase emails designed in under an hour each → A reusable brand design system that every new email pulls from automatically → Full inline editing — fonts, colors, buttons, images all editable in the canvas → HTML preview ready to hand off to your ESP Built 100% in with Claude Design. I put together a full playbook showing the design system setup, the exact structured prompt format, and the inline editing workflow. Want it for free? > Like this post > Comment "DESIGN" And I'll send it over (must be following so I can DM)

Mike Futia

31,732 views • 2 months ago

this guy built an ai-girl pipeline using real-time face filters, and d2c brands now pay him $2,000 per ugc video he got tired of watching brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs photoreal ai girls live from his own webcam, no actresses, no studios, no makeup artists his monthly revenue hit $89,000 last month from a network of 7 ai personas across tiktok and instagram. the average ugc creator caps at $6k juggling 4 brand deals the breakdown: > hardware is the moat, but most people butcher the setup in the first frame. face mesh locked at 60fps with zero artifacting > persona comes first, mess this up and nothing saves it: name, backstory, voice tone, niche before a single clip is shot > face selection is not random. you a/b test features (eye spacing, jawline, hair contrast) because some faces convert better in 9:16 > you're picking who your audience trusts, not who looks cool. that's targeting baked into bone structure > real-time physics run before the script, this is what kills the uncanny valley that destroys watch time in 2 seconds > the filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick > batching is the move 96% skip: one performance, multiple personas, three platforms > the system pushes 12 pieces before lunch while brands test 2 creators a week and wonder why their cpa sits at $94 the economics: each video costs $4 in compute, sells for $1,500 to $3,000, takes 14 minutes to produce. that's a 37,500% margin, while ugc agencies pay creators $400-800 per clip and net $200 after revisions one supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to la. they were paying $1,200 per ugc video and burning $6,000/week on content that didn't scale. now they spend $210 for 14 variants and their cpa dropped from $89 to $27 the avatars hold real products, warm window light on the persona, cold neon on the operator, mouth shapes sync to consonants not just vowels just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break
0:25

this guy built an ai-girl pipeline using real-time face filters, and d2c brands now pay him $2,000 per ugc video he got tired of watching brands burn $4,000 on a single creator who takes 2 weeks to deliver one angle, so he built a setup that runs photoreal ai girls live from his own webcam, no actresses, no studios, no makeup artists his monthly revenue hit $89,000 last month from a network of 7 ai personas across tiktok and instagram. the average ugc creator caps at $6k juggling 4 brand deals the breakdown: > hardware is the moat, but most people butcher the setup in the first frame. face mesh locked at 60fps with zero artifacting > persona comes first, mess this up and nothing saves it: name, backstory, voice tone, niche before a single clip is shot > face selection is not random. you a/b test features (eye spacing, jawline, hair contrast) because some faces convert better in 9:16 > you're picking who your audience trusts, not who looks cool. that's targeting baked into bone structure > real-time physics run before the script, this is what kills the uncanny valley that destroys watch time in 2 seconds > the filter has to survive the strap of a tank top, the texture of a knit cardigan, the hair flick > batching is the move 96% skip: one performance, multiple personas, three platforms > the system pushes 12 pieces before lunch while brands test 2 creators a week and wonder why their cpa sits at $94 the economics: each video costs $4 in compute, sells for $1,500 to $3,000, takes 14 minutes to produce. that's a 37,500% margin, while ugc agencies pay creators $400-800 per clip and net $200 after revisions one supplement brand generated 14 variants with 7 personas in 4 hours and found a winner in 36 hours without flying a creator to la. they were paying $1,200 per ugc video and burning $6,000/week on content that didn't scale. now they spend $210 for 14 variants and their cpa dropped from $89 to $27 the avatars hold real products, warm window light on the persona, cold neon on the operator, mouth shapes sync to consonants not just vowels just a webcam, a tracked face, and the discipline to move enough that the filter never has a chance to break

Kiyoro

31,137 views • 2 months ago

This Chinese guy created agents in Claude Code for landing pages and single-handedly serves 47 small businesses a month, taking $400 from each. He built a system of 7 agents on Claude Sonnet 4.6 that analyzes Google Maps in small towns, finds small businesses without websites there, and over 1 weekend takes each one to a finished mockup with video and cold message. No assistant, no sales team, no SDR. Just him, a MacBook, an iPhone, and 1 API key. And traditional web design agencies keep teams of 8 people on salary for the same order flow, while his expenses are only tokens and subscriptions to Lovable, Higgsfield, and Calendly. 7 agents work through 1 orchestrator on Claude Code Router. Usage is about 3 million tokens a day, the average API bill is about $480 a month. All 7 go through MCP servers and write shared state to the file system, without shared state in memory and without race conditions, and 1 of them lives right in the iPhone and picks up positive replies from the subway, a taxi, or on walks. And here is the system prompt he put into the orchestrator before launch: "You are the orchestrator of a solo agency that sells ready-made websites to local businesses. You delegate read-only tasks to 6 sub-agents and own all writes. sub-agents: // Scout (walks through Google Maps in selected cities, looks for narrow niches: 5+ years on the map, fewer than 50 reviews, no website or a website from 2014, but high ratings) // Diagnoser (for each lead writes a 50-word diagnosis, hero angle, tone matched to the industry, and a cold message under 70 words) // Builder (generates a landing page mockup in Lovable through MCP only for the top 5 leads per day, with the sharpest diagnoses and the biggest gap) // Filmer (pulls 5 screenshots of the mockup and through Higgsfield renders a 10-second vertical video 1080x1920 with a soft zoom) // Pitcher (sends a personalized cold message through the right channel for the niche: email to roofers, SMS to tradesmen, IG DM to salons, LinkedIn to realtors) // Checker (runs every message through evals for personalization, absence of AI markers and buzzwords before sending) // Mobile (lives in the iPhone, handles positive replies in real time, books Zoom calls in Calendly through MCP while the owner is on the go). You never let 2 sub-agents touch 1 lead. You stop and request approval from the human only when a deal exceeds $3,000 or the reply rate in a niche for the day drops below 12%." Meaning the system knows what it is and within what boundaries it is allowed to act. It knows it is supposed to find leads on its own. It knows it is supposed to take each one to a mockup, video, and cold message without intervention. It knows the human only steps in when a deal goes above $3,000 or the reply rate stops converging. → The system runs 24 hours a day → Scout goes through about 220 local businesses on Google Maps per day and leaves 30 new leads in the queue → Diagnoser outputs 30 structured diagnoses + briefs + cold messages per day → Builder assembles 3 to 5 finished landing pages in Lovable for the sharpest leads → Filmer renders a 10-second vertical video in Higgsfield for each one → Pitcher sends 30 personalized messages per day across 4 channels with a reply rate of about 14% → Checker runs every message through evals before sending And only when a deal breaks $3,000 or the reply rate for the day drops below 12% does the orchestrator wake the owner. And when the owner at that moment is sitting in the subway or a taxi, the Mobile agent in his iPhone picks up 1 move on its own: replies to a fresh positive reply from a dentist, books a Zoom through Calendly synced to the local time of the client, and puts the lead back in the queue. The owner only has to tap "approve" and in just 10 minutes join the call. Here is what the system writes in his log during 1 of the Saturdays: "scout report: 218 businesses checked in Austin, Denver, and Miami, 34 without a website, 19 with a website from 2014, 6 with an active redesign request in reviews. passing top 30 to diagnoser." "pitcher: 30 cold messages sent across 4 channels, 14 replies, 5 positive, 3 Zoom calls booked for Sunday. passing to closer." "builder: landing page for Westside Cosmetic Dentistry built in Lovable, 5 sections, mobile, soft beige. URL placed at /Users/dev/maps-agency/clients/westside/v1. filmer launching Higgsfield." "eval flag: deal with The Lotus Salon at $3,400 exceeds the approved limit of $3,000. sending for manual review." He has no server of his own and no separate backend. Just a local file sandbox at /Users/dev/maps-agency, an MCP router, 1 API key to Claude, and the same key forwarded to Claude Code on his iPhone. Out of everything I have seen this year, this is the cleanest one-person agency for selling websites to small businesses: $480 a month on the API, about $18,800 into the account, and between them 7 prompts, 1 file system, and 1 phone in the pocket.
2:02

This Chinese guy created agents in Claude Code for landing pages and single-handedly serves 47 small businesses a month, taking $400 from each. He built a system of 7 agents on Claude Sonnet 4.6 that analyzes Google Maps in small towns, finds small businesses without websites there, and over 1 weekend takes each one to a finished mockup with video and cold message. No assistant, no sales team, no SDR. Just him, a MacBook, an iPhone, and 1 API key. And traditional web design agencies keep teams of 8 people on salary for the same order flow, while his expenses are only tokens and subscriptions to Lovable, Higgsfield, and Calendly. 7 agents work through 1 orchestrator on Claude Code Router. Usage is about 3 million tokens a day, the average API bill is about $480 a month. All 7 go through MCP servers and write shared state to the file system, without shared state in memory and without race conditions, and 1 of them lives right in the iPhone and picks up positive replies from the subway, a taxi, or on walks. And here is the system prompt he put into the orchestrator before launch: "You are the orchestrator of a solo agency that sells ready-made websites to local businesses. You delegate read-only tasks to 6 sub-agents and own all writes. sub-agents: // Scout (walks through Google Maps in selected cities, looks for narrow niches: 5+ years on the map, fewer than 50 reviews, no website or a website from 2014, but high ratings) // Diagnoser (for each lead writes a 50-word diagnosis, hero angle, tone matched to the industry, and a cold message under 70 words) // Builder (generates a landing page mockup in Lovable through MCP only for the top 5 leads per day, with the sharpest diagnoses and the biggest gap) // Filmer (pulls 5 screenshots of the mockup and through Higgsfield renders a 10-second vertical video 1080x1920 with a soft zoom) // Pitcher (sends a personalized cold message through the right channel for the niche: email to roofers, SMS to tradesmen, IG DM to salons, LinkedIn to realtors) // Checker (runs every message through evals for personalization, absence of AI markers and buzzwords before sending) // Mobile (lives in the iPhone, handles positive replies in real time, books Zoom calls in Calendly through MCP while the owner is on the go). You never let 2 sub-agents touch 1 lead. You stop and request approval from the human only when a deal exceeds $3,000 or the reply rate in a niche for the day drops below 12%." Meaning the system knows what it is and within what boundaries it is allowed to act. It knows it is supposed to find leads on its own. It knows it is supposed to take each one to a mockup, video, and cold message without intervention. It knows the human only steps in when a deal goes above $3,000 or the reply rate stops converging. → The system runs 24 hours a day → Scout goes through about 220 local businesses on Google Maps per day and leaves 30 new leads in the queue → Diagnoser outputs 30 structured diagnoses + briefs + cold messages per day → Builder assembles 3 to 5 finished landing pages in Lovable for the sharpest leads → Filmer renders a 10-second vertical video in Higgsfield for each one → Pitcher sends 30 personalized messages per day across 4 channels with a reply rate of about 14% → Checker runs every message through evals before sending And only when a deal breaks $3,000 or the reply rate for the day drops below 12% does the orchestrator wake the owner. And when the owner at that moment is sitting in the subway or a taxi, the Mobile agent in his iPhone picks up 1 move on its own: replies to a fresh positive reply from a dentist, books a Zoom through Calendly synced to the local time of the client, and puts the lead back in the queue. The owner only has to tap "approve" and in just 10 minutes join the call. Here is what the system writes in his log during 1 of the Saturdays: "scout report: 218 businesses checked in Austin, Denver, and Miami, 34 without a website, 19 with a website from 2014, 6 with an active redesign request in reviews. passing top 30 to diagnoser." "pitcher: 30 cold messages sent across 4 channels, 14 replies, 5 positive, 3 Zoom calls booked for Sunday. passing to closer." "builder: landing page for Westside Cosmetic Dentistry built in Lovable, 5 sections, mobile, soft beige. URL placed at /Users/dev/maps-agency/clients/westside/v1. filmer launching Higgsfield." "eval flag: deal with The Lotus Salon at $3,400 exceeds the approved limit of $3,000. sending for manual review." He has no server of his own and no separate backend. Just a local file sandbox at /Users/dev/maps-agency, an MCP router, 1 API key to Claude, and the same key forwarded to Claude Code on his iPhone. Out of everything I have seen this year, this is the cleanest one-person agency for selling websites to small businesses: $480 a month on the API, about $18,800 into the account, and between them 7 prompts, 1 file system, and 1 phone in the pocket.

Blaze

2,709,869 views • 2 months ago

After years of being absolutely tortured by expensive ad creative pipelines, I think I finally found the ultimate savior for brand growth. Most AI video tools are great at generating flashy but random clips. The real challenge starts when you need to produce high-converting ecommerce content at scale without burning your budget. I’ve been testing Wizstar_official, and it honestly feels less like a simple AI generator and more like serious production infrastructure for scaling digital businesses. What stood out to me is how their ecosystem completely automates the two biggest bottlenecks in growth marketing: Bulk Testing and Creative Adaptation. First, their Agent setup paired with Fast Mode is a cheat code for volume. Instead of spending days scripting and storyboarding, the system intelligently extracts your product selling points, writes algorithm-friendly influencer scripts, and batch-produces massive ad variations in one day. It’s ultra-low-cost, built for rapid listing, and keeps your brand logos and product textures 100% consistent and lossless across the board. Second, the Video Reference workflow is an absolute game-changer. Instead of rebuilding every ad from scratch or guessing what works, you can reference any existing successful e-commerce video. The AI reverse-engineers its exact pacing, structure, camera movement, and storytelling style, and applies that winning DNA to a completely different product. That completely changes the production workflow from: prompt → random output into something closer to: reference → structured production → scalable content system Under the hood, Wizstar doesn't just rely on one platform; it supports flexible multi-model orchestration. Driven by their newly integrated Seedance 2.0 engine, it allows direct face input, meaning your character consistency and scene continuity stay rock-solid with absolutely none of that creepy AI face warping across complex cuts. If you are running global campaigns, you can also utilize their Video Translation tool to flip master clips into 12 languages with flawless, natural lip sync in minutes. ✨ New users get free credits upon registration 💸 First month subscription is only $19 (includes a complimentary 30-second E-commerce Agent experience to test features like Product to Video) Stop letting slow pipelines bottleneck your global growth. Try it here: #Wizstar #GrowthMarketing #AIVideo
0:40

After years of being absolutely tortured by expensive ad creative pipelines, I think I finally found the ultimate savior for brand growth. Most AI video tools are great at generating flashy but random clips. The real challenge starts when you need to produce high-converting ecommerce content at scale without burning your budget. I’ve been testing Wizstar_official, and it honestly feels less like a simple AI generator and more like serious production infrastructure for scaling digital businesses. What stood out to me is how their ecosystem completely automates the two biggest bottlenecks in growth marketing: Bulk Testing and Creative Adaptation. First, their Agent setup paired with Fast Mode is a cheat code for volume. Instead of spending days scripting and storyboarding, the system intelligently extracts your product selling points, writes algorithm-friendly influencer scripts, and batch-produces massive ad variations in one day. It’s ultra-low-cost, built for rapid listing, and keeps your brand logos and product textures 100% consistent and lossless across the board. Second, the Video Reference workflow is an absolute game-changer. Instead of rebuilding every ad from scratch or guessing what works, you can reference any existing successful e-commerce video. The AI reverse-engineers its exact pacing, structure, camera movement, and storytelling style, and applies that winning DNA to a completely different product. That completely changes the production workflow from: prompt → random output into something closer to: reference → structured production → scalable content system Under the hood, Wizstar doesn't just rely on one platform; it supports flexible multi-model orchestration. Driven by their newly integrated Seedance 2.0 engine, it allows direct face input, meaning your character consistency and scene continuity stay rock-solid with absolutely none of that creepy AI face warping across complex cuts. If you are running global campaigns, you can also utilize their Video Translation tool to flip master clips into 12 languages with flawless, natural lip sync in minutes. ✨ New users get free credits upon registration 💸 First month subscription is only $19 (includes a complimentary 30-second E-commerce Agent experience to test features like Product to Video) Stop letting slow pipelines bottleneck your global growth. Try it here: #Wizstar #GrowthMarketing #AIVideo

FELIX

97,682 views • 2 months ago

Hermes + Claude + Higgsfield MCP + ViralBuilder = 💰💰💰 Four tools. One prompt chain. Hook to finished video in 10 minutes. I built a Claude skill that writes shot-by-shot Higgsfield prompts from a single creative brief. ViralBuilder tells you what's winning. The skill turns it into a production-ready prompt. Higgsfield renders it. No creative director. No guessing. No separate tools. Here is the setup: Higgsfield MCP → Open Claude Code → Settings → Connectors → Enter: → Connect your account Hermes → The agent layer running underneath Claude Code → It holds your skills, crons, memory, and routing rules → When you prompt Claude, Hermes feeds it the context it needs ViralBuilder (like Gethookd) → The winning ecom video database → Scrapes top performing ecom videos across platforms → Claude reads the data and extracts what styles, hooks, and formats are actually scaling The skill: video-prompt-builder → Installed inside Claude via Hermes → Takes a creative brief and outputs a full shot-by-shot prompt → Covers camera work, effects, transitions, pacing, and energy arc → Every output is structured for Higgsfield to render without ambiguity No switching apps. No export steps. Everything runs from one place. ▸ FIND WINNING CREATIVE ANGLES ViralBuilder tells you what the market already validated. Claude reads it and extracts the pattern. Prompts to run: "Search ViralBuilder for the top performing ecom videos in [niche] over the last 21 days. Extract the 3 dominant hook styles and rank by view velocity." "Pull the winning video formats in [niche] from ViralBuilder. Which opening 3 seconds appears most across videos spending over $10k?" "Find what video style is scaling right now in [niche] for the US market. UGC, talking head, or product demo. Filter for videos with over 1M views." "Pull the last 30 days of viral ecom hooks in [niche] from ViralBuilder. Cluster by emotional trigger. Which cluster has the most longevity?" You are not guessing at angles. You are reading what the market already spent money validating. ▸ BUILD THE PROMPT WITH THE SKILL This is where the video-prompt-builder skill takes over. You give Claude the winning angle. The skill outputs a complete shot-by-shot prompt with effects, transitions, pacing, and energy arc ready to fire into Higgsfield. Prompts to run: "Use the video-prompt-builder skill. Brief: 15-second UGC ad for [product] in [niche]. Hook style: [style from ViralBuilder]. Tone: direct to camera, US English. Output the full shot-by-shot effects timeline, effects inventory, density map, and energy arc." "Use the video-prompt-builder skill. The dominant hook in [niche] this week is [hook]. Build a 10-second product video prompt that opens with a speed ramp into a close-up product reveal. Include a signature visual effect and a low-density CTA landing." "Use the video-prompt-builder skill. Brief: replicate the pacing and energy of a [style description] video for [product]. Target duration: 20 seconds. Output all four sections. Then generate the video with Higgsfield using the shot-by-shot prompt." The skill outputs four sections every time: → Shot-by-shot effects timeline with camera, movement, and transitions per shot → Master effects inventory showing every technique used and where → Effects density map showing high, medium, and low intensity across the timeline → Energy arc describing how the video opens, builds, and lands That output goes directly into Higgsfield. No rewriting. No translating. ▸ GENERATE THE CREATIVE Claude writes the brief via the skill. Higgsfield MCP builds the video. Both happen in the same session. Prompts to run: "Use the video-prompt-builder skill to write a 15-second UGC prompt for [product]. Hook in the first 3 seconds, speed ramp into product reveal, slow-motion CTA landing. Then generate with Higgsfield in 9:16 format." "Build 3 prompt variations on this winning angle: [angle]. Each variation opens with a different effect — speed ramp, digital zoom, whip pan. Use the video-prompt-builder skill for each. Then generate all three with Higgsfield." "Use the video-prompt-builder skill. Brief: problem-solution ad for [product], 20 seconds, US market. Problem shot at high density, product reveal at medium, result and CTA at low. Generate with Higgsfield in 9:16." No separate tool. No file transfer. The video comes back in the same thread. ▸ CHAIN THE WHOLE STACK One prompt. All four tools firing together. "You are my ad creative director. Hermes has loaded my brand context. Pull the top performing video style in [niche] from ViralBuilder this week. Use the video-prompt-builder skill to write a full shot-by-shot prompt for [product] that replicates that style — 20 seconds, 9:16, US market, hook in the first 3 seconds. Output the effects timeline, inventory, density map, and energy arc. Then generate the video with Higgsfield." That single prompt replaces a half-day of production. The math before this stack: Brief: 30 minutes Script: 1 hour Creative production: 2 to 3 hours Agency or freelancer cost: $500 to $2,000 per creative With this stack: Hook to finished creative: 10 minutes Cost per creative: tool subscription, a fraction of agency rate 5 product tests in the time it used to take to brief one Bad product tests are where US ad budget disappears. $600 to $1,500 per failed test, before you even know if the angle works. This stack shows you what the market already validated before you spend a dollar on production. Hermes = your context layer. Brand, goals, past performance. Claude is always informed. ViralBuilder = your winning video database. See exactly what styles, hooks, and formats are scaling before you produce anything. video-prompt-builder skill = the translation layer. Turns a creative brief into a structured, production-ready Higgsfield prompt every time. Claude = the brain. Reads the market, writes the brief, chains the tools. Higgsfield MCP = the output. Video generated directly from the prompt. No export step. Four tools. One session. 10 minutes. Comment + RT "STACK" and I'll DM you the full workflow + the video-prompt-builder skill file.
0:26

Hermes + Claude + Higgsfield MCP + ViralBuilder = 💰💰💰 Four tools. One prompt chain. Hook to finished video in 10 minutes. I built a Claude skill that writes shot-by-shot Higgsfield prompts from a single creative brief. ViralBuilder tells you what's winning. The skill turns it into a production-ready prompt. Higgsfield renders it. No creative director. No guessing. No separate tools. Here is the setup: Higgsfield MCP → Open Claude Code → Settings → Connectors → Enter: → Connect your account Hermes → The agent layer running underneath Claude Code → It holds your skills, crons, memory, and routing rules → When you prompt Claude, Hermes feeds it the context it needs ViralBuilder (like Gethookd) → The winning ecom video database → Scrapes top performing ecom videos across platforms → Claude reads the data and extracts what styles, hooks, and formats are actually scaling The skill: video-prompt-builder → Installed inside Claude via Hermes → Takes a creative brief and outputs a full shot-by-shot prompt → Covers camera work, effects, transitions, pacing, and energy arc → Every output is structured for Higgsfield to render without ambiguity No switching apps. No export steps. Everything runs from one place. ▸ FIND WINNING CREATIVE ANGLES ViralBuilder tells you what the market already validated. Claude reads it and extracts the pattern. Prompts to run: "Search ViralBuilder for the top performing ecom videos in [niche] over the last 21 days. Extract the 3 dominant hook styles and rank by view velocity." "Pull the winning video formats in [niche] from ViralBuilder. Which opening 3 seconds appears most across videos spending over $10k?" "Find what video style is scaling right now in [niche] for the US market. UGC, talking head, or product demo. Filter for videos with over 1M views." "Pull the last 30 days of viral ecom hooks in [niche] from ViralBuilder. Cluster by emotional trigger. Which cluster has the most longevity?" You are not guessing at angles. You are reading what the market already spent money validating. ▸ BUILD THE PROMPT WITH THE SKILL This is where the video-prompt-builder skill takes over. You give Claude the winning angle. The skill outputs a complete shot-by-shot prompt with effects, transitions, pacing, and energy arc ready to fire into Higgsfield. Prompts to run: "Use the video-prompt-builder skill. Brief: 15-second UGC ad for [product] in [niche]. Hook style: [style from ViralBuilder]. Tone: direct to camera, US English. Output the full shot-by-shot effects timeline, effects inventory, density map, and energy arc." "Use the video-prompt-builder skill. The dominant hook in [niche] this week is [hook]. Build a 10-second product video prompt that opens with a speed ramp into a close-up product reveal. Include a signature visual effect and a low-density CTA landing." "Use the video-prompt-builder skill. Brief: replicate the pacing and energy of a [style description] video for [product]. Target duration: 20 seconds. Output all four sections. Then generate the video with Higgsfield using the shot-by-shot prompt." The skill outputs four sections every time: → Shot-by-shot effects timeline with camera, movement, and transitions per shot → Master effects inventory showing every technique used and where → Effects density map showing high, medium, and low intensity across the timeline → Energy arc describing how the video opens, builds, and lands That output goes directly into Higgsfield. No rewriting. No translating. ▸ GENERATE THE CREATIVE Claude writes the brief via the skill. Higgsfield MCP builds the video. Both happen in the same session. Prompts to run: "Use the video-prompt-builder skill to write a 15-second UGC prompt for [product]. Hook in the first 3 seconds, speed ramp into product reveal, slow-motion CTA landing. Then generate with Higgsfield in 9:16 format." "Build 3 prompt variations on this winning angle: [angle]. Each variation opens with a different effect — speed ramp, digital zoom, whip pan. Use the video-prompt-builder skill for each. Then generate all three with Higgsfield." "Use the video-prompt-builder skill. Brief: problem-solution ad for [product], 20 seconds, US market. Problem shot at high density, product reveal at medium, result and CTA at low. Generate with Higgsfield in 9:16." No separate tool. No file transfer. The video comes back in the same thread. ▸ CHAIN THE WHOLE STACK One prompt. All four tools firing together. "You are my ad creative director. Hermes has loaded my brand context. Pull the top performing video style in [niche] from ViralBuilder this week. Use the video-prompt-builder skill to write a full shot-by-shot prompt for [product] that replicates that style — 20 seconds, 9:16, US market, hook in the first 3 seconds. Output the effects timeline, inventory, density map, and energy arc. Then generate the video with Higgsfield." That single prompt replaces a half-day of production. The math before this stack: Brief: 30 minutes Script: 1 hour Creative production: 2 to 3 hours Agency or freelancer cost: $500 to $2,000 per creative With this stack: Hook to finished creative: 10 minutes Cost per creative: tool subscription, a fraction of agency rate 5 product tests in the time it used to take to brief one Bad product tests are where US ad budget disappears. $600 to $1,500 per failed test, before you even know if the angle works. This stack shows you what the market already validated before you spend a dollar on production. Hermes = your context layer. Brand, goals, past performance. Claude is always informed. ViralBuilder = your winning video database. See exactly what styles, hooks, and formats are scaling before you produce anything. video-prompt-builder skill = the translation layer. Turns a creative brief into a structured, production-ready Higgsfield prompt every time. Claude = the brain. Reads the market, writes the brief, chains the tools. Higgsfield MCP = the output. Video generated directly from the prompt. No export step. Four tools. One session. 10 minutes. Comment + RT "STACK" and I'll DM you the full workflow + the video-prompt-builder skill file.

Kid Pak

57,123 views • 2 months ago