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Chris

@everestchris6 • 25,745 subscribers

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claude opus 5.5 completely solved three.js it took a floor plan and turned it into a 3d house you can walk through home builders pay $5k to $10k per floor plan for this, so buyers can tour a home before it's built and change things if needed here's how to automate client acquisition: > scrape builder sites for plans with no model home > give the plan and their photos to opus 5.5 > it builds the house to scale as a walkable site > send the builder their own plan before you pitch > charge per plan to do the rest of their catalog > rerun it on every new plan they launch give this prompt to your agent to get started: "here's a floor plan and photos for one house. build it as a three.js site i can walk through in the browser, to scale from the plan, with every room, finish and piece of furniture matched to the photos. the bar is the photos themselves. split the house into pieces you can judge separately, and give each one a builder and a separate critic with fresh context. the critic compares a screenshot of our room with the matching photo, picks the better one, names the biggest gap, and sends it back. keep looping until ours wins or i stop you, and tell me anything you couldn't match."

claude opus 5.5 completely solved three.js it took a floor plan and turned it into a 3d house you can walk through home builders pay $5k to $10k per floor plan for this, so buyers can tour a home before it's built and change things if needed here's how to automate client acquisition: > scrape builder sites for plans with no model home > give the plan and their photos to opus 5.5 > it builds the house to scale as a walkable site > send the builder their own plan before you pitch > charge per plan to do the rest of their catalog > rerun it on every new plan they launch give this prompt to your agent to get started: "here's a floor plan and photos for one house. build it as a three.js site i can walk through in the browser, to scale from the plan, with every room, finish and piece of furniture matched to the photos. the bar is the photos themselves. split the house into pieces you can judge separately, and give each one a builder and a separate critic with fresh context. the critic compares a screenshot of our room with the matching photo, picks the better one, names the biggest gap, and sends it back. keep looping until ours wins or i stop you, and tell me anything you couldn't match."

310,817 次观看

this is the only prompt you need to one-shot a viral ai influencer ------------------------------ you build ai influencers that go viral by putting a character people can't forget into a real clip people already know. you find the clip, design the character, render the remake and hand me a post that's ready to go. you measure before you spend and you never post anything yourself. - character: [path to a reference sheet, or "invent one" plus any steer on age, vibe or look] - niche: [where the clips come from, like hip-hop, sports, nightlife or hustle culture] - caption language: [language] - lane: [fresh, evergreen or both] - render: [kling 3.0 omni or seedance 2.5, plus the most i'll spend per video] - length: [10, 20 or 30 seconds] - no-go list: [people, topics or brands to avoid] if any of this is empty, ask me everything in one message, read the plan back with a cost estimate, then keep going until the post package is ready. - apify for instagram, x and tiktok scraping, replicate for every image and video model, yt-dlp for downloads, ffmpeg for trimming, frames, contact sheets and audio - keep every api key in environment variables and never write a key into any file - save everything into one run folder so i can see each step - the original clip carries the recognition and the motion, and the character carries the joke - the joke is status contrast. the absurd character takes the place of the coolest person in the clip and inherits their swagger - every remake that blew up came from a single continuous phone take with no hard cuts and one person holding the frame. treat that as a rule - one signature feature you can read at phone size from across a room, like a hair shape, a beard, sideburns or eyebrows. never a mask or a costume - strange face, immaculately dressed, one loud wardrobe colour that stands out in a dark club and on a grey street - normal body proportions, empty hands, face uncovered, because swap models break on capes, props and masks - never copy a look that's already viral - a short name people can repeat and a one-word catchphrase in the character's own language - the comedy comes from hair, face and clothes, never from ethnicity, disability or body shaming - render a reference sheet with gpt image 2.5 on a light grey studio backdrop: four full-body views on top (front, three-quarter, side, back) and four close-ups below (deadpan, laughing, shouting with a hand up, side profile of the signature feature) - it has to look like a real person photographed with a camera. if the feature drifts between panels or anything looks cgi, render it again fresh lane: - clips only stay remakeable for about a week, so this runs daily - scrape the last 4 days from big repost pages in the niche like worldstar, pubity, daquan, rap, complex, houseofhighlights and overtime - grow the page list from every "via @" and "🎥: @" credit and every tagged account, and keep any repost page over 100k followers - search x for native videos in the niche with high likes from the last 3 days, for cross-platform proof evergreen lane: - scrape the top posts of the ai influencers already going viral and work out which original clip each hit remakes. a clip that already worked as a remake for one character will work again with another - search for the most quoted clips in the niche (famous interviews, walk-outs, freestyles, flexes, dance moments) and pull them from youtube - an old clip that shows up again in this week's fresh scrape gets a bonus - prefer real phone or interview footage over film and tv, which gets claimed and muted - fresh: plays against that page's usual plays, plays per hour since posting, and whether the same clip or its audio is spreading across pages and platforms - evergreen: total plays across every copy you found, whether another ai influencer already remade it and beat their usual numbers, and whether it's resurfacing this week - drop anything older than 7 days in the fresh lane, because pinned posts leak into scrapes - expect sports broadcasts and press conferences to top the numbers, which is why the gate below decides - download the top 15 from each lane - count hard cuts with ffmpeg scene detection, and pass at 0 or 1 in the part you'll use - make an 8 frame contact sheet and look at it. pass only if one person is on screen most of the time with their face and upper body visible, it's real footage (not a broadcast, a stream overlay or a multi-camera edit), and that person is doing something and is the coolest one in the clip - if captions, tweet cards or frames are burned in over the person, trace the clean original through the caption credit and use that - reject anything with a minor as the subject, a private person being humiliated, injury, violence, crime, tragedy, politics, or anything on my no-go list - show me the top 3 with a frame strip, the scores, who gets replaced, the one-line joke and the cost for each render option, and let me pick both options take the real clip and the reference sheet with one prompt: "replace [person described by position and clothing] with the man in the image. keep his exact motion, gestures, mouth movement and timing. keep every other person, object, the location, camera shake, framing and lighting the same. no text." kling 3.0 omni (cheaper, about $0.28 a second): - video editing mode, with the clip as the base video and the sheet as the reference image, original sound kept - each piece has to be under 10.0 seconds, at least 720 pixels on every side, with square pixels, so re-encode first - for anything longer, split into pieces under 9.5 seconds at calm moments where the person is clearly visible, and render every piece with the exact same sheet and prompt - compare the last frame of each piece with the first frame of the next, and re-render any piece where the face, hair or outfit jumps - join the pieces with no audio, then lay the original audio back over the whole thing as one track seedance 2.5 (premium, about $0.97 a second with a video input): - up to 30 seconds in one pass with no seams and the best consistency - editing mode with the clip as the reference video and the sheet as the reference image, then lay the original audio back on never use kling motion control for this, because it rebuilds the whole scene from its image and rejects crowded clips. never use gemini omni edit mode either, because it blocks any video with a real person in it - make a contact sheet of the finished video and look at every frame - re-render once if the signature feature morphs, anyone except the target changes, text appears that wasn't there, or hands melt at a key moment - never do more than 2 render attempts without asking me - caption in my language, deadpan, in character, under 6 words, never explaining the joke - tag the person replaced and the original creator, because that's how the original artist ends up seeing it - turn on instagram's ai label for the post and the profile, since unlabelled ai accounts lose reach - fresh clips go out while the original is still inside its week, and evergreen clips go out at the account's best hour - first comment from the account is "follow for more" or the catchphrase - never launch or promote a token, and never imply the original person endorsed the character - log every post with the lane, scores, render option, cost, and plays at 24 and 72 hours - the next time you run, scrape the account first and fill those columns in - after 10 posts, compare plays against each score and each lane, shift the weighting toward whatever actually predicted views, and write down what changed - only put numbers on screen or in captions that you scraped or measured - mark anything you guessed rather than measured - if no clip passes the gate today, say so instead of forcing a weak one - the final mp4 at the source resolution, with the original audio - the reference sheet - a short note on why this clip won and why the runners-up lost - the caption, tags and posting time - total spend, and anything a human should still check ```

this is the only prompt you need to one-shot a viral ai influencer ------------------------------ you build ai influencers that go viral by putting a character people can't forget into a real clip people already know. you find the clip, design the character, render the remake and hand me a post that's ready to go. you measure before you spend and you never post anything yourself. - character: [path to a reference sheet, or "invent one" plus any steer on age, vibe or look] - niche: [where the clips come from, like hip-hop, sports, nightlife or hustle culture] - caption language: [language] - lane: [fresh, evergreen or both] - render: [kling 3.0 omni or seedance 2.5, plus the most i'll spend per video] - length: [10, 20 or 30 seconds] - no-go list: [people, topics or brands to avoid] if any of this is empty, ask me everything in one message, read the plan back with a cost estimate, then keep going until the post package is ready. - apify for instagram, x and tiktok scraping, replicate for every image and video model, yt-dlp for downloads, ffmpeg for trimming, frames, contact sheets and audio - keep every api key in environment variables and never write a key into any file - save everything into one run folder so i can see each step - the original clip carries the recognition and the motion, and the character carries the joke - the joke is status contrast. the absurd character takes the place of the coolest person in the clip and inherits their swagger - every remake that blew up came from a single continuous phone take with no hard cuts and one person holding the frame. treat that as a rule - one signature feature you can read at phone size from across a room, like a hair shape, a beard, sideburns or eyebrows. never a mask or a costume - strange face, immaculately dressed, one loud wardrobe colour that stands out in a dark club and on a grey street - normal body proportions, empty hands, face uncovered, because swap models break on capes, props and masks - never copy a look that's already viral - a short name people can repeat and a one-word catchphrase in the character's own language - the comedy comes from hair, face and clothes, never from ethnicity, disability or body shaming - render a reference sheet with gpt image 2.5 on a light grey studio backdrop: four full-body views on top (front, three-quarter, side, back) and four close-ups below (deadpan, laughing, shouting with a hand up, side profile of the signature feature) - it has to look like a real person photographed with a camera. if the feature drifts between panels or anything looks cgi, render it again fresh lane: - clips only stay remakeable for about a week, so this runs daily - scrape the last 4 days from big repost pages in the niche like worldstar, pubity, daquan, rap, complex, houseofhighlights and overtime - grow the page list from every "via @" and "🎥: @" credit and every tagged account, and keep any repost page over 100k followers - search x for native videos in the niche with high likes from the last 3 days, for cross-platform proof evergreen lane: - scrape the top posts of the ai influencers already going viral and work out which original clip each hit remakes. a clip that already worked as a remake for one character will work again with another - search for the most quoted clips in the niche (famous interviews, walk-outs, freestyles, flexes, dance moments) and pull them from youtube - an old clip that shows up again in this week's fresh scrape gets a bonus - prefer real phone or interview footage over film and tv, which gets claimed and muted - fresh: plays against that page's usual plays, plays per hour since posting, and whether the same clip or its audio is spreading across pages and platforms - evergreen: total plays across every copy you found, whether another ai influencer already remade it and beat their usual numbers, and whether it's resurfacing this week - drop anything older than 7 days in the fresh lane, because pinned posts leak into scrapes - expect sports broadcasts and press conferences to top the numbers, which is why the gate below decides - download the top 15 from each lane - count hard cuts with ffmpeg scene detection, and pass at 0 or 1 in the part you'll use - make an 8 frame contact sheet and look at it. pass only if one person is on screen most of the time with their face and upper body visible, it's real footage (not a broadcast, a stream overlay or a multi-camera edit), and that person is doing something and is the coolest one in the clip - if captions, tweet cards or frames are burned in over the person, trace the clean original through the caption credit and use that - reject anything with a minor as the subject, a private person being humiliated, injury, violence, crime, tragedy, politics, or anything on my no-go list - show me the top 3 with a frame strip, the scores, who gets replaced, the one-line joke and the cost for each render option, and let me pick both options take the real clip and the reference sheet with one prompt: "replace [person described by position and clothing] with the man in the image. keep his exact motion, gestures, mouth movement and timing. keep every other person, object, the location, camera shake, framing and lighting the same. no text." kling 3.0 omni (cheaper, about $0.28 a second): - video editing mode, with the clip as the base video and the sheet as the reference image, original sound kept - each piece has to be under 10.0 seconds, at least 720 pixels on every side, with square pixels, so re-encode first - for anything longer, split into pieces under 9.5 seconds at calm moments where the person is clearly visible, and render every piece with the exact same sheet and prompt - compare the last frame of each piece with the first frame of the next, and re-render any piece where the face, hair or outfit jumps - join the pieces with no audio, then lay the original audio back over the whole thing as one track seedance 2.5 (premium, about $0.97 a second with a video input): - up to 30 seconds in one pass with no seams and the best consistency - editing mode with the clip as the reference video and the sheet as the reference image, then lay the original audio back on never use kling motion control for this, because it rebuilds the whole scene from its image and rejects crowded clips. never use gemini omni edit mode either, because it blocks any video with a real person in it - make a contact sheet of the finished video and look at every frame - re-render once if the signature feature morphs, anyone except the target changes, text appears that wasn't there, or hands melt at a key moment - never do more than 2 render attempts without asking me - caption in my language, deadpan, in character, under 6 words, never explaining the joke - tag the person replaced and the original creator, because that's how the original artist ends up seeing it - turn on instagram's ai label for the post and the profile, since unlabelled ai accounts lose reach - fresh clips go out while the original is still inside its week, and evergreen clips go out at the account's best hour - first comment from the account is "follow for more" or the catchphrase - never launch or promote a token, and never imply the original person endorsed the character - log every post with the lane, scores, render option, cost, and plays at 24 and 72 hours - the next time you run, scrape the account first and fill those columns in - after 10 posts, compare plays against each score and each lane, shift the weighting toward whatever actually predicted views, and write down what changed - only put numbers on screen or in captions that you scraped or measured - mark anything you guessed rather than measured - if no clip passes the gate today, say so instead of forcing a weak one - the final mp4 at the source resolution, with the original audio - the reference sheet - a short note on why this clip won and why the runners-up lost - the caption, tags and posting time - total spend, and anything a human should still check ```

119,910 次观看

claude fable 5 can scrape thousands of sold homes and finds the patios with zero shade in 100°+ heat. then it mails the owner a postcard with the fix rendered into their own backyard here's the system you can sell to contractors: - scrapes every home sold in the metro in the last 12 months (recent buyers spend the most) - vision-reads the listing photos, skips the 64% with cover already - measures the sun on each patio, hour by hour, off google's satellite data - renders a louvered pergola into the owner's actual backyard photo - prints the diagnosis on the postcard: "your patio takes 11 hours of direct sun a day. saturday it hits 97°." - QR opens a heat report for their exact address with a booking link every install is $6.5k to $18k, one close covers months of retainers and homes sell every single day. reply "SYSTEM" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

claude fable 5 can scrape thousands of sold homes and finds the patios with zero shade in 100°+ heat. then it mails the owner a postcard with the fix rendered into their own backyard here's the system you can sell to contractors: - scrapes every home sold in the metro in the last 12 months (recent buyers spend the most) - vision-reads the listing photos, skips the 64% with cover already - measures the sun on each patio, hour by hour, off google's satellite data - renders a louvered pergola into the owner's actual backyard photo - prints the diagnosis on the postcard: "your patio takes 11 hours of direct sun a day. saturday it hits 97°." - QR opens a heat report for their exact address with a booking link every install is $6.5k to $18k, one close covers months of retainers and homes sell every single day. reply "SYSTEM" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

819,010 次观看

My OpenClaw bot runs 6 AI agents 24/7: - Finds local businesses without a website - Builds a custom demo site for them automatically - Sends outreach with the preview + payment link - Handles objections and closes the sale Most local businesses don't have a website, this system finds them, pitches them, and collects payment automatically Reply "OpenClaw" and I'll send you early access (must be following)

My OpenClaw bot runs 6 AI agents 24/7: - Finds local businesses without a website - Builds a custom demo site for them automatically - Sends outreach with the preview + payment link - Handles objections and closes the sale Most local businesses don't have a website, this system finds them, pitches them, and collects payment automatically Reply "OpenClaw" and I'll send you early access (must be following)

1,170,513 次观看

i built a free library of 70+ video components you can use in your videos agentic video editing is getting so good you can basically one shot a high quality video now they're all code btw, so your agent can customize every part of the component to fit your video you can access it here for completely free:

i built a free library of 70+ video components you can use in your videos agentic video editing is getting so good you can basically one shot a high quality video now they're all code btw, so your agent can customize every part of the component to fit your video you can access it here for completely free:

17,499 次观看

grok bot + hermes can generate unlimited leads on autopilot now - reads 3 months of what buyers actually say - turns that data into ads in their own words - runs them through whop ads, funded by sales - finds who needs the trade and renders the fix - reaches them by email, sms or post daily - builds a dashboard where you track all of it works if you sell a product, own a business, or want to sell leads to businesses that do just wrote a full guide on how you can set this up:

grok bot + hermes can generate unlimited leads on autopilot now - reads 3 months of what buyers actually say - turns that data into ads in their own words - runs them through whop ads, funded by sales - finds who needs the trade and renders the fix - reaches them by email, sms or post daily - builds a dashboard where you track all of it works if you sell a product, own a business, or want to sell leads to businesses that do just wrote a full guide on how you can set this up:

141,328 次观看

this OpenClaw bot finds warehouses with old roofs, renders solar panels on their actual building, and books the owner a call, all on autopilot... here's how commercial roofers can close $2M+ deals before the solar tax break ends: - scans thousands of commercial roofs via satellite - scores each building by roof age & urgency - pulls exact panel count from Google Solar API - finds the real owner (not the property manager) - calculates their federal credit to the dollar - renders a video of panels materializing on their roof - ships a personalized proposal - fully automated end to end every day that passes is money off the table. reply "ROOF" + RT and i'll send you the full breakdown so you can build this too (must be following so i can DM)

this OpenClaw bot finds warehouses with old roofs, renders solar panels on their actual building, and books the owner a call, all on autopilot... here's how commercial roofers can close $2M+ deals before the solar tax break ends: - scans thousands of commercial roofs via satellite - scores each building by roof age & urgency - pulls exact panel count from Google Solar API - finds the real owner (not the property manager) - calculates their federal credit to the dollar - renders a video of panels materializing on their roof - ships a personalized proposal - fully automated end to end every day that passes is money off the table. reply "ROOF" + RT and i'll send you the full breakdown so you can build this too (must be following so i can DM)

575,699 次观看

here's how to make money with jev on autopilot it's a super fast decision model, so it picks an answer in a fifth of a second and tells you how sure it is - put instant pricing on a business that has none - sell the same thing to bigger businesses for more - sell a file that decides what an agent may do - charge monthly to keep all of it running - costs a fraction of a cent per decision - runs on hermes or grok bot, on a schedule just wrote a whole guide on how you can set this up:

here's how to make money with jev on autopilot it's a super fast decision model, so it picks an answer in a fifth of a second and tells you how sure it is - put instant pricing on a business that has none - sell the same thing to bigger businesses for more - sell a file that decides what an agent may do - charge monthly to keep all of it running - costs a fraction of a cent per decision - runs on hermes or grok bot, on a schedule just wrote a whole guide on how you can set this up:

90,674 次观看

this OpenClaw bot finds restaurants with ugly menus, rebuilds them as live web menus, and mails the owner a postcard...on autopilot. here's how agencies can land recurring contracts with this system: - scrapes every restaurant in a city in real time - filters by review count + rating + last menu update + photo quality - pulls the real menu items from the official site, PDF, or Google reviews - samples the brand palette from the restaurant's own visual identity - renders a 9:16 brand-matched menu, hosted live at a QR-accessible URL - writes a personalized postcard referencing a real reviewer and a real dish - mails it to the registered office addressed to the owner by first name every step from discovery to brand-matching to outreach is automated. reply "MENU" + RT and i'll send you a free guide so you can build this too

this OpenClaw bot finds restaurants with ugly menus, rebuilds them as live web menus, and mails the owner a postcard...on autopilot. here's how agencies can land recurring contracts with this system: - scrapes every restaurant in a city in real time - filters by review count + rating + last menu update + photo quality - pulls the real menu items from the official site, PDF, or Google reviews - samples the brand palette from the restaurant's own visual identity - renders a 9:16 brand-matched menu, hosted live at a QR-accessible URL - writes a personalized postcard referencing a real reviewer and a real dish - mails it to the registered office addressed to the owner by first name every step from discovery to brand-matching to outreach is automated. reply "MENU" + RT and i'll send you a free guide so you can build this too

456,767 次观看

kimi k3 + hermes finds local businesses with ugly or zero websites, builds them a real one and sends the owner a loom-style video of it i sold my first website on literally my first dm, just off a loom video the system you can run as a one-person agency: - it scrapes one niche off google maps and flags everyone without a site - it keeps only rated, reviewed, still-alive businesses - pulls the owner's name from review replies - kimi k3 writes each site from their real reviews, nothing invented - a face-cam walkthrough plays over the new site - the owner clicks, sees their business look professional, claims the site every step from sourcing to outreach is fully automated reply "SITE" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

kimi k3 + hermes finds local businesses with ugly or zero websites, builds them a real one and sends the owner a loom-style video of it i sold my first website on literally my first dm, just off a loom video the system you can run as a one-person agency: - it scrapes one niche off google maps and flags everyone without a site - it keeps only rated, reviewed, still-alive businesses - pulls the owner's name from review replies - kimi k3 writes each site from their real reviews, nothing invented - a face-cam walkthrough plays over the new site - the owner clicks, sees their business look professional, claims the site every step from sourcing to outreach is fully automated reply "SITE" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

144,787 次观看

this OpenClaw bot finds restaurants with ugly food photos, redrafts them as IG posts, and mails the owner a postcard...on autopilot. here's how social-media agencies can use this system and land clients: - scrapes every restaurant in a city in real time - filters by review count + rating + last post date + photo quality - pulls the strongest food photo from Google Maps reviews - samples the brand palette from the restaurant's own visual identity - AI-redrafts the photo into a 9:16 brand-matched Instagram post - writes a postcard quoting a real reviewer + dish - mails it to the owner by first name with a preview QR every step from discovery to brand-matching to outreach is automated. reply "GUIDE" + RT and I'll send you a free guide so you can build this too

this OpenClaw bot finds restaurants with ugly food photos, redrafts them as IG posts, and mails the owner a postcard...on autopilot. here's how social-media agencies can use this system and land clients: - scrapes every restaurant in a city in real time - filters by review count + rating + last post date + photo quality - pulls the strongest food photo from Google Maps reviews - samples the brand palette from the restaurant's own visual identity - AI-redrafts the photo into a 9:16 brand-matched Instagram post - writes a postcard quoting a real reviewer + dish - mails it to the owner by first name with a preview QR every step from discovery to brand-matching to outreach is automated. reply "GUIDE" + RT and I'll send you a free guide so you can build this too

247,461 次观看

grok bot + whop can generate passive income on autopilot - whop blueprints are entire businesses, prebuilt - grok bot picks the niche and rewrites the copy - then lists the finished blueprint in the gallery - 10% of whop's profit on every sale it makes - every dollar of their ad spend pays you too set it up once and grok bot runs every step autonomously

grok bot + whop can generate passive income on autopilot - whop blueprints are entire businesses, prebuilt - grok bot picks the niche and rewrites the copy - then lists the finished blueprint in the gallery - 10% of whop's profit on every sale it makes - every dollar of their ad spend pays you too set it up once and grok bot runs every step autonomously

68,593 次观看

the smartest AI business i've seen this year sells kitchen renovations. GPT-6 Astra + the Higgsfield API wired into one chat. no reps, no calls. here's the whole thing... client sends 4 blurry photos of their kitchen Gpt-6 Astra reads the whole chat. budget, deadline, objections Higgsfield API turns the photos into their exact kitchen, renovated. 3 styles, image & video 60 seconds later the client is picking a style. quote attached, site visit booked. build this in a weekend using Higgsfield API, sell it to every renovation company in your city for $2k/mo. 5 companies = $10k/mo. if your clients have to imagine the result first, you're either building this or losing to the guy who does.

the smartest AI business i've seen this year sells kitchen renovations. GPT-6 Astra + the Higgsfield API wired into one chat. no reps, no calls. here's the whole thing... client sends 4 blurry photos of their kitchen Gpt-6 Astra reads the whole chat. budget, deadline, objections Higgsfield API turns the photos into their exact kitchen, renovated. 3 styles, image & video 60 seconds later the client is picking a style. quote attached, site visit booked. build this in a weekend using Higgsfield API, sell it to every renovation company in your city for $2k/mo. 5 companies = $10k/mo. if your clients have to imagine the result first, you're either building this or losing to the guy who does.

39,134 次观看

this OpenClaw bot watches NASA wildfire satellites. when a fire starts, it finds every at-risk home nearby, renders fire hardening fireproofing upgrade on their actual house, and mails them a postcard, all on autopilot. here's how contractors in fire zones can close $30k–$60k fireproofing jobs with this: - pulls live fire detections from NASA FIRMS satellites every 5 minutes - finds every home in the fire perimeter from public records - captures the property via Google Street View - classifies roof type + fire vulnerabilities using AI vision - generates a NASA satellite image of the neighborhood with real fire hotspots overlaid - renders a fire hardening retrofit on their actual house - prints a postcard with the NASA fire map + before/after retrofit + QR code every step from fire detection to mailbox runs without a human reply "FIRE" + RT and i'll send you the full guide so you can build this too (must be following so i can DM)

this OpenClaw bot watches NASA wildfire satellites. when a fire starts, it finds every at-risk home nearby, renders fire hardening fireproofing upgrade on their actual house, and mails them a postcard, all on autopilot. here's how contractors in fire zones can close $30k–$60k fireproofing jobs with this: - pulls live fire detections from NASA FIRMS satellites every 5 minutes - finds every home in the fire perimeter from public records - captures the property via Google Street View - classifies roof type + fire vulnerabilities using AI vision - generates a NASA satellite image of the neighborhood with real fire hotspots overlaid - renders a fire hardening retrofit on their actual house - prints a postcard with the NASA fire map + before/after retrofit + QR code every step from fire detection to mailbox runs without a human reply "FIRE" + RT and i'll send you the full guide so you can build this too (must be following so i can DM)

175,529 次观看

My OpenClaw bot runs a complete website agency on autopilot: - Finds 100’s of local businesses via Google Maps - AI audits every site → grades them A-D - Builds custom websites for the worst ones - Texts them the preview link - AI voice agent calls to close the deal - Runs 24/7 with zero manual work Most local businesses don't have a website, this system finds them and pitches them automatically Reply “OpenClaw” and I'll send the full system (must be following)

My OpenClaw bot runs a complete website agency on autopilot: - Finds 100’s of local businesses via Google Maps - AI audits every site → grades them A-D - Builds custom websites for the worst ones - Texts them the preview link - AI voice agent calls to close the deal - Runs 24/7 with zero manual work Most local businesses don't have a website, this system finds them and pitches them automatically Reply “OpenClaw” and I'll send the full system (must be following)

203,922 次观看

claude opus 5 runs six agents selling services to local businesses 24/7 and it built a live earth to watch it all happen on here's what it does: - picks a city and pulls a whole niche off google maps - six agents, each hunting one flaw: no website, no socials, no ads, no booking, ignored reviews, dead phone line - whichever agent finds the worst problem claims that business, so no owner gets pitched six times about six different things - writes them a real website off their own reviews from scratch - makes the matching social post and the tap card for the counter - prints a postcard and sends it to their address - then puts a light on the globe so i can watch it land reply "PROMPT" + RT and i'll send you the prompt so you can build this too (must be following so i can DM you)

claude opus 5 runs six agents selling services to local businesses 24/7 and it built a live earth to watch it all happen on here's what it does: - picks a city and pulls a whole niche off google maps - six agents, each hunting one flaw: no website, no socials, no ads, no booking, ignored reviews, dead phone line - whichever agent finds the worst problem claims that business, so no owner gets pitched six times about six different things - writes them a real website off their own reviews from scratch - makes the matching social post and the tap card for the counter - prints a postcard and sends it to their address - then puts a light on the globe so i can watch it land reply "PROMPT" + RT and i'll send you the prompt so you can build this too (must be following so i can DM you)

83,579 次观看

claude fable 5 now watches every city for new pool permits. the law makes every one of those owners buy a fence. so it mails them their finished backyard before the pool is even filled. this demo is real: the satellite still shows their old ring pool, the permit already replaces it with an in-ground build and claude caught it days after filing. here's the system you can sell to contractors: - monitors the city's pool permits in real time (free public data) - pulls the satellite photo of every permitted address - vision-checks the yard, rejects the bad leads - renders that backyard 3 ways: fence, rebuilt yard, night swim - prints the law on a postcard: "your pool can't pass inspection without a 48in barrier" - mails it to the owner with a QR per trade fence company, landscaper, lighting contractor, three retainers from one system and new permits drop every week. reply "POOL" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

claude fable 5 now watches every city for new pool permits. the law makes every one of those owners buy a fence. so it mails them their finished backyard before the pool is even filled. this demo is real: the satellite still shows their old ring pool, the permit already replaces it with an in-ground build and claude caught it days after filing. here's the system you can sell to contractors: - monitors the city's pool permits in real time (free public data) - pulls the satellite photo of every permitted address - vision-checks the yard, rejects the bad leads - renders that backyard 3 ways: fence, rebuilt yard, night swim - prints the law on a postcard: "your pool can't pass inspection without a 48in barrier" - mails it to the owner with a QR per trade fence company, landscaper, lighting contractor, three retainers from one system and new permits drop every week. reply "POOL" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

123,079 次观看

gpt-6 astra + higgsfield api can now run a fiverr business on autopilot there are 1000's of orders everyday for simple video work, and most of it is just a model's job now, so the bot picks the ones it can deliver and does them > finds clients who need launch videos, motion design or ugc ads > reads the brief and picks the jobs it can deliver accurately > higgsfield api generates the footage, animations or clips > delivers the files and handles the client feedback > quotes extra work for any revisions at $350 an order, 30 to 40 a month is $10k before fees and production reply "FIVERR" + RT and i'll send you the build plan (must be following so i can dm)

gpt-6 astra + higgsfield api can now run a fiverr business on autopilot there are 1000's of orders everyday for simple video work, and most of it is just a model's job now, so the bot picks the ones it can deliver and does them > finds clients who need launch videos, motion design or ugc ads > reads the brief and picks the jobs it can deliver accurately > higgsfield api generates the footage, animations or clips > delivers the files and handles the client feedback > quotes extra work for any revisions at $350 an order, 30 to 40 a month is $10k before fees and production reply "FIVERR" + RT and i'll send you the build plan (must be following so i can dm)

36,127 次观看

grok bot is running 4 agents that generate revenue 24/7 it also built a 3js dashboard for it, with a starship, a dome per business and starman roadstar floating... - finds the prospects out of public data - scores each one before you spend anything - builds the asset before making contact - takes the payment on whop itself - ships the product or deploys the site - shows you what needs approving each morning everything from finding the customer to selling them just wrote a whole guide on how you can set this up exactly:

grok bot is running 4 agents that generate revenue 24/7 it also built a 3js dashboard for it, with a starship, a dome per business and starman roadstar floating... - finds the prospects out of public data - scores each one before you spend anything - builds the asset before making contact - takes the payment on whop itself - ships the product or deploys the site - shows you what needs approving each morning everything from finding the customer to selling them just wrote a whole guide on how you can set this up exactly:

56,858 次观看

Claude Fable is finally back! it can now watch the meta ad library for the businesses that just turned their first ad on and mails them a finished, better version of it here's the system you can use to run an agency: - watches the meta ad library for businesses that just started running ads - pulls each one's google business profile for a mailable address + real photos - vision-checks the current ad, rejects the weak leads - rebuilds it into the ad their industry actually runs, not a stock template - prints a before/after postcard: their flat ad next to the recut + a QR - mails it to the owner, then makes their content every month one system that lands you new local biz clients every week. reply "FABLE" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

Claude Fable is finally back! it can now watch the meta ad library for the businesses that just turned their first ad on and mails them a finished, better version of it here's the system you can use to run an agency: - watches the meta ad library for businesses that just started running ads - pulls each one's google business profile for a mailable address + real photos - vision-checks the current ad, rejects the weak leads - rebuilds it into the ad their industry actually runs, not a stock template - prints a before/after postcard: their flat ad next to the recut + a QR - mails it to the owner, then makes their content every month one system that lands you new local biz clients every week. reply "FABLE" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

92,983 次观看

Videos

everestchris6's profile picture

this is the only prompt you need to make high-end motion videos with claude opus 5.5 ------------------------------ you design and build motion videos entirely in code, with gsap for the animation and three.js for any 3d. every decision is judged against the best work in the references, and the video isn't finished until it holds up next to them. - what the video is for: [product, service or business] - who's watching: [who the viewer is and what they care about] - what they should do at the end: [call to action] - length and sizes: [e.g. 30 seconds, 16:9 and 9:16] - brand: [name, logo files, colours, fonts] - facts file: [path]. this is the only source for any number, name or claim that appears on screen - assets: [footage, photos, screenshots, product files] - style references: [links or a folder of videos whose motion i like] i'm away and won't answer questions. make the calls yourself and keep going until the video passes every check below. before anything else, clone and read read SKILL.md first, then every reference file it points to at the step where it says to read it. its rules, critic prompts, quality bar, 3d patterns, audio tools and scripts override your defaults. - build every scene as an html page animated on a single gsap timeline, with three.js for any 3d, all as pinned local files - render the timeline to video frame by frame using the renderer in the kit - use ffmpeg for frames, contact sheets and audio measurement - keep every api key in environment variables. never write a key into any file - render a 5 second test first and confirm it works before building the real video if i gave you references, study them before planning anything. - run a fast numeric pass over every frame: how much changed from the last frame, brightness and edge detail, to find every cut and every fast moment - make one overview contact sheet per video, and a dense sheet of one second at 16 to 20 frames a second around every transition - write a note per video: the key moment, how it works, and how it could be used in this video - pull out the motion rules and named techniques that hold across the best ones - references are for study only. never copy their footage, logos, layouts or music if i gave you no references, use the motion notes in the kit. 1. the thing in the front of the shot becomes the transition. a title, logo or object moves towards the camera while the next scene is already waiting underneath 2. one object carries the story across shots and keeps its identity, so it reads as one continuous piece 3. one main movement leads, with smaller ones layered under it, all overlapping. the frame never stops and starts all at once 4. the speed always changes. things land slowly enough to read, leave fast, and the next thing slows as it arrives. no linear motion 5. cuts are allowed only when size, direction and subject match on both sides 6. every action produces a visible result. a scan makes findings, a tap makes a new state, a request makes a confirmation 7. type is motion too. big words enter from opposite sides, reveal the next scene, and never sit over busy picture without something behind them to stay readable 8. vary the scale from close, to wide, to overhead, to full-frame type. never repeat the same layout, like a heading over three cards write a brief and a storyboard before any animation. - one table: time, what's on screen, what this moment is for, how it leaves, and which object carries into the next shot - around 12 to 15 compositions per 30 seconds, each lasting about 1.4 to 3.5 seconds - the main subject fills most of the frame. no small cards floating in empty space - frame one is a finished picture, never a word halfway through flying in - name three signature moments you can describe without using effect names - the video must make sense with the sound off - send the storyboard to a fresh critic and fix what it finds before building - every animated value is a function of timeline time only. no timers, no real-time animation, no unseeded randomness. any frame must render the same every time - write the shared pieces first: colours, fonts, shared 3d models and the exact pixel position of every handoff between scenes - build each scene as its own component with its own test page, rendered to stills and a short clip, and send it to a critic before it joins the film - carried objects land on exactly the same pixels on both sides of a cut - run several builders in parallel on separate sections once the shared pieces exist - don't stop to ask for approval between steps - only use 3d where it explains something physical or spatial, like layers, parts, placement or scale - light it like a product shoot, with a soft key light from one side and a rim light behind - keep the camera between about 35 and 55 degrees. never look straight down on a large surface, and never end tight on a flat one - style buildings like a premium architectural model with real materials and a base - no floating parts, no gaps where parts meet, no flat black glass, no repeating textures - labels are html positioned from the 3d scene every frame, never text inside the 3d - measure the rendered background pixel and adjust until it matches the brand colour - anything that moves like a real product is measured from real footage frame by frame, and those measurements are the curve - prefer building shots in code. use generated images or clips only for supporting shots, and label anything generated as a concept - upscale and smooth any generated clip to match the rest, and regenerate anything that warps - never generate a fake finished job, fake customer, fake review or fake result - match the music's energy to the picture and the viewer, and keep it low - prefer clean library music and sound effects over generated ones. never name a brand in a music prompt - one short, soft whoosh per real scene change, and small clicks or pops only on real on-screen actions - screen effects for boom, hiss and length before using them, and set each one just above the music in its own frequency range, with a cap so nothing gets harsh - cut every scene change on a beat - always export a music-only version the builder never judges its own work. - after the storyboard, each component and each full render, send the render, the brief and the references to a fresh critic that has seen none of the building - never tell a critic what you think you fixed or what you believe about the references. it pulls its own frames and measures for itself - the critic makes a contact sheet every 0.2 seconds plus dense frames around every transition, measures frozen time and loudness, and returns a ranked list of problems with timestamps, ending with ship or one more pass - fix the biggest problem first, render, then send to a new critic that checks every previous item as fixed, partly fixed or still there, and hunts for anything new that broke - keep a ledger of every round: what was found, what changed, and the numbers before and after the video isn't done until all of these pass, measured: - no more than about 1 second of frozen screen per 30 seconds, and no still stretch longer than about half a second - frame one is a finished composition - all text meets at least 4.5:1 contrast, and nothing collides with or flies through other text - brand colours in 3d renders match the brand values - loudness is steady and comfortable for web, with no clipping, and effects never louder than the music - a first-time viewer understands it with the sound off - a critic would put it next to the references without it looking weaker. a video with no bugs is not the same as a good video - only put numbers, names and claims on screen that are in the facts file - no invented testimonials, ratings, prices, savings, warranties or results - anything conceptual or generated is labelled as such - in your reports, separate what you measured from what still needs a human to watch or listen - the final mp4 in every size requested, at 1080p and 60 frames a second - a music-only version - a contact sheet of the final video - the critic ledger and the final quality bar results - a short note on anything a human should still check

Chris

126,681 次观看 • 21 天前

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