Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Fable 5 and GPT-5.6 built the same scroll-animated website from one skill in 32 minutes. Only one of them made it feel like a film. Same prompt. Boutique Japan travel brand, origami style. A subway pulls in, a paper house unfolds into a hotel, a bird takes flight as...

RoundtableSpace's profile picture

0xMarioNawfal

257,000 subscribers

48,091 görüntüleme • 3 gün önce •via X (Twitter)

Bilim & TeknolojiSanatEğitim
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

GPT-5.6 vs GPT-5.5 on my custom spaceship prompt. I gave both models the exact same custom prompt. This is also the same prompt I previously gave to Fable 5. For context, GPT-5.6 Pro worked for 87 minutes, while GPT-5.5 Extra High worked for 34 minutes and 42 seconds. As I’ve said before, based on great authority GPT-5.6 will be an incremental/soldi improvement over GPT-5.5, not a “Fable killer.” My rough expectation has been that it would trade blows with Fable 5 on some benchmarks, maybe win around half depending on the category, but not clearly surpass it overall. And again fable five will have bigger model smell, but this was expected. After testing this coding output, that view feels pretty accurate. GPT-5.6 is clearly better than GPT-5.5 in several visual areas. The lighting, shading, chairs, object details, and exterior of the spaceship looked noticeably stronger. The scene was also easier to test. I do want to give GPT-5.5 credit though. It built out the rooms much much better and the planets looked better than GPT-5.6’s. It was also interesting that both GPT-5.5 and GPT-5.6 produced better-looking planets than Fable 5 in this specific test. The downside with GPT-5.5 was stability. The game was much glitchier and harder to test compared to GPT-5.6. But when it comes to the core of the demo, which is the spaceship itself, Fable 5 still beat both models pretty comfortably. GPT-5.6 is impressive, but from this test, it looks exactly like what I expected which was a meaningful incremental improvement over GPT-5.5, at least for indie game demos, but not something that replaces Fable 5. In collaboration with Chetaslua
0:42

GPT-5.6 vs GPT-5.5 on my custom spaceship prompt. I gave both models the exact same custom prompt. This is also the same prompt I previously gave to Fable 5. For context, GPT-5.6 Pro worked for 87 minutes, while GPT-5.5 Extra High worked for 34 minutes and 42 seconds. As I’ve said before, based on great authority GPT-5.6 will be an incremental/soldi improvement over GPT-5.5, not a “Fable killer.” My rough expectation has been that it would trade blows with Fable 5 on some benchmarks, maybe win around half depending on the category, but not clearly surpass it overall. And again fable five will have bigger model smell, but this was expected. After testing this coding output, that view feels pretty accurate. GPT-5.6 is clearly better than GPT-5.5 in several visual areas. The lighting, shading, chairs, object details, and exterior of the spaceship looked noticeably stronger. The scene was also easier to test. I do want to give GPT-5.5 credit though. It built out the rooms much much better and the planets looked better than GPT-5.6’s. It was also interesting that both GPT-5.5 and GPT-5.6 produced better-looking planets than Fable 5 in this specific test. The downside with GPT-5.5 was stability. The game was much glitchier and harder to test compared to GPT-5.6. But when it comes to the core of the demo, which is the spaceship itself, Fable 5 still beat both models pretty comfortably. GPT-5.6 is impressive, but from this test, it looks exactly like what I expected which was a meaningful incremental improvement over GPT-5.5, at least for indie game demos, but not something that replaces Fable 5. In collaboration with Chetaslua

Chris

228,126 görüntüleme • 27 gün önce

this is f**king insane Fable 5 goes away in 24 hours from Claude Code and someone just figured out how to get fable 5 reasoning in GPT 5.6 Sol with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Go the Codex App > Settings > Personalisation > Custom Instructions 3) Use GPT 5.5 / GPT 5.6 and now you have Fable 5 reasoning at 1/3 th the price save and bookmark it no matter what
0:32

this is f**king insane Fable 5 goes away in 24 hours from Claude Code and someone just figured out how to get fable 5 reasoning in GPT 5.6 Sol with one prompt you have less than 24 hours to set this up as this takes away 20% of your usage limit here is how: 1) Paste the prompt and ask it to "make an operating manual" 2) Go the Codex App > Settings > Personalisation > Custom Instructions 3) Use GPT 5.5 / GPT 5.6 and now you have Fable 5 reasoning at 1/3 th the price save and bookmark it no matter what

Avid

51,393 görüntüleme • 3 gün önce

Fable 5 is BACK on AI/ML API We gave Sonnet 5 and Fable 5 the exact same prompt and same real flight dataset of 70 airports and 435 routes pulled from flightradar. Then asked each one to turn it into a cinematic 3D globe as a single HTML file. Outputs: Sonnet 5: 9.8k tokens, $0.10 Fable 5: 15k tokens, $0.77 Sonnet 5 came in 87% cheaper. It drew the routes, but the planet underneath them barely exists: a dark wireframe with the arcs floating in space. Fable 5 built an actual Earth: textured oceans, ice caps, atmospheric glow. Mythos-class models are truly a masterpiece. Docs, guides & setup below:
0:37

Fable 5 is BACK on AI/ML API We gave Sonnet 5 and Fable 5 the exact same prompt and same real flight dataset of 70 airports and 435 routes pulled from flightradar. Then asked each one to turn it into a cinematic 3D globe as a single HTML file. Outputs: Sonnet 5: 9.8k tokens, $0.10 Fable 5: 15k tokens, $0.77 Sonnet 5 came in 87% cheaper. It drew the routes, but the planet underneath them barely exists: a dark wireframe with the arcs floating in space. Fable 5 built an actual Earth: textured oceans, ice caps, atmospheric glow. Mythos-class models are truly a masterpiece. Docs, guides & setup below:

AI/ML API

497,609 görüntüleme • 14 gün önce

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

54,531 görüntüleme • 1 ay önce

Obsidian Bases are better than Notion databases. Most people never use them because they're too technical. This Claude skill changes this: Bases automatically aggregate notes from your vault into a structured table. I have dozens of bases; the one in the video replaces the reference manager, for instance. Problem: Most struggle with setting them up. There's now a skill built by one of the Obsidian developers that runs inside Claude. The skill scans your vault and automatically generates the base. The hardest Obsidian feature to learn. Solved with one sentence.
1:53

Obsidian Bases are better than Notion databases. Most people never use them because they're too technical. This Claude skill changes this: Bases automatically aggregate notes from your vault into a structured table. I have dozens of bases; the one in the video replaces the reference manager, for instance. Problem: Most struggle with setting them up. There's now a skill built by one of the Obsidian developers that runs inside Claude. The skill scans your vault and automatically generates the base. The hardest Obsidian feature to learn. Solved with one sentence.

Ilya Shabanov

34,010 görüntüleme • 2 ay önce

A CHINESE GIRL USED FABLE 5 TO BUILD A GAME THAT TURNS YOUR HAND INTO WATER it's for meditation you move your hand, the water moves with it that's the whole game what's running under the hood: > Fable 5 built the entire interaction logic > meshy turned text into the 3D water world > three.js and webGL render everything live in your browser > mediapipe tracks your hand through the camera alone whole thing takes 3-5 minutes and 300+ people already tried it she built this as a way to breathe for 5 minutes ended up making one of the coolest things anyone's done with Fable 5 if you wanna see what else Fable 5 can do full guide below
1:23

A CHINESE GIRL USED FABLE 5 TO BUILD A GAME THAT TURNS YOUR HAND INTO WATER it's for meditation you move your hand, the water moves with it that's the whole game what's running under the hood: > Fable 5 built the entire interaction logic > meshy turned text into the 3D water world > three.js and webGL render everything live in your browser > mediapipe tracks your hand through the camera alone whole thing takes 3-5 minutes and 300+ people already tried it she built this as a way to breathe for 5 minutes ended up making one of the coolest things anyone's done with Fable 5 if you wanna see what else Fable 5 can do full guide below

Madni Aghadi

13,187 görüntüleme • 12 gün önce

THIS GUY BUILT A VISUAL CALENDAR THAT SHOWS YOU EVERY SUBSCRIPTION YOU'RE PAYING FOR the best part is it auto-imports your subscriptions directly from the app store so no manual entry, no typing in amounts, it just pulls everything automatically you open it and instantly see when every charge is hitting and how much is going out each month we're all paying for at least 5-10 subscriptions we forgot about and this puts all of them in one visual calendar clean UI and a simple concept that solves a problem everyone has but nobody bothers to fix
0:22

THIS GUY BUILT A VISUAL CALENDAR THAT SHOWS YOU EVERY SUBSCRIPTION YOU'RE PAYING FOR the best part is it auto-imports your subscriptions directly from the app store so no manual entry, no typing in amounts, it just pulls everything automatically you open it and instantly see when every charge is hitting and how much is going out each month we're all paying for at least 5-10 subscriptions we forgot about and this puts all of them in one visual calendar clean UI and a simple concept that solves a problem everyone has but nobody bothers to fix

Om Patel

148,791 görüntüleme • 1 ay önce

This is one of the wildest things I have built with AI so far 😱 Asked Claude Fable 5 to create a fully interactive 3D crime investigation board using Three.js and it did it in ONE Prompt. It took one more prompt to give it a polished UI inspired by a reference design that I created with GPT Image. What surprised me most was not how it looked. It was how it worked. Fable built a complete Verlet rope physics system with 46 particles in every thread. It handled gravity, damping, distance constraints and all other features of file upload, text and everything. The threads/ropes even lift naturally with pinned evidence instead of clipping through it. I never asked it to implement any of that. I only described the experience I wanted. Maybe that's how we should work with AI. Instead of writing long long specs, we should explain what we want as an experience and let AI do its thing. Anyway, every day Fable 5 raises the bar for what I think AI can build. More to this Live: Code:
0:49

This is one of the wildest things I have built with AI so far 😱 Asked Claude Fable 5 to create a fully interactive 3D crime investigation board using Three.js and it did it in ONE Prompt. It took one more prompt to give it a polished UI inspired by a reference design that I created with GPT Image. What surprised me most was not how it looked. It was how it worked. Fable built a complete Verlet rope physics system with 46 particles in every thread. It handled gravity, damping, distance constraints and all other features of file upload, text and everything. The threads/ropes even lift naturally with pinned evidence instead of clipping through it. I never asked it to implement any of that. I only described the experience I wanted. Maybe that's how we should work with AI. Instead of writing long long specs, we should explain what we want as an experience and let AI do its thing. Anyway, every day Fable 5 raises the bar for what I think AI can build. More to this Live: Code:

The Bugged Dev

92,073 görüntüleme • 5 gün önce

This is actually cool - I tried the same prompt for the new Interactive Playwright skill in Codex & GPT-5.4 xHigh - the one above is with the skill and the one below is without. What the skill does is uses the computer use capability of GPT-5.4 to look and navigate the UI. This never worked for me before, but with GPT-5.4 this is the first time I can actually see a massive difference. You can see how the first scene is much more coherent, higher fidelity and complete. The one below is missing a lot of elements and isn't as rich in detail. I'll keep using it for any UI work now.
0:32

This is actually cool - I tried the same prompt for the new Interactive Playwright skill in Codex & GPT-5.4 xHigh - the one above is with the skill and the one below is without. What the skill does is uses the computer use capability of GPT-5.4 to look and navigate the UI. This never worked for me before, but with GPT-5.4 this is the first time I can actually see a massive difference. You can see how the first scene is much more coherent, higher fidelity and complete. The one below is missing a lot of elements and isn't as rich in detail. I'll keep using it for any UI work now.

Peter Gostev

257,111 görüntüleme • 4 ay önce

how to use Google's NEW open source Design.md + AI Skills to make your startup look like a $100 million company in 1 hour: 1. Design.md is an open source file from Google that captures the soul of a design. Typography, colors, spacing, all in one markdown file. You attach it to your prompt and your agent builds beautiful things every time. 2. Think of it this way. The HTML is the finished dish. The design.md is the recipe. The skills are the ingredients. Put them together and everything you build looks consistent and professional. 3. Don't create a design system from scratch. Find a brand you love. Linear, Stripe, Vercel, whatever resonates. Study it. Use ChatGPT or Claude to help you extract the design language into your own design.md file. 4. Build skills on top of your design.md. A landing page skill. A mobile app skill. A motion design skill. A slide deck skill. Each one references the same design.md so everything looks like it came from the same designer. 5. The biggest mistake people make: they nail one screen and then everything else looks generic. Design.md solves this. One file keeps every page, every format, every medium consistent. 6. Use it across everything. Your landing page. Your app. Your pitch deck. Your promo videos. Same DNA. Same taste. Same system. That's what separates a startup that looks real from one that looks vibe-coded. 7. Build a second brain for design inspiration. When you see something beautiful in the real world or online, capture it. Save it. When you're building something new, reference it. Taste is developed, not downloaded. 8. It's obvious but the difference between a product people trust and a product people bounce from is how it looks and feels. Design.md gives you that edge. you can watch below shoutout to Meng To for coming on The Startup Ideas Podcast (SIP) 🧃 and walking through his full workflow. if you want to use AI to actually build gorgeous designs, you'll want to use see this. watch
51:01

how to use Google's NEW open source Design.md + AI Skills to make your startup look like a $100 million company in 1 hour: 1. Design.md is an open source file from Google that captures the soul of a design. Typography, colors, spacing, all in one markdown file. You attach it to your prompt and your agent builds beautiful things every time. 2. Think of it this way. The HTML is the finished dish. The design.md is the recipe. The skills are the ingredients. Put them together and everything you build looks consistent and professional. 3. Don't create a design system from scratch. Find a brand you love. Linear, Stripe, Vercel, whatever resonates. Study it. Use ChatGPT or Claude to help you extract the design language into your own design.md file. 4. Build skills on top of your design.md. A landing page skill. A mobile app skill. A motion design skill. A slide deck skill. Each one references the same design.md so everything looks like it came from the same designer. 5. The biggest mistake people make: they nail one screen and then everything else looks generic. Design.md solves this. One file keeps every page, every format, every medium consistent. 6. Use it across everything. Your landing page. Your app. Your pitch deck. Your promo videos. Same DNA. Same taste. Same system. That's what separates a startup that looks real from one that looks vibe-coded. 7. Build a second brain for design inspiration. When you see something beautiful in the real world or online, capture it. Save it. When you're building something new, reference it. Taste is developed, not downloaded. 8. It's obvious but the difference between a product people trust and a product people bounce from is how it looks and feels. Design.md gives you that edge. you can watch below shoutout to Meng To for coming on The Startup Ideas Podcast (SIP) 🧃 and walking through his full workflow. if you want to use AI to actually build gorgeous designs, you'll want to use see this. watch

GREG ISENBERG

503,527 görüntüleme • 2 ay önce

ONE PROMPT IN CHATGPT IMAGE 2 JUST REPLACED AN ENTIRE $5,000-$50,000 BRAND DESIGN TEAM Full brand identity. Colors, typography, logo style, aesthetic. All generated in one single prompt. Here's the exact workflow: Step 1: Paste one prompt asking for a complete brand identity. GPT Image 2 generates everything – color palette, fonts, logo direction, overall visual style. Step 2: Use that output as context for every asset you generate after. Campaign visuals, shop graphics, product mockups, social posts – all stay consistent and on-brand automatically. The result: A full visual identity that looks like a real design team built it. Clean text rendering. Consistent style across every single asset. Design agencies charge $5,000-$50,000 for brand identity work. GPT Image 2 does it in one prompt. The full prompt that makes this work is in the video below. Bookmark this post, you'll want to come back to it.
0:48

ONE PROMPT IN CHATGPT IMAGE 2 JUST REPLACED AN ENTIRE $5,000-$50,000 BRAND DESIGN TEAM Full brand identity. Colors, typography, logo style, aesthetic. All generated in one single prompt. Here's the exact workflow: Step 1: Paste one prompt asking for a complete brand identity. GPT Image 2 generates everything – color palette, fonts, logo direction, overall visual style. Step 2: Use that output as context for every asset you generate after. Campaign visuals, shop graphics, product mockups, social posts – all stay consistent and on-brand automatically. The result: A full visual identity that looks like a real design team built it. Clean text rendering. Consistent style across every single asset. Design agencies charge $5,000-$50,000 for brand identity work. GPT Image 2 does it in one prompt. The full prompt that makes this work is in the video below. Bookmark this post, you'll want to come back to it.

SCOTTY BEAM

12,023 görüntüleme • 27 gün önce

THIS GUY BUILT REAL FLYING SWORD DRONES AND CONTROLS THEM WITH HAND GESTURES fan shisan is a physics student in chengdu who coded and built flying drones shaped like actual swords he controls them entirely with hand gestures. no controller or a phone. just his hands wave your hand and the sword follows. point and it flies where you direct it. multiple swords in the air at the same time responding to different gestures he built the gesture recognition system HIMSELF and coded the flight control algorithms. designed the drone hardware in the shape of swords. the gesture tracking uses sensors that read the position and movement of his hands in real time and translate them into flight commands for each drone independently he even built one large enough to ride on a physics student with coding skills just brought something straight out of a kung fu movie into the real world the line between science fiction and side projects is getting thinner every month
0:23

THIS GUY BUILT REAL FLYING SWORD DRONES AND CONTROLS THEM WITH HAND GESTURES fan shisan is a physics student in chengdu who coded and built flying drones shaped like actual swords he controls them entirely with hand gestures. no controller or a phone. just his hands wave your hand and the sword follows. point and it flies where you direct it. multiple swords in the air at the same time responding to different gestures he built the gesture recognition system HIMSELF and coded the flight control algorithms. designed the drone hardware in the shape of swords. the gesture tracking uses sensors that read the position and movement of his hands in real time and translate them into flight commands for each drone independently he even built one large enough to ride on a physics student with coding skills just brought something straight out of a kung fu movie into the real world the line between science fiction and side projects is getting thinner every month

Om Patel

307,264 görüntüleme • 1 ay önce

google flow + claude + gpt image is actually f*cking cracked i figured out how to lock one AI character across an entire video. same face, same voice, same outfit, every single shot. zero drift. everyone making AI video right now hits the same wall. the character looks different in every clip so you can never tell an actual story. you get 5 second clips, not films. the fix isn't better prompting. it's building the character ONCE before you ever touch video, then referencing it everywhere. here's the workflow: > build the character inside Flow's character section, not a per-clip prompt > design the voice + personality one time and reuse it across every clip > generate a full turnaround sheet (Claude writes the prompt, GPT image renders the angles) > pull the character into any scene with a single @ tag > ingredients vs frames: when to let a shot float vs lock it to your source image > the end-frame loop that chains 4-10 sec clips into one seamless scene > stitch + trim in the timeline editor and export the whole thing as one film i packaged the entire thing. every prompt, the exact tool order, the character sheet template, and the continuity loop nobody actually explains. RT + reply "FLOW" and i'll send it over (must be following so i can dm)
0:25

google flow + claude + gpt image is actually f*cking cracked i figured out how to lock one AI character across an entire video. same face, same voice, same outfit, every single shot. zero drift. everyone making AI video right now hits the same wall. the character looks different in every clip so you can never tell an actual story. you get 5 second clips, not films. the fix isn't better prompting. it's building the character ONCE before you ever touch video, then referencing it everywhere. here's the workflow: > build the character inside Flow's character section, not a per-clip prompt > design the voice + personality one time and reuse it across every clip > generate a full turnaround sheet (Claude writes the prompt, GPT image renders the angles) > pull the character into any scene with a single @ tag > ingredients vs frames: when to let a shot float vs lock it to your source image > the end-frame loop that chains 4-10 sec clips into one seamless scene > stitch + trim in the timeline editor and export the whole thing as one film i packaged the entire thing. every prompt, the exact tool order, the character sheet template, and the continuity loop nobody actually explains. RT + reply "FLOW" and i'll send it over (must be following so i can dm)

Sulfur

34,612 görüntüleme • 14 gün önce

The truth about 5.6 sol after using it all day : The hype is overblown. Sort of. The benchmarks, and the commentary on X convinced me we were receiving AGI that runs at hyper speed, and is insanely cheap. in reality, 5.6 is built on the same spud pretraining as 5.5 this means its a nice bump, but not the opus to fable 5 LEAP in intelligence we recently experienced from anthropic. 5.6 is 2x times cheaper than fable on paper, and actually 3x cheaper when you look at actual task execution because of its token efficiency. BUT on swe bench where the models have to fix actual github bugs it falls behind fable pretty big. For vibecoders like myself this means I will be using 5.6 sol as a worker agent for Fable 5 to orchestrate alongside grok 4.5 I love this new era.
7:29

The truth about 5.6 sol after using it all day : The hype is overblown. Sort of. The benchmarks, and the commentary on X convinced me we were receiving AGI that runs at hyper speed, and is insanely cheap. in reality, 5.6 is built on the same spud pretraining as 5.5 this means its a nice bump, but not the opus to fable 5 LEAP in intelligence we recently experienced from anthropic. 5.6 is 2x times cheaper than fable on paper, and actually 3x cheaper when you look at actual task execution because of its token efficiency. BUT on swe bench where the models have to fix actual github bugs it falls behind fable pretty big. For vibecoders like myself this means I will be using 5.6 sol as a worker agent for Fable 5 to orchestrate alongside grok 4.5 I love this new era.

Max Blade

36,351 görüntüleme • 6 gün önce

I built a Harvard-style resume builder Claude Skill that does it for you, and I’m giving it away free. Claude Applying for jobs without tailoring your resume should be a taboo by now. Most job seekers still treat applications like a volume game. Send the same CV everywhere. Make tiny edits. Hope something lands. But every strong application follows the same workflow: → understand the role → match your experience to it → rewrite your CV around that fit → refine it → repeat for the next role Same process. Every single time. So I stopped doing it manually and built a Claude Skill for each part of that thinking. Here’s what this one does: → Takes your current CV → Structures it properly → Outputs a clean Harvard-style resume → Tailors it to any job description in seconds → You just have to click download. What used to take a lot of effort now takes seconds. And the result is better because its Harvard style, ready to go and works in Claude, no new tool needed. Even we ditched our old model at hellocv and adopted the Harvard Style Resume Builder. Want it? -> Like this post -> RT + Comment “RESUME” I’ll DM it to you.
0:41

I built a Harvard-style resume builder Claude Skill that does it for you, and I’m giving it away free. Claude Applying for jobs without tailoring your resume should be a taboo by now. Most job seekers still treat applications like a volume game. Send the same CV everywhere. Make tiny edits. Hope something lands. But every strong application follows the same workflow: → understand the role → match your experience to it → rewrite your CV around that fit → refine it → repeat for the next role Same process. Every single time. So I stopped doing it manually and built a Claude Skill for each part of that thinking. Here’s what this one does: → Takes your current CV → Structures it properly → Outputs a clean Harvard-style resume → Tailors it to any job description in seconds → You just have to click download. What used to take a lot of effort now takes seconds. And the result is better because its Harvard style, ready to go and works in Claude, no new tool needed. Even we ditched our old model at hellocv and adopted the Harvard Style Resume Builder. Want it? -> Like this post -> RT + Comment “RESUME” I’ll DM it to you.

Opeyemi Awoyemi

14,599 görüntüleme • 3 ay önce

Using Claude Fable 5, I built a model that predicts the entire 2026 FIFA world cup.. every single game, not just the final.. so let me break the whole thing down. what it does, how it works, and exactly how i built it.. #1 First what it does: it predicts all 104 games of the tournament. not just who lifts the trophy, but every group match, every knockout, the full path from the round of 32 to the final.. everything lands in one dashboard: > group stage, every match with each team's win % and the chance of a draw > standings, how all 12 groups are projected to finish > bracket, the full knockout tree with each team's odds of advancing > champion odds, who's most likely to actually win it all and it doesn't freeze after one prediction. the moment a real game is played, it locks that result in and re-runs everything around it. so the odds move live as the tournament goes, week by week you watch favorites rise and contenders collapse. #2. How it works: the core idea is simple. the model only ever predicts one thing, a single match. the real trick is the repetition. it learns from decades of match history, then plays the whole tournament out from the first game to the final, tens of thousands of times. each run it records who advanced and who won. do that enough and you stop getting one guess and start getting real odds, one team lifts the trophy in maybe 14% of the runs, another in 9%, and so on. #3. So, how i built it ? i didn't hand-write most of the code. i broke the project into 4 pieces, described each one to fable, and let it build while i focused on getting the football logic exactly right. - The data every international match going back over a century, around 50,000 games, plus each team's elo rating, which is the truest measure of strength, and the official 2026 schedule. garbage data means garbage predictions, so this part mattered most. - The features i turned that raw history into signals the model can learn from, the elo gap between the two teams, recent form, goals scored and conceded, and a home boost for the hosts, usa, canada and mexico. - The model for each match it predicts the expected goals for both sides, then turns that into win, draw and loss probabilities plus a likely scoreline. that's what feeds the simulation. - The tournament engine this was the hard part. the 2026 world cup is brand new, 48 teams, 12 groups, a round of 32 that's never existed before, and 8 "best third-placed" teams that slot into the bracket by a fixed fifa table. even the group tiebreakers changed this year, head to head now counts before goal difference. get any of it wrong and the whole bracket falls apart, so i built it carefully and tested the format until it was exact, then wrapped it in a simulation loop that plays the tournament out tens of thousands of times. and the last piece, the live part. as real results come in, they get locked, and only the unplayed games get re-simulated. that's what makes it a living model instead of a one-time prediction. all of it outputs to a clean dashboard you can actually read and screenshot.. right now, before kickoff, it already has a clear favorite to lift the trophy.. 👀 btw who's your pick to win the 2026 world cup?
0:20

Using Claude Fable 5, I built a model that predicts the entire 2026 FIFA world cup.. every single game, not just the final.. so let me break the whole thing down. what it does, how it works, and exactly how i built it.. #1 First what it does: it predicts all 104 games of the tournament. not just who lifts the trophy, but every group match, every knockout, the full path from the round of 32 to the final.. everything lands in one dashboard: > group stage, every match with each team's win % and the chance of a draw > standings, how all 12 groups are projected to finish > bracket, the full knockout tree with each team's odds of advancing > champion odds, who's most likely to actually win it all and it doesn't freeze after one prediction. the moment a real game is played, it locks that result in and re-runs everything around it. so the odds move live as the tournament goes, week by week you watch favorites rise and contenders collapse. #2. How it works: the core idea is simple. the model only ever predicts one thing, a single match. the real trick is the repetition. it learns from decades of match history, then plays the whole tournament out from the first game to the final, tens of thousands of times. each run it records who advanced and who won. do that enough and you stop getting one guess and start getting real odds, one team lifts the trophy in maybe 14% of the runs, another in 9%, and so on. #3. So, how i built it ? i didn't hand-write most of the code. i broke the project into 4 pieces, described each one to fable, and let it build while i focused on getting the football logic exactly right. - The data every international match going back over a century, around 50,000 games, plus each team's elo rating, which is the truest measure of strength, and the official 2026 schedule. garbage data means garbage predictions, so this part mattered most. - The features i turned that raw history into signals the model can learn from, the elo gap between the two teams, recent form, goals scored and conceded, and a home boost for the hosts, usa, canada and mexico. - The model for each match it predicts the expected goals for both sides, then turns that into win, draw and loss probabilities plus a likely scoreline. that's what feeds the simulation. - The tournament engine this was the hard part. the 2026 world cup is brand new, 48 teams, 12 groups, a round of 32 that's never existed before, and 8 "best third-placed" teams that slot into the bracket by a fixed fifa table. even the group tiebreakers changed this year, head to head now counts before goal difference. get any of it wrong and the whole bracket falls apart, so i built it carefully and tested the format until it was exact, then wrapped it in a simulation loop that plays the tournament out tens of thousands of times. and the last piece, the live part. as real results come in, they get locked, and only the unplayed games get re-simulated. that's what makes it a living model instead of a one-time prediction. all of it outputs to a clean dashboard you can actually read and screenshot.. right now, before kickoff, it already has a clear favorite to lift the trophy.. 👀 btw who's your pick to win the 2026 world cup?

Axel Bitblaze 🪓

49,714 görüntüleme • 1 ay önce

This style of AI renovation video is helping RE agents and contractors close more deals (and it starts with a single photo). No staging company. No 3D rendering service. No $2K virtual staging package. Just one image and 10 minutes inside Calico AI. Here's how the system works: → Drop any room photo into the AI Room Renovator GPT → Choose a renovation style: modern, coastal, luxury → It hands you a perfectly tuned image prompt → Paste it inside Calico along with the original photo → Generate the renovated room in seconds → Open Kling 3.0 (same platform, no switching tools) — set original as start, renovation as end → Generate the animation — the room transforms before your eyes Before to after. In a video. From one photo. Drop that into a listing, an ad, or a client walkthrough and watch what happens. Comment "RENOVATE" and I'll send you the exact GPT link, prompts, and workflow (must be following so I can DM you!).
1:03

This style of AI renovation video is helping RE agents and contractors close more deals (and it starts with a single photo). No staging company. No 3D rendering service. No $2K virtual staging package. Just one image and 10 minutes inside Calico AI. Here's how the system works: → Drop any room photo into the AI Room Renovator GPT → Choose a renovation style: modern, coastal, luxury → It hands you a perfectly tuned image prompt → Paste it inside Calico along with the original photo → Generate the renovated room in seconds → Open Kling 3.0 (same platform, no switching tools) — set original as start, renovation as end → Generate the animation — the room transforms before your eyes Before to after. In a video. From one photo. Drop that into a listing, an ad, or a client walkthrough and watch what happens. Comment "RENOVATE" and I'll send you the exact GPT link, prompts, and workflow (must be following so I can DM you!).

David Roberts

34,599 görüntüleme • 3 ay önce

SHE CHARGES $7500 FOR A SITE YOU CONTROL BY WAVING AT YOUR WEBCAM no mouse, no scroll, no clicking anything, the camera tracks your hand and the whole site responds as you move it through the air how she built it: render the base clip in seedance 2 open replit and attach your design reference tell it to wire hand tracking with mediapipe map the hand position to the video in a single prompt still in the same chat, switch it to slide mode or a scroll transform whenever you want she never wrote one line of the tracking code, replit stood up the entire gesture layer from that one instruction meanwhile your local dev still thinks interactive means a button that lights up when the cursor grazes it the exact mediapipe prompt is in the guide below, save it before this becomes the standard
0:33

SHE CHARGES $7500 FOR A SITE YOU CONTROL BY WAVING AT YOUR WEBCAM no mouse, no scroll, no clicking anything, the camera tracks your hand and the whole site responds as you move it through the air how she built it: render the base clip in seedance 2 open replit and attach your design reference tell it to wire hand tracking with mediapipe map the hand position to the video in a single prompt still in the same chat, switch it to slide mode or a scroll transform whenever you want she never wrote one line of the tracking code, replit stood up the entire gesture layer from that one instruction meanwhile your local dev still thinks interactive means a button that lights up when the cursor grazes it the exact mediapipe prompt is in the guide below, save it before this becomes the standard

Bounce

53,405 görüntüleme • 7 gün önce

EVERYONE IS COPYING AI PROMPTS, BUT ALMOST NOBODY IS COPYING THE SYSTEM BEHIND THEM That is exactly why a small number of creators are generating millions of views while everyone else keeps wondering why the same prompts never work twice. 27 videos → 175,000 subscribers → Millions of views per upload ust a system and the patience to set it up once. The channel is about backyard bunker timelapses. Which sounds absurdly niche. And that's exactly why it works. It's the one content format where: the viewer literally cannot stop watching because they need to see it finished > ChatGPT generates the full construction blueprint, every phase, every prompt, in perfect sequence > Google Whisk creates the opening frame in 9:16 before a single video is generated > Grok animates each phase from the last frame of the previous clip, seamless continuity > the frame extractor is the secret, last frame of clip 1 becomes first frame of clip 2, every time > CapCut stitches it all together, and the raw construction sounds stay in because they're what hooks people
1:00

EVERYONE IS COPYING AI PROMPTS, BUT ALMOST NOBODY IS COPYING THE SYSTEM BEHIND THEM That is exactly why a small number of creators are generating millions of views while everyone else keeps wondering why the same prompts never work twice. 27 videos → 175,000 subscribers → Millions of views per upload ust a system and the patience to set it up once. The channel is about backyard bunker timelapses. Which sounds absurdly niche. And that's exactly why it works. It's the one content format where: the viewer literally cannot stop watching because they need to see it finished > ChatGPT generates the full construction blueprint, every phase, every prompt, in perfect sequence > Google Whisk creates the opening frame in 9:16 before a single video is generated > Grok animates each phase from the last frame of the previous clip, seamless continuity > the frame extractor is the secret, last frame of clip 1 becomes first frame of clip 2, every time > CapCut stitches it all together, and the raw construction sounds stay in because they're what hooks people

Shadow Nick

35,606 görüntüleme • 1 ay önce

What started as building a personal taste.md skill for myself, turned into building a pipeline to create any taste as a skill. The most important piece is references. This is where you should spend time. If the references suck, so does the skill. I find that references cropped tightly on details in high resolution work the best. Each image gets analyzed by both Opus 4.7 and GPT 5.5. The analysis is based on why the reference is successful as a piece of design - not what it does functionally. Using two models helps rule out biases and gaps from each. The models focus on layout, spacing, typography, rhythm, composition, hierarchy, etc. At the end, each image has: reference-01/ - opus-4-7-analysis.md - gpt-5-5-analysis.md Then we fuse them together using GPT 5.5 - but the md files are anonymized so 5.5 doesn't prefer itself. reference-01/ - fused-analysis.md reference-02/ - fused-analysis.md etc. After fusion, we have one synthesized analysis per reference. Now the goal is to combine all of those into a single rule set. This is where chunking matters. If you ask one model to combine 100 image analyses at once, the result becomes too broad. It summarizes instead of preserving the granular design rules we want. Instead we chunk the fused analyses into smaller groups. Each group gets merged into a chunk-level synthesis, usually from around 6 to 8 image notes at a time. Then one final model pass fuses those chunks into a single md rule set. Finally, using the rule set, we write a skill of concrete instructions. It enforces constraints, uses imperative wording, and avoids vague taste words.
3:43

What started as building a personal taste.md skill for myself, turned into building a pipeline to create any taste as a skill. The most important piece is references. This is where you should spend time. If the references suck, so does the skill. I find that references cropped tightly on details in high resolution work the best. Each image gets analyzed by both Opus 4.7 and GPT 5.5. The analysis is based on why the reference is successful as a piece of design - not what it does functionally. Using two models helps rule out biases and gaps from each. The models focus on layout, spacing, typography, rhythm, composition, hierarchy, etc. At the end, each image has: reference-01/ - opus-4-7-analysis.md - gpt-5-5-analysis.md Then we fuse them together using GPT 5.5 - but the md files are anonymized so 5.5 doesn't prefer itself. reference-01/ - fused-analysis.md reference-02/ - fused-analysis.md etc. After fusion, we have one synthesized analysis per reference. Now the goal is to combine all of those into a single rule set. This is where chunking matters. If you ask one model to combine 100 image analyses at once, the result becomes too broad. It summarizes instead of preserving the granular design rules we want. Instead we chunk the fused analyses into smaller groups. Each group gets merged into a chunk-level synthesis, usually from around 6 to 8 image notes at a time. Then one final model pass fuses those chunks into a single md rule set. Finally, using the rule set, we write a skill of concrete instructions. It enforces constraints, uses imperative wording, and avoids vague taste words.

Jaytel

55,377 görüntüleme • 1 ay önce