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We taught Framer’s Agent to design in 3D. It coordinates perspective, depth, rotations, animations, and more across every axis, while keeping every layer editable on the canvas. We found Opus 5 to be especially great at this.

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Framer

202,084 subscribers

14,515 просмотров • 9 дней назад •via X (Twitter)

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We just released Turntable in Illustrator for everyone 🎉 You can rotate 2D vector art in 3D. Place all frames on canvas. Great for animations and game design. No Redrawing, just drag the slider and done!
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We just released Turntable in Illustrator for everyone 🎉 You can rotate 2D vector art in 3D. Place all frames on canvas. Great for animations and game design. No Redrawing, just drag the slider and done!

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This model is insane at 3D website design. I asked GLM 5.3 (left) & Fable 5 (right) to make me a 3d biking website. GLM nailed it while Fable failed. GLM cost $0.14 while Fable cost $2.21. More than 15x cheaper while being even better in this case!

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An OpenAI engineer stopped me at a hackathon in Hayes Valley I had my terminal open on a table. Three panels. Live trades scrolling. He was walking past and froze. "That's not a demo. That's a live scoring engine. What model is that" I told him. Claude Opus 4.7. Four repos. $25 a month. He pulled up a chair without asking. "We benchmarked Opus 4.7 internally. It beat o3 on structured reasoning across every eval we ran. And you're telling me you're using it to trade" I told him it does more than trade. It reads 86 million trades and finds who wins and why. No fine-tuning. No prompting chains. Just raw context. He leaned back. "Show me the data source" I opened one link. 86 million trades. Every wallet. Every entry. Every exit. "You point Opus 4.7 at this and it reverse-engineers the strategy. It finds the wallets that win. Then it finds why they win. Then it copies the pattern" His team spent 14 months building something similar. 10 engineers. Custom infra. Still in staging. "The part that killed us was exit timing. Every model we trained nailed entries. But the best traders exit before the crowd. We never figured out the threshold" I told him my bot cuts at 85% of expected move. Or on a 3x volume spike. Whichever comes first. He stopped talking. "How did you find that" Opus 4.7 found it in poly_data. Top wallets exit before resolution 86% of the time. Losers hold to 58%. Exits are the entire game. I opened another tab. "Three commands. 500 markets. Opus scores them in 20 minutes" "That's our internal eval pipeline. Except it took us a year and you did it in a weekend with our competitor's model" My setup: Claude Opus 4.7 - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 214 trades. 74% win rate. +$9,400 in 19 days. Copytrade here: I showed him the article where I broke down every repo and every command. He read it twice. Then looked up. "You just published what we've been trying to ship for six months. Using the other team's model" He texted me the next day. "My manager found your thread. Delete it" Too late.
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An OpenAI engineer stopped me at a hackathon in Hayes Valley I had my terminal open on a table. Three panels. Live trades scrolling. He was walking past and froze. "That's not a demo. That's a live scoring engine. What model is that" I told him. Claude Opus 4.7. Four repos. $25 a month. He pulled up a chair without asking. "We benchmarked Opus 4.7 internally. It beat o3 on structured reasoning across every eval we ran. And you're telling me you're using it to trade" I told him it does more than trade. It reads 86 million trades and finds who wins and why. No fine-tuning. No prompting chains. Just raw context. He leaned back. "Show me the data source" I opened one link. 86 million trades. Every wallet. Every entry. Every exit. "You point Opus 4.7 at this and it reverse-engineers the strategy. It finds the wallets that win. Then it finds why they win. Then it copies the pattern" His team spent 14 months building something similar. 10 engineers. Custom infra. Still in staging. "The part that killed us was exit timing. Every model we trained nailed entries. But the best traders exit before the crowd. We never figured out the threshold" I told him my bot cuts at 85% of expected move. Or on a 3x volume spike. Whichever comes first. He stopped talking. "How did you find that" Opus 4.7 found it in poly_data. Top wallets exit before resolution 86% of the time. Losers hold to 58%. Exits are the entire game. I opened another tab. "Three commands. 500 markets. Opus scores them in 20 minutes" "That's our internal eval pipeline. Except it took us a year and you did it in a weekend with our competitor's model" My setup: Claude Opus 4.7 - $20/mo VPS - $5/mo poly_data - free polymarket-cli - free 214 trades. 74% win rate. +$9,400 in 19 days. Copytrade here: I showed him the article where I broke down every repo and every command. He read it twice. Then looked up. "You just published what we've been trying to ship for six months. Using the other team's model" He texted me the next day. "My manager found your thread. Delete it" Too late.

Lunar

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I found 9 sites that generate Design Markdown files for your AI builds ! here are the links: - - - - - - - - They help turn your visual direction into an actual design system your coding agent can follow. typography, colors, spacing, radius, shadows, components, states and responsive behaviour. before you build any screen, pick a visual direction and generate the design .md file aligned with your product mechanics and outcome goals add it to Claude Code or Cursor, then use /design to describe what should stay consistent across every screen this gives the agent actual constraints instead of asking it to “make the UI look premium” and hoping for a good output you'll ship much cleaner product ideations at lightning fast speed ! ( this and a folder of 5-6 visual references are the first things we prepare before starting a client build )
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I found 9 sites that generate Design Markdown files for your AI builds ! here are the links: - - - - - - - - They help turn your visual direction into an actual design system your coding agent can follow. typography, colors, spacing, radius, shadows, components, states and responsive behaviour. before you build any screen, pick a visual direction and generate the design .md file aligned with your product mechanics and outcome goals add it to Claude Code or Cursor, then use /design to describe what should stay consistent across every screen this gives the agent actual constraints instead of asking it to “make the UI look premium” and hoping for a good output you'll ship much cleaner product ideations at lightning fast speed ! ( this and a folder of 5-6 visual references are the first things we prepare before starting a client build )

Harshil Tomar

77,811 просмотров • 4 дней назад