SWE-bench Verified: state-of-the-art. This benchmark tests real software engineering. Actual GitHub issues that require multi-file edits, testing, dependency management. Sonnet 4.5 leads the leaderboard. It maintains focus for 30+ hours on complex tasks.
@godofprompt
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Anthropic’s Sonnet 4.5: A Coding Breakthrough
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Anthropic dropped Sonnet 4.5 today. It's the best coding model in the world. Same price as Sonnet 4. But the capabilities gap is massive. This isn't incremental. It's a different category of reasoning.
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Three.js 3D Environment with Camera Controls
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2. Three.js 3D environment
— God of Prompt (@godofprompt) 30 septembre 2025
Requested an interactive 3D site with camera controls.
Claude generated a rotating, zoomable cube with ambient lighting and responsive canvas.
That's production-grade Three.js from a single prompt. Most devs still copy-paste examples for this. pic.twitter.com/q73JEZdeXR2. Three.js 3D environment Requested an interactive 3D site with camera controls. Claude generated a rotating, zoomable cube with ambient lighting and responsive canvas. That's production-grade Three.js from a single prompt. Most devs still copy-paste examples for this.
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Claude 4.5 Sonnet: 3 Quick Projects
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Claude 4.5 Sonnet is insanely powerful 🤯
— God of Prompt (@godofprompt) 30 septembre 2025
Here are 3 projects I made in it in few seconds:
1. Retro Snake in pure JavaScript pic.twitter.com/VTkTERWuTmClaude 4.5 Sonnet is insanely powerful Here are 3 projects I made in it in few seconds: 1. Retro Snake in pure JavaScript
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AI Coding Assistants’ Hidden Delivery Stability Drop
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Everyone's celebrating AI coding assistants, but nobody's talking about the 7.2% drop in delivery stability that comes with them. DORA just dropped a bombshell report on generative AI in software development, and the findings are way more complicated than the hype suggests. The
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AI creativity is architecture, not imagination
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people think ai creativity is magic. it paints, writes, composes – so we assume it’s “thinking” like us. but that’s not what’s happening under the hood. researchers recently showed that creativity in models comes from architecture, not imagination. the wiring matters more than
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AI’s creativity stems from pattern recognition
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ai doesn’t create because it “wants to.” it creates because we wired it to notice patterns. architectural choices like locality and equivariance force the model to capture structure in the data. that’s why it can remix old knowledge into something that looks new. creativity in
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Building an AI-Powered Lead Generation Workflow in n8n
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Watch Ben build my lead generation workflow in n8n New YT video dropped
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Using XML to improve Claude model performance
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XML is a great way to get best results from Claude