Introduction - React Three Fiber
https://r3f.docs.pmnd.rs/getting-started/introduction
https://r3f.docs.pmnd.rs/getting-started/introduction
spend a few weeks learning about loops to run several agents while I sleep, treat AI like a workforce.
Three.js adapter | Adapters | Documentation | Anime.js | JavaScript Animation Engine
https://animejs.com/documentation/adapters/threejs-adapter/
https://animejs.com/documentation/adapters/threejs-adapter/
Animejs
Three.js adapter | Adapters | Documentation | Anime.js | JavaScript Animation Engine
A fast, multipurpose and lightweight JavaScript animation library
The basic idea is easy and v0 is a hackathon project. The product here is a lot closer to *it actually works*, for enterprise grade deployments, and after quite a bit of internal experimentation and iteration. It’s kind of hard to describe other than (per the post) it’s writing majority of code, it’s deeply integrated, multiplayer, and it starts to feel like everyone is a manager. So I understand it looks easy to dismiss on quick reading but it’s not some LLM Q&A with RAG over Slack, it’s not even OpenClaw adjacent, it’s a different way of working entirely, for people and teams. I work from Slack now.
Game theory pretty much proves that the long game is not a strategy most people can execute at all. That's because it tends to require a negative short-term position in exchange for a real advantage later. Most people cannot commit to this because their threat-detection system reads current loss as an existential failure. And that's vicious short-sightedness. It leads them to optimize for visible progress and sacrifice their real position. The people who constantly win rarely have better information. Instead, they accept that losing now will pay off later. Never quit a game before it starts.