Claude Opus 4.8 Generates an Animation of How an LLM Works in One Shot

Melvin Vivas · X video post · 2026-05-28 · 0:11 · 1,544 views · Open on X

Topics: AI Dev Tools & Productivity, LLM Fundamentals · Level: beginner

Summary

An 11-second X video with no narration. It shows an animation of how a large language model works, which Claude Opus 4.8 reportedly made from a single prompt ("one-shotted"). The post shows what the model can do and that LLMs can be used to make visual explainers, but it doesn't share the prompt, the code or the method. You can't get a technical lesson out of it without watching the animation itself.

Key points

• The creator says Claude Opus 4.8 produced the whole 'how an LLM works' animation from one prompt, with no back-and-forth.
• The video is 11 seconds long and has no speech, so nothing about how LLMs work is explained out loud.
• The post doesn't share the prompt, the generated code or the tools used to render the animation.
• The caption link points to an X post by DonvitoAI with the same status ID as this post. It's probably just the link to the post's own video.
• Takeaway: frontier coding models can turn a concept into an animated visual explainer, which can help you study or teach LLM basics.

Resources mentioned

• Claude Opus 5.5 · tool · claude.ai · paid · open in a browser to verify · recommended by both Bashiri Smith & Melvin Vivas
  Anthropic's AI assistant, used throughout the guide to tailor resumes, add live roles to the tracker, match connections to target companies and find hiring managers.
  Also in: Generating a Repo Promo Video with a Claude Skill on Sonnet 5.5 vs Opus 5.5 (Melvin Vivas on X · notes), Comparing Coding Models on the Same Task in Devin iOS (Melvin Vivas on X · notes), Customizing Your Coding Setup with Pi Coding Agent Extensions (Melvin Vivas on X · notes), AI Engineer Roadmap Overview: From ML Foundations to RAG, Agents & Ops (Bashiri Smith on Facebook · notes) and 53 more
• X post by DonvitoAI: animation of how an LLM works · video · x.com · free
  The linked X post with the short animation that shows how an LLM works.

Try this

• Ask a coding model like Claude to build an animated explainer of the LLM pipeline (tokenization → embeddings → attention → next-token prediction), then check that each step is accurate.