Reviews/EDUCATION/How LLMs Work
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How LLMs Work

Andrej Karpathy's LLM lecture, rebuilt as an interactive visual experience

PriceFreeReviewed2026-04-24
Verdict — Ship
3 Ships1 Skips
Visit ynarwal.github.io

The Panel's Take

"How LLMs Work" is a free, browser-based interactive guide that walks through the complete pipeline for building large language models — from raw web scraping to RLHF-trained conversational assistant. Created by Yash Narwal and based on Andrej Karpathy's technical deep-dive lecture, it's been getting significant traction on Hacker News (214+ points) for turning dense ML theory into something genuinely accessible. The site covers data collection and deduplication, Byte Pair Encoding tokenization with a live demo, pre-training and next-token prediction, inference with a probability sampling simulator, post-training with RLHF, and RAG. Each section uses animated visualizations, clickable pipeline diagrams, and canvas-based graphics — not static explainer images. The progressive narrative structure follows a single piece of text through every stage of the pipeline, making abstract concepts concrete. In an era where everyone uses LLMs but few understand how they work, this kind of high-quality educational resource matters for a different reason than tools: it raises the baseline competency of the entire developer ecosystem. Better-informed builders ask better questions, make better design decisions, and push vendors toward more transparency. This is the kind of project the HN community rewards — and deserves the signal boost.

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How LLMs Work verdict: SHIP 🚀

3 ships · 1 skip from the expert panel

Full review: shiporskip.io/tool/how-llms-work-interactive-visual-karpathy-educational-2026

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Ship · 7.5/10
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The reviews

Best visual explanation of tokenization I've seen — the live BPE demo finally made it click for me after years of reading static diagrams. Bookmarked for onboarding new engineers and explaining RAG to non-technical stakeholders.

Helpful?

It's a beautiful explainer, but Karpathy's own YouTube lectures already do this and go deeper. Building on someone else's lecture without significant original contribution is fine, but 'Ship or Skip' implies you'd use it now — this is more bookmark-and-forget.

Helpful?

The gap between AI capability and public understanding is the single biggest risk factor for good AI policy. Tools like this that translate technical reality into accessible visuals are infrastructure for an informed society — more important than most 'real' tools.

Helpful?

The scroll-based animation and progressive reveals are exactly how technical content should be designed. Whoever built this UX understands both pedagogy and web craft — it's a masterclass in making complex systems legible through thoughtful visual design.

Helpful?

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