🌱 AI Engineering · How LLMs Work (Visual First) · cozy lesson

Transformer Architecture Simplified

14 min · 1 min read · no scary math, promise

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You’ve got this. Read a little, play a little — I’ll wait. No rush.

LEGO stack

Tokens → embeddings + positions → N× [attention → MLP] → next-token head.

Play /animations/attention: query·key scores → weighted values. Multi-head = several views at once. KV-cache reuses past keys for speed.

You don’t need to derive softmax to use LLMs. Remember: context mixing + depth.

Correct answers earn XP (once each).

1. Self-attention does…

2. Transformer block =

Select text above → Save selection, or write your own. AlgoMaster-style notebook, local-first for MVP.

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The checkbox in the explorer turns green too — same progress.