Token Shredder
Type a word, watch AI shred it into tokens.
The 'why AI can't spell' reveal: proves, on the learner's own typed word, that the model operates on opaque token IDs, not letters -- the mechanism behind a famous, real failure mode, not a claim about it.
What goes in, what comes out
Learner types any text and it splits live into color-coded token chips, each labeled with its numeric ID as the model itself would see it. A side-by-side 'letter view' shows the same text as individual characters, so the gap between what a human reads and what the model actually receives is visible at a glance, not asserted.
Free text typed or pasted by the learner (or one of three preset 'gotcha' strings, incl. 'strawberry').
A color-chunked token strip, live token count, per-1K-token cost estimate, and a one-line reveal of why the model can't count letters in a word it never sees as letters.
Tokenizer/model-family selector; language toggle (English vs Hindi/Tamil/Spanish to expose non-English token bloat); show/hide token IDs; running token-count and estimated-cost readout.
Free lead magnet at /playgrounds and embedded on resource/blog pages (GEO/SEO); paired demo inside AIE-101's opening tokens-and-vocabulary lesson.
Go deeper, elsewhere
Hand-picked public explainers and open tools that complement this one — always optional, never required, never graded.
Concepts click when you open the machinery.
Three labs are already live and free — the same hands-on style this playground brings to its module.