What is WCAG contrast and why do product companies ask it?
PICTURE THIS: A SENTENCE BECOMES TOKENS
The model does not read letters like humans. It reads these pieces, then predicts the next one.
Simple meaning
Text needs enough contrast against its background so low-vision users can read it, with stricter ratios for small text.
WHY — Accessibility instead of guessing?
Why interviewers care about Accessibility:
who only read docs from people who shipped.
and tied to Frontend work.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens with tokens?
Before the model can read a sentence, it goes through these steps:
- 1Text needs enough contrast
against its background so low-vision users can read it, with stricter ratios for small text.
- 2Design tokens should be
checked, not guessed from a pretty palette.
- 3Legal risk and App
Store reviews make this a real product requirement, not a nice-to-have.
- 4Context mix
Attention looks at nearby tokens together.
- 5Next token
The model scores what should come next.
- 6Decode
IDs turn back into readable text.
EXAMPLE — See it in action
Let's see how a real sentence is tokenized (tokens may vary by model):
Note: Actual tokens and IDs depend on the tokenizer (e.g., GPT, Llama, etc.).
Key takeaway
Text needs enough contrast against its background so low-vision users can read it, with stricter ratios for small text. Design tokens should be checked, not guessed from a pretty palette.