Last week @figma announced exciting new features at #Schema2025, and like many others in the design systems community, I was thrilled to hear about them. In this post, I focus on #DTCG@DesignTokens spec reaching stable status - and how Figma helps integrate it into your work.
@devongovett@opatrickgdl@devongovett where would I find this in the docs? There are no results when doing a search for that function โ I'm curious what other hidden gems there may be?
@arzatskis@tan_stack@devongovett +1 I'd love to see more official documentation on using both of those libraries together - especially the more complex features
This is utterly fascinating. Weโve known code written by AI is harder to untangle. It appears this is the case with writing as well.
Tricia is an editor and she says that when an author submits work that is written by AI, she has a much harder time editing it. Itโs all one interconnected black-box piece of writing that is not amenable to change. Whereas she finds that human writing, while seemingly messier, is actually much more structurally straightforward.
My theory as to why this is is that LLMs think one token at a time. And after every token, they essentially look back and ask, โhave I said the thing the prompt wants me to say?โ If not, it keeps elucidating.
The result is tight chain of thought writing that requires each preceding token to make sense of the next.
Whereas human writing starts from a pre-language idea in the authorโs head, and looks forward many sentences and paragraphs ahead to approximate the authorโs intent.
Itโs somewhat fuzzy. But I think LLMs fundamentally โthinkโ in a much different way than humans. They are certainly not useless. But I think itโs a grave mistake to equate them with human intelligence.
USERS care if code is messy.
They care if the app is buggy. Or slow. Or if the UX is frustrating. Or if important features are missing or broken.
These are downstream effects of messy, unmaintainable code.