Mykhaylo 🇺🇦🌻

Lead Front-End Engineer @ Manulife 💻 Building design system libraries and tooling ✨

[Mykhaylo 🇺🇦🌻 @mryechkin]

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.

[Mykhaylo 🇺🇦🌻 @mryechkin]

@devongovett @opatrickgdl @devongovett where would I find this in the docs? There are no results when doing a search for that function – I'm curious what other hidden gems there may be?

[Mykhaylo 🇺🇦🌻 @mryechkin]

@kenwheeler Goddamn man, you gotta start putting an NSFW tag on these

[Mykhaylo 🇺🇦🌻 @mryechkin]

@rauchg

[Mykhaylo 🇺🇦🌻 @mryechkin]

@kenwheeler Kvas! 🤤👌

[Mykhaylo 🇺🇦🌻 @mryechkin]

@KevinVanCott @MaterialUI @mantinedev @shadcn @base_ui @radix_ui Awesome! 🥳 Thanks for confirming - looking forward to checking them out

[Mykhaylo 🇺🇦🌻 @mryechkin]

@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

[Mykhaylo 🇺🇦🌻 @mryechkin]

@devongovett @KevinVanCott @orlik03800930 @MaterialUI @mantinedev @shadcn @base_ui @radix_ui Can confirm, we're using v8 along with React Aria right now - it's working great so far, but it would be helpful to see official examples of the more complex features (eg. row expansion) of both libraries together.

[Mo @atmoio]

This is utterly fascinating. We’ve 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. It’s 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, “have I said the thing the prompt wants me to say?” 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 author’s head, and looks forward many sentences and paragraphs ahead to approximate the author’s intent.

It’s somewhat fuzzy. But I think LLMs fundamentally “think” in a much different way than humans. They are certainly not useless. But I think it’s a grave mistake to equate them with human intelligence.

[David K 🎹 @DavidKPiano]

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.

[Mykhaylo 🇺🇦🌻 @mryechkin]

@adamwathan Jesus man, that is scary 😨 Hopefully she’s OK and it’s nothing serious 🤞

[Out of Context Human Race @NoContextHumans]

I’ve never seen anything more accurate

[Mykhaylo 🇺🇦🌻 @mryechkin]

@AdamRackis @kenwheeler Agreed ☝️

[Mykhaylo 🇺🇦🌻 @mryechkin]

@vladmoroz 💯

[❖ Murphy @murphytrueman]

New post!

https://t.co/K5vbZskbpj

[Mykhaylo 🇺🇦🌻 @mryechkin]

@devongovett TIL! 💡

[Product Hunt 😸 @ProductHunt]

holy sh*t they actually did it

[Mykhaylo 🇺🇦🌻 @mryechkin]

@devongovett This is huge! Appreciate the work you guys have put into this 🙌

[Thariq @trq212]

https://t.co/45C3gKydTK