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Jaytel

@Jaytel6,287 subscribers

Design Studio @Shopify, prev co-founder of https://t.co/VDEWznCnn2 (acq by Shopify), and design at Apple

Shorts

So many R&D artifacts (motion, code, and origami) came out of this project, we had to build our own internal software for organizing, reviewing, and presenting them But that's a post for another time...

So many R&D artifacts (motion, code, and origami) came out of this project, we had to build our own internal software for organizing, reviewing, and presenting them But that's a post for another time...

42,814 Aufrufe

A few of my (mini) favorite moments from our new Shop Minis site we launched today.

A few of my (mini) favorite moments from our new Shop Minis site we launched today.

43,845 Aufrufe

If you can't make a decision, ask Cursor to make you a quiz. I've found this helpful when dealing with a lot of variables in a project - I can go through (pressing Y or N keys) and see/compare results at the end. This example, I needed to compare three different sans across length and scale.

If you can't make a decision, ask Cursor to make you a quiz. I've found this helpful when dealing with a lot of variables in a project - I can go through (pressing Y or N keys) and see/compare results at the end. This example, I needed to compare three different sans across length and scale.

15,750 Aufrufe

claude code can't, Yaël Bienenstock can

claude code can't, Yaël Bienenstock can

10,998 Aufrufe

Videos

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What started as building a personal taste.md skill for myself, turned into building a pipeline to create any taste as a skill. The most important piece is references. This is where you should spend time. If the references suck, so does the skill. I find that references cropped tightly on details in high resolution work the best. Each image gets analyzed by both Opus 4.7 and GPT 5.5. The analysis is based on why the reference is successful as a piece of design - not what it does functionally. Using two models helps rule out biases and gaps from each. The models focus on layout, spacing, typography, rhythm, composition, hierarchy, etc. At the end, each image has: reference-01/ - opus-4-7-analysis.md - gpt-5-5-analysis.md Then we fuse them together using GPT 5.5 - but the md files are anonymized so 5.5 doesn't prefer itself. reference-01/ - fused-analysis.md reference-02/ - fused-analysis.md etc. After fusion, we have one synthesized analysis per reference. Now the goal is to combine all of those into a single rule set. This is where chunking matters. If you ask one model to combine 100 image analyses at once, the result becomes too broad. It summarizes instead of preserving the granular design rules we want. Instead we chunk the fused analyses into smaller groups. Each group gets merged into a chunk-level synthesis, usually from around 6 to 8 image notes at a time. Then one final model pass fuses those chunks into a single md rule set. Finally, using the rule set, we write a skill of concrete instructions. It enforces constraints, uses imperative wording, and avoids vague taste words.

Jaytel

54,721 Aufrufe • vor 11 Tagen

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Inspect element never looked so good

Jaytel

115,188 Aufrufe • vor 2 Monaten

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Surely this can't go wrong...

Jaytel

129,893 Aufrufe • vor 5 Monaten

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