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A-TIER design

Let me know if you want this skill — This is a 90-second walkthrough of how to turn your taste into a...

rndyrbrts · 2026-05-11T22:32:16.000Z · in AI Saves, Vol. 7
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100k ft — What is this?

Let me know if you want this skill — This is a 90-second walkthrough of how to turn your taste into a...
designA-tier

50k ft — Why care?

Let me know if you want this skill.. — @rndyrbrts; demonstrates AI agents, prompt engineering.
LLMUI/UXagentsarchivesartcreative codingdesignreference

10k ft — Key takeaways

(no takeaways yet)

5k ft — Tools & techniques

(no tools tagged) AI agents, prompt engineering, workflow automation

1k ft — Deep-dive / try it

Let me know if you want this skill.. This is a 90-second walkthrough of how to turn your taste into a generative design system. The process is simple: Collect a moodboard. Extract the patterns. Tag the visual DNA. Write the philosophy behind it. Turn that into a structured atlas. Use an AI agent to generate new live interfaces from the rules. The point is not to copy reference images. The point is to extract the meta: color behavior, layout pressure, motion, density, texture, symbols, interface logic, emotional tone, and the worldview underneath the collection. Then you use that data to generate new artifacts that feel related to the source material without directly harvesting it. Taste -> data -> art. This is how I have been working with AI agents lately: not just prompting for ra…
Transcript excerpt
Ultra-fast breakdown of how I take a mood board that looks like this and turn it into a design system that generates code art that looks like this. This how you build a living, taste engine, a repeatable workflow, collect references, extract structure, map to DNA, generate interfaces, then mutate and critique. Start with a real mood board, put the 1000 one place, include screenshots, links, exports, notes, winners, rejects, and sentences about why each reference matters. Give the agent a contract, goal, context, and constraints and proof. The goal is what to build context as the archive proof means screenshots and paths empirical. Backed to import the archive into a manifest. One row, per artifact, title, source, local file type, dimensions, preview notes, and why it belongs. Next, measure what the eye is doing, palette, contrast, density, spacing, motion, texture, type, hierarchy, composition, and emotional pressure. Turn labels into rules, do not tag things as color futuristic, tag behavior, dense grid, quiet toolbar, radio, map scan, drift, caption stack. Cluster those tags into visual DNA channels. Each channel needs a recipe, a layout, motion, palette, density, interaction examples, and source ideas. Then write the thesis from evidence with the LLM, what is your archive value? What should the system always do? What should it never do? That becomes the constraint. Build the Alice before generating the art you need an index channel pages, relationship, view, detail,…

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Collection: AI Saves, Vol. 7