Point your AI agent at any website. Get back a complete design breakdown — colors, type, spacing, and the reasoning behind every decision — ready to use in your next build.
Thanks for all the support on Taste Lab. A lot of you used it to pull the visual DNA out of websites you love.
But I kept running into the next problem. Even with the right visual style, an AI-built page can still feel off, because the agent doesn't know what belongs on the page, in what order, or why.
The extractor used to be all-or-nothing: if one part failed, everything failed. Now each section runs independently if button detection breaks on a weird site, you still get colors, typography, and everything else. The report tells you which parts degraded so you know what to trust.
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This hits a real pain. Telling an AI agent to build "in the style of X" almost always loses the spacing and type scale. The clever part is capturing the reasoning behind each design choice, not just the raw tokens. Can it export to a Tailwind config or design tokens I can drop straight into a build? Congrats on shipping.
“Design DNA” is a useful way to package what builders often struggle to describe. Colors and type are helpful, but the reasoning behind decisions is the really valuable part. Can it compare multiple reference sites and synthesize a direction?
Great launch Sen! Extracting a website's design DNA is such a useful tool for designers who want to understand the visual language behind great sites. Does Taste Lab break down things like spacing systems and typography scales, or is it focused more on color palette and imagery?
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@sunlinsen Congratulations, I like that this focuses on the reasoning behind the design, not just extracting colors and fonts. For AI-built interfaces, understanding why a layout works is much more useful than copying surface-level style tokens.
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I like that Taste Lab explains the reasoning behind visual choices, not just colors and fonts. For AI-built frontends, that context could help avoid generic-looking pages. Would be interesting to see how it handles sites with several design systems.
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It would be useful if the AI could also highlight where those standards are not being followed. Usually, you create a design, hand it over to the client, and then they start changing fonts, spacing, or other elements, and everything gradually falls apart.
Manually finding those inconsistencies takes a lot of time. An automated system that could detect and flag such issues would be fantastic.
This hits a real pain. Telling an AI agent to build "in the style of X" almost always loses the spacing and type scale. The clever part is capturing the reasoning behind each design choice, not just the raw tokens. Can it export to a Tailwind config or design tokens I can drop straight into a build? Congrats on shipping.
“Design DNA” is a useful way to package what builders often struggle to describe. Colors and type are helpful, but the reasoning behind decisions is the really valuable part. Can it compare multiple reference sites and synthesize a direction?
Great launch Sen! Extracting a website's design DNA is such a useful tool for designers who want to understand the visual language behind great sites. Does Taste Lab break down things like spacing systems and typography scales, or is it focused more on color palette and imagery?
@sunlinsen Congratulations, I like that this focuses on the reasoning behind the design, not just extracting colors and fonts. For AI-built interfaces, understanding why a layout works is much more useful than copying surface-level style tokens.
I like that Taste Lab explains the reasoning behind visual choices, not just colors and fonts. For AI-built frontends, that context could help avoid generic-looking pages. Would be interesting to see how it handles sites with several design systems.
It would be useful if the AI could also highlight where those standards are not being followed. Usually, you create a design, hand it over to the client, and then they start changing fonts, spacing, or other elements, and everything gradually falls apart.
Manually finding those inconsistencies takes a lot of time. An automated system that could detect and flag such issues would be fantastic.
Love this! Which coding tool integration with Taste Lab do you recommend the most? Which one do you enjoy using?