Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star git...
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I'm usually the one asking Claude to "just build a UI that doesn't suck," and that's usually about as good as it gets 🤣 This at least gives me a direction to give it much better than my default. I'll definitely be checking out the tools you mentioned, too. Thanks for the great overview!
Haha, lemme know how it goes xD @anchildress1
Solid frontend write-up. If anyone needs quick AI image tools (background removal, headshots, product photos), we built a free suite at tools.shopveigo.com. All browser-based, no signup needed for most tools.
Aightt
Appreciate the nod. Since you are keeping up with the AI tooling space, I am curious how you handle style consistency when feeding generated assets into your frontend components. It seems like the hardest part of giving AI actual taste is maintaining a unified design system.
Solid frontend architecture. In production, I'd add that proper asset loading strategy (code splitting, resource hints, and responsive images with srcset) often makes a bigger performance difference than any single CSS optimization.
Cool
Since you agree on the architecture side, I am curious about the design aspect. It really highlights how much manual refinement is still needed to give AI-generated layouts actual taste. Have you found any specific workflows that help bridge that gap between raw AI output and a polished frontend?
Exactly. The real challenge is bridging the gap between what the AI designs and what the browser can actually render efficiently without bloating the bundle. Are you currently using any specific build tools to automatically optimize those AI-generated assets?
The three moves framing is right: taste is upstream of tools, not a prompt you bolt on at the end. The part that still bites is that agents will happily "polish" a page into the same statistical average you were trying to leave, so the critique pass has to name concrete rejects (Inter everywhere, purple gradients, a hero that could sell any SaaS) the way Impeccable does. When I review agent UI work I treat the CSS and layout hunks as the surface that matters, not the summary that says "modern and clean." If those hunks look like every other landing page, the session was not done.
Impeccable for the save :D
Core Summary: Functional AI code isn't enough; AI needs explicit design guidelines. By loading structured design skills and tokens into your AI tools, you can force coding agents to generate distinct, production-ready interfaces with actual taste.
Yeah
Small plumbing note before anyone wires an image MCP into Claude Code: when a tool of mine returned images to the CLI, the image blocks didn't land, so I ended up writing the PNG to a temp dir and handing back the path as text. Which is fine for the loop you describe, since you're the one eyeballing the four hero options anyway. It's the step after that gets awkward, when you want the agent to compare its own output and it actually needs to see the page.
Got it, thanks @valentin_monteiro
The "mathematical average of the training distribution" framing is exactly right — it does not stop at CSS. We hit the same wall building an AI video generator: outputs were technically fine but perceptually mediocre because "good music video aesthetic" is buried under the statistical center of every mid YouTube video uploaded.
Same fix worked: we built a reference library of annotated clips we liked and injected them as few shot examples at generation time. The model output shifted noticeably. Not because the model got better, but because we gave it a different center to regress toward.
What is your approach for keeping the taste library fresh? Ours drifted toward what the team already liked, which is its own kind of slop.
I learned so much with your post, thank you for sharing!
Thanks V <3
Good CSS/HTML coverage. The landscape here moves quickly — worth noting that container queries and :has() selector support have reached baseline, which can simplify many of the responsive patterns we previously needed JS for.
This made me realize how often I blame the AI for generic design when my prompt was literally just make it modern.