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OnSystem.Design

Drop-in components for the screens AI builds badly

We audited 11 real apps built with AI coding tools. Nearly all broke the same six ways: decorative color, numbers that don't reconcile, no empty states. OnSystem is three React + Tailwind kits built to make those failures structurally impossible.

Top comment

Hey Product Hunt, A few months ago I wanted to know what "AI-built software looks off" actually means. Not as a vibe, as a list. So I audited 11 real apps that other people built with v0 and published to its public gallery. Not toy demos: apps with hundreds of forks and likes. I opened every one, clicked through every screen, and wrote down exactly what broke. I expected the problems to be scattered. They weren't. The same handful of failures showed up over and over, in apps that had nothing to do with each other: - Color picked for variety instead of meaning. One app showed the identical fake "+4.5%" next to all three stocks in a "biggest daily movers" list, regardless of which way they actually moved. - Numbers that don't agree with themselves. One account card rendered "$34,280.56" and "$1376.98" one field apart. Same card, same currency, two different formatting rules. - No states besides the happy path. Five of six internal-tools apps showed sample data forever, with no evidence they'd ever rendered a loading, empty, or error state. - A trading chart whose own author noted it "only animates the last data point," dressed as live data, disclosed nowhere on screen. None of these are broken logic. The totals compute, the forms submit. What's missing is the layer that decides what a visual choice means, and nothing in the generation process makes that structural. It's up to whichever prompt happened to ask for it, on whichever screen someone remembered to ask. That's a component-library problem, not a prompting problem. You fix it once at the level of the building blocks, or you fix it forever, once per screen. So that's what OnSystem is. Three kits, one for each vertical I audited: Internal Tools, Fintech, E-commerce. Every kit routes color through five semantic roles, shares one set of currency and percent formatters, ships loading and empty and error states as defaults rather than afterthoughts, and includes a live-vs-demo badge for anything claiming to be real time. Installs with npx shadcn add, or you can just ask your assistant, since the registry is MCP-ready. To be straight about what this is: it's a paid component kit, one-time purchase, no subscription and no free tier right now. Everything is clickable before you buy at demo.onsystem.design, and the full audit with screenshots is at onsystem.design/blog. What I'd genuinely like feedback on: does the vertical split hold up? I picked internal tools, fintech, and e-commerce because that's where the audit evidence was densest, but I'd like to hear which screen types keep breaking for you. If there's a fourth vertical hiding in the replies, I'd rather find it here than guess. And if you've shipped a screen with a fake delta or a "live" badge on static data, no judgment. It's what the tools do by default.

About OnSystem.Design on Product Hunt

Drop-in components for the screens AI builds badly

OnSystem.Design was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #158 on the daily leaderboard. We audited 11 real apps built with AI coding tools. Nearly all broke the same six ways: decorative color, numbers that don't reconcile, no empty states. OnSystem is three React + Tailwind kits built to make those failures structurally impossible.

On the analytics side, OnSystem.Design competes within Design Tools, User Experience and Developer Tools — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how OnSystem.Design performed against the three products that launched closest to it on the same day.

Who hunted OnSystem.Design?

OnSystem.Design was hunted by Ryan Nance. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of OnSystem.Design including community comment highlights and product details, visit the product overview.