I built a gamified coding app in Flowstep this week. 18 screens. Here's the part nobody posts. Br...I built a gamified coding app in Flowstep this week. 18 screens. Here's the part nobody posts. Br...
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I built a gamified coding app in Flowstep this week. 18 screens. Here's the part nobody posts.
Bracket is a learn-to-code app built on language-app mechanics — streaks, XP, hearts, a winding skill path — across HTML, CSS, Python, JavaScript, C++, Java and SQL.
I generated every screen by connecting Flowstep's MCP to Claude. No Figma file, no pixel-pushing.
But "prompt it and it appears" is not what happened.
What actually happened: I set design guidelines at the file level first — colour, type, screen chrome, motion — so all 18 screens inherited one system. Then I generated. Then I read the code of what came back, and found what had drifted. Borders set to 1% opacity, invisible. Text left near-white on a white background. A button stuck permanently in its pressed state. A screen I was told existed that didn't, and one I thought was missing that was there all along.
None of that showed up in a preview. It only showed up in the markup.
This is the junior-employee-versus-senior-collaborator thing I keep coming back to. AI executed 18 screens faster than I could have drawn three. It did not know that neon lime on white is 1.4:1 contrast and unreadable — that's why Bracket's light mode uses warm paper instead of white, and why the neons became fills and borders, never text. That call was mine. The judgment checkpoints are the job.
The flow, if you want to tap through it:
Launch → Intro → Create Account → Choose Language → Path → Lesson → Correct → Lesson Complete → back to Path.
Plus the branch most learning apps quietly skip: wrong answer → heart lost → out of hearts → practice to earn one back. A learning app that only demos its happy path isn't showing the interesting half.
Navigation is wired element by element on the canvas. Every button, link and tab icon has its own destination, so it runs like an app instead of a slideshow.
Built for the @Flowstep x @Contra HQ challenge.
Tools used: Flowstep X @Claude.ai
Same pattern holds in outbound tooling. Filtering, dedupe and enrichment lookups are plain code. The model only writes the first line once the row is already verified. Cuts cost and the weird outputs.
spot the fake being the one that sticks makes sense, catching grown-ups out is the best game there is. one build question. do kids need an account, or does progress live on the device? no-login is usually the hardest part of a kids product and the part parents actually check.
An AI content bot for IspFlow. It writes posts from live product numbers and Nigerian/Kenyan trends, designs X cards and TikTok videos in five rotating looks from a library of real app screens, adds voice, captions and sound, and sends each draft to Telegram for one-tap approval. It learns from what gets approved or skipped.
I'd separate a timing skip from a content rejection in that learning loop. Does Telegram capture why a draft was skipped, so an otherwise good format doesn't get penalized just because it wasn't the right day to publish?