I run ARLing s. r. o. out of Bratislava. It's a one-person company: I'm 22, I can't write code, and most of what gets built is written by AI. Three days ago I decided to test how far that setup could go if I pushed it hard: pick real problems, ship free tools that fix them, and see what happens.
This is not a growth story. After 48 hours the tools have a few dozen visitors each, no email signups, and one paid sale that happened today, the first day a paid product existed. I'm writing it anyway because the build side worked better than I expected, and the numbers are worth being honest about.
Written with AI assistance and published by me. Numbers are from my own self-hosted analytics.
What got built
Over three days, 14 pages went live on arling.sk:
- 8 "doctor" tools, each diagnosing one specific, common error: an Expo plus Supabase redirect problem, a Supabase web redirect issue, a Flutter deep link issue, Universal Links setup, Google OAuth redirect errors, SEPA payment file errors, a Stripe webhook checker, and one more.
- SEPA Generator Pro, a paid tool built with Stripe, for accountants who need to produce SEPA payment files.
- A beta of a book club app (bookapp).
- Docs, notes, a privacy page, and a "how we work" page.
The first tool, a redirect checker for Expo and Supabase apps, went from idea to live page in about 4 hours on day one. Two more tools followed the same day. On day two, three more tools came out of a single 30 minute build workflow, along with the bookapp beta. Day three added two more tools plus the Stripe based generator.
How the work actually splits
I don't write code. What I do is decide which problems are worth a tool, answer the people who show up, and say no to ideas that don't fit. Claude agents write the code, the tests, the pages, and the technical hygiene: robots.txt, sitemap, structured data.
The setup underneath: one orchestrator model plans a tool, then cheaper models build and verify the pieces in parallel. A typical tool uses three agents, one for the engine and UI, one for hygiene and launch notes, one for tests. Each tool runs entirely in the browser, nothing gets uploaded anywhere, and every rule a tool checks against is cited to the official documentation it comes from. Test counts per tool, across the eight doctor tools: 52, 87, 94, 106, 125, 108, 125, 178 automated tests.
The design mistake
The first version of every page looked the same: dark background, orange gradient buttons, everything in cards. It's a recognizable look at this point, generic AI output. I looked at it and called it AI slop. So every page got rebuilt on day two: a light, typographic layout, real screenshots instead of icons and cards, plain sentences instead of the usual AI writing tics. It meant redoing pages that already worked, but the result reads like something a person made on purpose, not a template.
The numbers, 48 hours in
Unique visitors, from self-hosted Umami analytics, no cookies:
| Tool | Unique visitors |
|---|---|
| Expo redirect doctor | 31 |
| Hub (arling.sk) | 24 |
| bookapp beta | 20 |
| Web Supabase redirect tool | 19 |
| Flutter deep link tool | 19 |
| Universal Links checker | 19 |
| Google OAuth checker | 18 |
| Stripe webhook checker | 13 |
| SEPA Generator Pro | 12 |
| SEPA Doctor | 8 |
Roughly one in ten visitors actually runs a diagnosis, instead of just landing on the page. About half of visitors are from the US, the rest mostly Slovakia, the Netherlands, Germany, and Canada. Email signups: 0. Paid sales: 0, though the first paid product only went live today. One person downloaded the bookapp APK.
What did not work
Early on, each tool had a "would you pay for Pro" button, meant to gauge interest before I built anything paid. It measured nothing: zero clicks, across every tool. I pulled it and put an email signup in its place instead, on the theory that asking for an email is a real commitment and a button click is not.
Distribution took more effort than building did: technical replies in 12 GitHub threads, posted from my own account with consent, 3 pull requests to awesome list repos, submissions to Bing and IndexNow, a Google Search Console setup, and 6 dev.to notes. No Hacker News or Reddit post yet. Both communities have explicit rules against AI written text, and posting there has to be me, in my own words. I'll do that myself, separately.
The clearest lesson from three days: building is no longer the bottleneck. AI agents can put a tested, documented tool online faster than I can find people to look at it. Distribution is the actual constraint now.
The other pattern in the numbers: tools that fix a one time error get visitors, and then those visitors leave, because once their redirect or OAuth setup works, they have no reason to come back. That is fine for traffic, but it is not a business by itself. The two things I am actually betting on are recurring problems: SEPA payment files for accountants, who run into this every month, and a culling app for photographers, who shoot constantly. Free error fixing tools bring people to the site; the paid products need a reason for people to come back.
What's next
I post to Hacker News and Reddit myself, in my own words, once there is enough here worth talking about. Costs so far: 0 EUR beyond the AI subscription I already pay for, and a 12 EUR domain. My own target is 200 EUR in revenue by September 27 to justify keeping this pace up. Right now that number is 0, so the next two weeks are about turning a few dozen daily visitors per tool into people who actually pay for the two products built to be paid for.
If you want to see what is live: the hub is at https://arling.sk/, there is a page on how the human and AI split actually works at https://arling.sk/how-we-work/, and the running build notes are at https://arling.sk/notes/.
Written with AI assistance and published by me. Numbers are from my own self-hosted analytics.
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