I built 17 AI tools for developers in 4 months. Here's what I learned about shipping fast.

From idea to 17 production AI tools using Gemini, Supabase Edge Functions, and a brutal focus on shipping. Real numbers, real mistakes, real lessons.

Four months ago I had an idea: what if devs could roast their own code with AI, calculate their market salary, simulate interviews, and learn programming — all in one place, all free, all multilingual?

Today CodeMasterIp has 17 production AI tools, runs in 15 languages, and serves thousands of devs. Here's what I learned shipping that fast.

1. Pick the boring stack on purpose I went with React + Vite + Supabase + Gemini 2.5 Flash via Edge Functions. Nothing exotic. No K8s. No microservices.

Why? Because the bottleneck was never tech — it was always deciding what to build next.

// One Edge Function. One model. One pattern. Repeat 17 times.
const response = await fetch(
'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent',
{
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ contents: [{ parts: [{ text: prompt }] }] }),
}
);
That's it. That's the architecture for all 17 tools.

1. Each tool ships as a "complete product" Every tool has its own URL, its own OG image, its own shareable result page. Why? Because a tool that can't be shared on Twitter doesn't exist.

/code-roast → AI roasts your code with severity badges
/salary-calculator → market salary with country adjustments
/dev-quiz → "what dev are you" personality test
/typing-speed → WPM ranks for coders
/dev-bingo → bingo card with dev clichés
Each one has a /result/:id page that generates a custom 1200×630 SVG card via Edge Function. Twitter, LinkedIn, Reddit — all eat them up.

1. Free is not a strategy. It's the strategy. Most tools competing with mine charge $9/mo. Mine are free. Why?

Because attention is the bottleneck, not money. A free tool that 10,000 people share beats a $9 tool that 200 people pay for — every time.

Monetization comes from the one thing people pay for: the AI chat with persistent context.

1. Internationalization from day 1 15 languages. react-i18next. Every tool, every page, every error message. The code? Pre-rendered in 12 languages inside blocks for SEO.

Aprende programación con IA

Learn programming with AI

用AI学编程

Result: traffic from countries I didn't even target.

1. The most underrated growth lever: programmatic SEO I generated 45,000 unique URLs programmatically by combining:

12 languages × 200 topics × 18 page types
Each one has unique content, unique meta tags, unique JSON-LD. Each one pings IndexNow on creation.

Most never rank. Some rank #1 for long-tail queries I never imagined.

1. Mistakes I made (so you don't have to) Built ads first, removed them later. AdSense killed page speed and SEO. -40% LCP. Removed everything. Tried Reddit autopromo. r/learnprogramming closed my post in 2h. Lesson: provide value first, sell later. Over-engineered auth early. Supabase auth + Google OAuth = 30 minutes. Done. What I'd do differently Ship the first tool in a weekend. Not 4. Not 17. One.

The 17 came from compounding learnings: each tool was 30% faster to build than the previous one because the patterns repeated.

If you want to see all 17 tools in action: codemasterip.com. The Code Roast one is the most fun — paste any code and the AI will tell you what's wrong with it (with severity levels, like a real code review).

What would you build with this stack? Drop it in the comments — I'm curious.