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How I Built 6 AI Products in One Week (And What I Learned)

One week. Six products. All AI-powered. Some made money. Some flopped. Here's the full breakdown with actual numbers, mistakes, and lessons.

The Products

I built all six under Avatrix LLC using a lean methodology: smallest testable version first, measure for signal, iterate or kill.

1. CoverCraft — AI Cover Letter Generator

What: Web app where you paste a job description and get a tailored cover letter.
Stack: Next.js, Stripe, Claude API.
Price: $1 per letter.
Build time: 3 hours.

web-tool-gray.vercel.app

The build was simple. One form, one API call, one Stripe checkout. The hard part was distribution. Nobody knows your product exists on day one.

2. StructureAI — Data Extraction API

What: API that turns unstructured text into clean JSON. Receipts, emails, resumes, custom schemas.
Stack: Next.js API routes, Claude API, Stripe.
Price: $2 for 100 requests.
Build time: 4 hours.

api-service-wine.vercel.app

This was the most technically interesting. The custom schema feature — where users define their own fields — turned out to be the killer feature. Every use case is slightly different, and custom fields handle them all.

3. StructureAI MCP Server

What: MCP server that connects StructureAI to Claude Desktop and Cursor.
Stack: TypeScript, MCP SDK.
Price: Free (10 requests), paid via API key.
Build time: 2 hours.

github.com/avatrix1/structureai-mcp

The idea: give developers a free taste via MCP, then convert to paid API keys. The MCP ecosystem is growing fast, and being early matters.

4. AI Worker Hub

What: Submit tasks (bug fixes, content, data analysis) and get AI-generated results.
Stack: Next.js, Stripe, Claude API.
Price: $8-15 per task.
Build time: 2 hours.

api-service-wine.vercel.app/worker

This was the "service arbitrage" play: charge human freelancer prices, fulfill with AI. The margins are enormous (97%+). The challenge is convincing people that AI output is worth paying for.

5. Telegram AI Bot

What: Telegram bot offering cover letters, content writing, and more.
Stack: Node.js, Telegram Bot API, Telegram Stars payments.
Price: $0.07-$0.28 per task.
Build time: 3 hours.

@avatrix_ai_bot

Telegram Stars are the lowest-friction payment method I've ever used. No Stripe integration, no credit card forms. Users tap a button and pay. The downside: prices are in Stars, so users don't think in dollars.

6. OpenClaw Skills

What: AI skills for the ClawHub marketplace.
Stack: TypeScript/SKILL.md format.
Price: $7-9 per skill.
Build time: 1 hour.

Built three skills, then discovered ClawHub has a 2-5 day review process. Marketplace timing killed this one for fast revenue. Long-term play.

What I Learned

Lesson 1: Distribution Is Everything

All six products work. The tech is solid. None of that matters without users.

The products with distribution channels (Telegram's built-in user base, GitHub's organic discovery) showed more promise than the standalone web apps. Beautiful landing pages don't generate traffic.

Lesson 2: Build Time Should Be Under 4 Hours

If it takes more than 4 hours to build v1, you're overbuilding. Every product above was deployed in under 4 hours. Some in under 2. The point of v1 is to test demand, not to ship a polished product.

Lesson 3: Payment Integration Is a Solved Problem

Stripe took 30 minutes to integrate. Telegram Stars took 15 minutes. Don't let payment implementation block your launch. It's literally copy-paste at this point.

Here's the entire Stripe checkout in Next.js:

import Stripe from 'stripe';

const stripe = new Stripe(process.env.STRIPE_SECRET_KEY!);

export async function POST(req: Request) {
  const { product, email } = await req.json();

  const session = await stripe.checkout.sessions.create({
    line_items: [{
      price_data: {
        currency: 'usd',
        product_data: { name: product },
        unit_amount: 100, // $1.00
      },
      quantity: 1,
    }],
    mode: 'payment',
    success_url: `${process.env.BASE_URL}/success`,
  });

  return Response.json({ url: session.url });
}
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Lesson 4: AI API Costs Are Negligible

Claude Sonnet costs ~$0.003 per request for my use cases. At $1-15 per customer request, that's 97%+ gross margin. The cost of AI is not the constraint. The cost of customer acquisition is.

Lesson 5: Marketplace Timing Matters

ClawHub reviews take 2-5 business days. If you need revenue this week, marketplaces with review queues won't work. Check the listing timeline BEFORE building for any marketplace.

Lesson 6: Service Arbitrage Has Real Potential

Selling AI work at human prices ($8-15) is viable because customers pay for outcomes, not process. They don't care if a human or AI wrote the bug fix. They care that the bug is fixed.

The challenge: building trust that AI output meets quality standards. Social proof, guarantees, and samples help.

The Tech Stack That Moves Fast

After building six products in a week, here's the stack I'd recommend for speed:

  1. Next.js — Full-stack in one framework. API routes, SSR, deploy to Vercel with one command.
  2. Stripe — Payments in 30 minutes. Checkout Sessions for one-time, Subscriptions for recurring.
  3. Claude API — Best quality-to-cost ratio for text generation and extraction.
  4. Vercel — Deploy in 30 seconds. Free tier covers early-stage products.
  5. Tailwind CSS — Ship decent-looking UIs without a designer.

Total cost to run all six products: roughly $20/month (Vercel Pro plan). Everything else is pay-per-use.

What's Next

The products are live. Now comes the hard part: distribution. The plan:

  1. Content marketing (articles like this one)
  2. MCP ecosystem discovery
  3. Service marketplace listings (Fiverr, etc.)
  4. Community engagement (Dev.to, Reddit, HN)

The products that get traction will get investment. The ones that don't will be pivoted or killed. Data decides.

Try Them

Build fast. Ship fast. Let data decide what survives.

Built by Avatrix LLC. Building in public, one product at a time.

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