How I Built a Paid SaaS in 7 Days Using AI

Seven days. That's how long it took to go from "what if there was a tool that generates AI skill files?" to a live, paid product with Stripe integration, 21 pre-built skills, and a security scanner.

Here's how it happened, what the tech stack looks like, and the 5 lessons I wish I knew before starting.

The Idea

AI coding assistants like Claude Code and OpenClaw use SKILL.md files — markdown documents that define agent behavior. Writing these files manually is tedious: you need to know the exact YAML frontmatter format, the right trigger phrases, proper tool declarations, and platform-specific conventions.

What if you could describe what you want in plain English and get a production-ready skill file in 60 seconds?

That's SkillForge.

The Tech Stack

| Layer | Technology | |-------|-----------| | Framework | Next.js 16 (App Router + Turbopack) | | AI | AI SDK v6 + Kilo Gateway (OpenAI-compatible) | | Auth | Supabase Auth (magic link + Google OAuth) | | Database | Supabase (PostgreSQL) | | Payments | Stripe (one-time purchases, not subscriptions) | | Hosting | Vercel (auto-deploy from git push) | | Styling | Tailwind CSS v4 | | Analytics | Google Analytics 4 + Vercel Analytics |

The Timeline

Day 1-2: Core Generation Engine

Built the AI pipeline first — no UI. Just a function that takes a plain English description and returns a formatted SKILL.md file. This was the riskiest part: if the AI output wasn't good enough, there was no product.

Key decision: streaming responses. Users watch the skill generate token by token instead of staring at a loading spinner. This alone made the product feel 10x faster.

Day 3: Auth, Credits & Payment

Supabase for auth (magic links are underrated for developer tools). Atomic credit deduction via a PostgreSQL RPC function — no race conditions. Stripe with one-time payments, not subscriptions, because nobody wants a monthly commitment to a product they just discovered.

Day 4: Pre-built Skill Catalog

Not everyone wants to generate from scratch. We curated 21 skills (12 free, 9 premium) covering development, testing, documentation, DevOps, data, and writing. Each with a full preview and one-click download.

Day 5: Polish & Landing Page

Hero section, feature grid, pricing cards, format comparison, social proof. The landing page is the product's first impression — I spent a full day on it.

Day 6: Security Scanner

This was the game-changer. Nobody else was auditing AI skill files for security. We built a scanner that checks 9 categories (command injection, network exfiltration, prompt injection, etc.) and produces a scored report with reasoning for every finding.

Day 7: Launch

Deployed to Vercel, posted on Reddit, X, and LinkedIn. Started the content engine.

5 Hard Lessons

1. Validate AI Quality First, UI Second

My first "feature" was a raw API call. No frontend. I tested whether the AI output was actually useful before writing a single React component. This saved me from building UI around bad output.

2. SDK Version Hell is Real

AI SDK v5 and v6 have completely different APIs. maxTokens became maxOutputTokens. toAIStreamResponse() became toTextStreamResponse(). The tutorials online lag behind the actual packages.

Lesson: Pin your versions. Read changelogs, not tutorials.

3. Credits Beat Subscriptions (Early On)

$5 for 20 credits feels like a low-risk impulse buy. $10/month feels like a commitment. For a new product with no brand recognition, reduce the purchase barrier as much as possible. You can always add subscriptions when you have retention data.

4. Security Became the USP

I built the security scanner almost as an afterthought. It became the #1 thing people ask about. Security = trust. Trust = conversions.

If your AI product touches user code or data, build the security narrative from day 1.

5. Streaming is Non-Negotiable

Users will wait 8 seconds watching tokens appear. They'll abandon after 3 seconds staring at a spinner. Same total wait time, completely different experience.

What's Next

• Integrated blog (you're reading it)
• "Roast My Skill" community campaign
• GitHub Actions integration for CI/CD skill auditing
• More skill formats as new AI assistants emerge

If you're building with AI coding assistants, try SkillForge. Generate a skill, scan one for security, or browse the free catalog.

The future of AI development is instruction-driven. The question is whether those instructions are secure.