Vibe Coding: How I Built 3 Applications Without Hiring a Developer

In 2023, I decided to build a platform for property investors. Plot purchase checklists, budget tracking, document management, experts, land maps — all in one place. Mobile app for iOS and Android, plus web.

I had zero developers on the team.

I wasn’t looking for a freelancer either. Instead, I opened Claude Code and started writing prompts.

Today, naswoim.org is live. Users logged in. Data in Supabase. Mobile version in the App Store and Google Play. And I built it in parallel with two other projects.

What vibe coding actually is

Vibe coding isn’t the same as no-code. You still write code. But you don’t write it alone from scratch — you write it together with an AI model that generates implementation based on your specification.

It’s also not about pasting questions into ChatGPT and copying the output. It’s about thinking precisely about a problem and describing it in a way that AI can translate into working code.

This shifts what’s required. You don’t need to know how to write a React hook with optimistic UI updates. You need to know that you need one — and why.

Three products, zero external developers

marcinpaszkiewicz.com — this site. Astro SSR, WordPress Headless as CMS, deployed on Vercel. Every change — new article, layout fix, new feature — is built through Claude Code. Time from idea to live change: usually under an hour.

naswoim.org — full stack: React 19 + Vite, Tailwind CSS, Supabase (PostgreSQL + Auth + Storage + Realtime), Capacitor for iOS and Android. Twenty pages, fourteen domain hooks, twenty-four feature components. Row-level security, 20 SQL migrations, Leaflet maps integration. Built entirely without hiring.

industrverse.com — the most technically ambitious. Frontend: Next.js + React 19. Backend: NestJS with 13 modules, Prisma + PostgreSQL, Redis, JWT/Passport, Socket.io for real-time VR sessions, Swagger, Google API integrations. Docker Compose with four services. npm monorepo. Seven user roles. Nine role-specific dashboards.

None of these projects would have been feasible within a reasonable time and budget without AI as a programming partner. With AI — each one became executable for a single person.

My workflow

There’s no single tool. I use several depending on the task:

• Claude Code (CLI) — for deep file-level work: new features, refactoring, debugging with full project context. It understands repo structure, reads multiple files simultaneously, and proposes changes down to the line.
• Claude.ai — for architecture planning, design decision discussions, rapid questions at the design stage. I use this to talk through what I’m building before writing a line of code.
• GitHub Copilot — for in-editor autocomplete, especially for repetitive patterns (components, tests, SQL migrations).

The iteration loop: define the task precisely → AI generates a scaffold → I review and guide → AI refines → I test → repeat. The key word is „guide” — this isn’t an autopilot. You’re driving.

What AI does well

• Scaffolding and boilerplate — new API endpoint, new component, new SQL migration. AI knows what these look like and generates them quickly and correctly.
• Debugging with context — paste the error + relevant code → AI diagnoses. Usually accurately. This saves hours of Stack Overflow searches.
• Refactoring — renaming, restructuring, adding TypeScript types to existing JavaScript. AI is fast and precise at this.
• Cross-layer translation — „I have this logic on the backend, write the corresponding frontend hook.” AI understands both sides.

Where humans are still required

Vibe coding doesn’t eliminate the need for thinking. It changes what you think about.

• Architecture decisions — how to split the system, where to put logic, what tradeoffs to accept. AI suggests, but you decide.
• UX and product design — what a user should feel at a given moment. AI doesn’t know your users.
• Security — any code touching auth, sensitive data, or permissions requires your verification. AI makes mistakes in RLS, input validation, API exposure.
• Complex state in large codebases — above a certain project size, AI loses context. You need to guide it precisely.

What I learned along the way

The biggest trap: treating AI as a code vending machine. You paste a description, receive code, paste it into the project without reading. This ends with security bugs, inconsistent style, and technical debt you’ll only understand six months later.

The second trap: prompts that are too vague. „Write me a budget management app” produces generic, unusable output. „Write a useProjectBudget hook that subscribes to the expenses table in Supabase via Realtime, aggregates totals per category, and returns isLoading, error, totals, and addExpense” — gives you exactly what you need.

Vibe coding doesn’t require knowing every line of code. It requires thinking precisely about problems — and that’s a skill you can deliberately develop.

Where to start

If you want to start building in vibe coding mode, three things give the highest return:

• Git basics — commit, push, branch, merge. Without this you can’t experiment safely. Git is your safety net.
• How to read error messages — you don’t need to understand every line of code, but you do need to read an error message and paste it to AI with context. That’s 80% of debugging.
• SQL fundamentals — most applications have a database. Understanding SELECT, INSERT, JOIN and basic schema design lets you guide AI through data layers.

Next step: pick a tool. Claude Code, Cursor, GitHub Copilot — each has strengths. Start with one, on a small project. Not a database-backed application right away.

What problem would you solve with your first vibe coding project?

Author has been building in vibe coding model since 2023. Stack: naswoim.org (React 19, Supabase, Capacitor), industrverse.com (NestJS, Next.js, PostgreSQL, Redis, Docker), marcinpaszkiewicz.com (Astro SSR, WordPress Headless, Vercel).