My AI Dev Stack (2025): From Idea to Launch in 14 Days
Two weeks. That’s how long it takes me to go from scribbled idea to live product. Not a prototype. Not a pretty Figma mock. I mean something real. Users. Backend. DNS records. The whole thing. Wild, right?
The first time I pulled it off, I was sitting in a noisy café, steam rising off a chipped mug of espresso, sketching a random idea on a napkin. I sent a few prompts to ChatGPT, fired up Cursor, and by the time my coffee went cold, I had a working UI and a backend schema.
That’s when it hit me. AI isn’t just helping me code faster. It’s changing how I think. It’s cutting out all the BS between spark and ship. So here’s how I build solo in 2025: smart, lean, and fast.
1. Brainstorm with AI
Tools: ChatGPT, Claude, Gemini
I usually start with chaos. Maybe a late-night voice note. Maybe a half-baked Notion doc. Doesn’t matter. I toss it to AI and let the sparks fly. Claude’s great when I want nuance. Gemini pulls in fresh web context. But ChatGPT? That’s my ride-or-die for quick ideation.
Why this matters:
- I get viable MVP concepts in a couple of hours
- I validate ideas with AI-powered research
- I avoid wasting a week on something nobody wants
Honestly, it’s like having a brainstorming partner who never gets tired or shoots down ideas with “but what if the scope’s too big?”
2. Product Specs That Don’t Suck
Where: Notion or just Markdown
How: Structured prompts
I don’t do 10-page specs anymore. They’re lightweight but sharp. AI helps me map flows, edge cases, and must-haves in minutes. The result? Clear specs that actually get used. No fluff. No jargon.
My goal: fewer pivots later. Clarity upfront means smoother dev, every time.
3. MVP the Visual Way
Tool: Lovable.so
Lovable is my secret sauce. I drag, drop, wire it up, and it spits out code connected to GitHub. It’s like if Figma grew up and got a CS degree. I’ve built entire flows in a single afternoon. Same-day feedback, same-day progress. Designers love it. Devs get it. It bridges that annoying gap between “what we imagine” and “what actually runs.”
4. Code Smarter, Not Harder
Tools: Cursor AI, Model Context Protocols
Cursor is a game-changer. It knows my entire repo. I mean the actual codebase, not just a few lines I copy-paste. It writes with context, flags broken logic, and even suggests tests. Sometimes it catches edge cases I missed.
Big win:
- No tabbing between docs and code
- Real-time feedback
- Fewer bugs, cleaner PRs
It’s like pair programming with a super nerd who never sleeps or eats.
5. Backend? Already Done
Tool: Supabase
Postgres, auth, file storage, real-time subs. All in one. I barely have to touch infra. Setup takes 15 minutes, tops. Then I tweak Row-Level Security, seed some data, and I’m in business.
Why I love it:
- Zero boilerplate
- Works out of the box
- Scales better than Firebase, in my opinion
Backend used to be the bottleneck. Now it’s just… handled.
6. Ship It Like It’s Nothing
Tools: Coolify for self-hosted PaaS, Hetzner Cloud for cheap, fast VPS, Cloudflare for DNS, CDN, and security
Hook up CI. Push to main. Deploy in minutes. Coolify keeps it simple. Hetzner gives me performance without the AWS bill shock. Cloudflare handles the rest.
Result:
I hit publish, refresh the browser, and boom — it’s live.
The AI Dev Cycle (Now with Actual Speed)
Here’s what my flow looks like:
- Day 1: Idea spark + AI brainstorm
- Day 2: Specs locked in
- Day 3–6: Build UI, backend, polish
- Day 7–10: Test, tweak, test again
- Day 11–14: Deploy, share, iterate
That’s not a pipe dream. I’ve done it. More than once. AI didn’t replace me. It cleared the junk from my path. And who knows? In a few weeks, some new tool might blow half of this out of the water. That’s the fun part. Everything’s evolving. Fast. Very fast!