I built and launched Dead Simple Nutrition in under 24 hours.
I’ve learned a lot while building and launching this product in such a short timeframe.
Here’s the tech stack I used:
- GPT-5 Codex in VS Code.
- Next.js with React for the app.
- Shadcn UI for the design system.
- SQLite for the DB.
- OpenAI API for AI-powered features.
- Render for the web server.
Here are the lessons I learned along the way:
- The lighter the tech stack, the better, especially around the DB. I decided to go with SQLite as it seems to play nice with automatically making updates to the DB and mitigating issues.
- Who says SQLite doesn’t scale?! If I run into SQLite limitations, then I have a great problem on my hands.
- I found that planning before building works really well. Map out the entire journey of the app, then feed it to the model and let it understand the product before building.
- After it understands everything, prompt one feature at a time through the user experience and have it build each feature end-to-end.
- After every build, retest in an incognito window to ensure nothing broke.
- When errors inevitably come up, fix the bug before building out the next feature.
- Workflow: build first feature in user journey -> test in incognito window -> fix bugs/adjust until perfect -> push updates to git repo -> build out next feature -> repeat
I don’t think this will work well at scale, as I ran into a plethora of build issues and type errors that I had to resolve before it finally ran in production. All of my prompts were to build out end-to-end features from the UI to DB.
Where I think this could work at scale is when you’re working with a few files at a time or even just on one end of the stack (frontend, API, etc.)
All in all, I’m impressed with AI’s ability to build and ship an MVP.