I did a Backend/API/Frontend 100% with Cursor(16h/day - 250$ spend). Part 2 - What I learned

🚀 **In this post, you’ll get:**

✅ How to ship big solo AI projects without losing your mind

✅ My best tips, mistakes, and how to avoid the biggest traps

✅ **+ a free GPT link I made** to help you write better prompts for Cursor

✅ My full tech stack (backend, frontend, infra) — short version  
  
Ok first of all — **THANK YOU SO MUCH** for the love on my last post!!  
It got **48k views**, **100+ upvotes and comments**, **1.5k+ visitors** on the website, and… **my first clients**!  
You’re crazy!! What an amazing community.  
I really want to give back what you gave me, so here’s everything I learned on this journey with Cursor — I’ll try to be as precise and honest as possible, so you can reuse it!

1️⃣ **How to start a project with Cursor**

This is maybe the most important point.

**Before** starting any project (with Cursor or any IDE), **ask a reasoning model** (like **Cursor o1/o3/o4-mini**) something like:

“How would you develop *my project, precisely*?”  
  
Push it:  
 \- Why this stack, not another?  
 \- What kind of database should I use? (I recommend Supabase or PostgreSQL)  
 \- Is it secure?  
 \- Is it easy to deploy?  
 \- Any faster alternatives?  
 \- What dependencies will I face?

**Example mistake I made:**  
For one feature, I wanted to let users upload a YouTube video, and it would transcribe it for fine-tuning.  
But I didn’t challenge the AI — so it made me install Whisper (OpenAI translation system) + another dependency to download the MP3.  
BUT YouTube has tons of restrictions… I lost **one full week** trying to make this work, instead of just using an external API like ones form RapidAPI (marketplace of API :[https://rapidapi.com](https://rapidapi.com)).  
Why? Because I was too impatient to take *5 minutes* and ask all the ways to do it.  
  
In code — and in entrepreneurship — **the most important thing is that the flow works**.  
There are a thousand ways to get to 10:  
5 + 5 = 10  
2 + 3 + 4 + 1 = 10  
1 + 1 + 1 + 1… = 10

Sure, someone will always tell you *“do it another way”*—but the key is to **ship fast**, get user feedback, and improve *later* once you’ve validated product-market fit.

So, once you’ve got the info, just ask the AI to turn it into one big prompt (or multiple prompts if the project is big).  
And don’t forget to ask for theme recommendations too (colors, shapes, futuristic/classic/modern…).  
  
👉 **Become a learner**: when the AI creates a document you don’t know or understand, **ask** ***why***. That way, you’ll learn everything you need for a dev project — databases, routers, endpoints…

2️⃣ **Inside Cursor**

Start with your prompt in agent mode, and **ask the model to write full documentation of your project** (at least a [README.md](http://README.md) file).  
You can even add Cursor-specific rules if you want.  
Don’t use Auto/YOLO mode if you’re not already experienced with dev projects — you need to understand what the AI is doing and follow its carefully.  
  
Congrats — you’re now at the best part, where you watch everything getting built!

**And don’t forget** to set up a github repository, so you can update and deploy your code later.

**2.1 Picking the right model**

Ok, this part changes all the time (a new damn model arrives every day), but here’s what worked for me *right now*.  
If this post gets enough upvotes, I’ll update it over time.

**Cursor models**

* Claude 3.5 → forget, grandpa
* Claude 3.7 → decent logic & design
* Claude 3.7 + thinking → better logic & design, but small context window
* Claude 3.7 MAX + thinking → great logic & design, decent context window 

✅ Good for: JS apps, unlocking logic problems, frontend design  
❌ Bad: Super stubborn (if it *thinks* it should do something a certain way, it’ll keep doing it even if it doesn’t work), small context window

**GPT models**

* GPT-4o → great for re-prompting (my custom GPTs)
* GPT-4.1 → honestly feels like a scam, big context but bad logic/design (probably OpenAI just scared of Cursor)
* GPT-o3 → insanely good at logic, saved me tons of debugging time (feels like AGI)
* GPT-o4-mini → similar to o3, but I haven’t tested it much yet 

✅ Good for: reasoning, debugging, figuring out next project steps  
❌ Bad: not great for full-page generation (except backend), small-ish context, slow

**Cursor models**

* Cursor 2.5-pro → no idea, never used
* Cursor 2.5-pro MAX (my baby) → insanely good, big context window, great logic & design 

✅ Good for: big context, design, logic  
❌ Bad: can get a bit lost if you overload context, slightly worse at debugging compared to GPT-o3  
  
And please stop being cheap by using low-end models — you’ll lose *more* money later debugging everything with the big ones anyway. I spent €250… but how much would it have cost with a full-stack freelance dev? €10–20k?

**2.2 How to use models**

⚡ **SWITCHING IS THE KEY!**  
You have to jump between different models, depending on the task, to see which one does it best.

**STOP thinking the model is the problem. YOU are.**

I’m tired of seeing people complain, “the model doesn’t understand!!” — and then you look at their prompts, and you just want to cry.

Imagine: every time you ask something, you’re talking to a real assistant (who only knows things up to 2023).  
If they mess up, maybe it’s because **you** didn’t give clear instructions, enough context, or the right documentation.

✅ **Re-prompt your prompt!**  
I’m lazy too, so I built a custom GPT just to help me improve prompts:  
👉 [https://cursor.com/g/g-6809fcb196348191893e5cb8fc71739c-cursor-prompt-builder](https://cursor.com/g/g-6809fcb196348191893e5cb8fc71739c-cursor-prompt-builder) (free 🐀😘)

✅ **Use context well.**  
Add only the context you need. Compile it in **.md** files (e.g., **API\_documentation.md**) and load them when needed.  
In your prompt, use **@** to tag content (gives the best results).  
Also use the « **doc »** feature to insert live documentation when needed.

3️⃣ **Deployment (mmm, the worst part)**

Ok, this was **brutal** for me — way harder than I thought.  
If someone more expert wants to write a better explanation, I’ll happily update this part with your upvoted comments!

What I understood 👇

To deploy a web app, you have two choices:

1️⃣ **Serverless systems (like Vercel)**  
✅ Easy — just upload from GitHub  
❌ Only works for frontend framworks apps (not big backends)

2️⃣ **Own server (VPS + Docker)**  
✅ You can do *anything*  
❌ Really hard if you’re a beginner

Of course, you’re starting to know me… I love easy stuff.  
So obviously, I bought a VPS 😂.

Here’s what worked:

* I asked GPT-o3 to help set up the VPS
* It made me use Docker (to keep it simple: Docker lets you create containers where you put your code to deploy)
* Why Docker and not something else? Honestly, **the whole world** was screaming at me to use it, so I did haha. 

Did it work first try? Of course not.  
I spent **almost a week** stuck, almost gave up.  
Luckily, I got on video call with a super-experienced backend dev — and even for *him*, it was hard! But he found the issue:  
The AI was updating my code in the wrong space. 😅

In the end, what worked was:  
✅ Update your GitHub code  
✅ Pull it to your VPS  
✅ Build with Docker

4️⃣ **Extra**

There’s no **single** way to do AI coding.  
This is just what worked for me — I hope it helps!  
  
I realized maybe I could help some of you, so I created an **official X (Twitter)** account where I post daily about vibe coding, shipping my app, and honest updates.  
My first post is about how I made my landing page + animations. [https://x.com/MaximeMarsal/status/1918317838076461444](https://x.com/MaximeMarsal/status/1918317838076461444)  
  
You can still fine-tune your models with my project:  
👉 [https://finetuner.io](https://finetuner.io/)  
  
**TL;DR**  
Finetuner is a tool that helps you fine-tune your OpenAI or Cursor models on your own content in just a few minutes.  
  
I took all your feedback, and soon I’ll post a full benchmark showing how fine-tuning makes a difference!

**Huge THANK YOU** to the creators of Cursor — you really changed my life.  
I can finally unleash my creativity, and I *hope* one day I’ll build a product that makes people vibrate as much as Cursor made me vibrate.  
  
Ah, and yes — **don’t go back into the history of the Cursor chat after generating code** because it restores your code to the moment of the chat (honestly, the dumbest feature ever I think 😆).  
  
⚙️ **My Stack for this project**

* **Backend** → FastAPI (Python 3.11), PostgreSQL, Celery + Redis, OAuth2/JWT, OpenAI/Anthropic APIs, Stripe, PyPDF2, youtube-transcript-api.
* **Frontend** → React + MUI, React Query, React Router, Formik + Yup, Notistack, axios, Chart.js, i18next.
* **Infra** → Docker, Docker Compose, Nginx, simple git pull + docker-compose deploy.

Huge thanks also to everyone who took the time to comment, ask questions and cheer me on! 🙏💙  

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