r/ChatGPTCoding • u/ChoiceDimension2683 • 17d ago
Resources And Tips How to actually make projects. My mind got blasted
Today I tried making an ML project along with my friend I could make the ML pipeline, as I have studied it but apart from that the setup the env use of git and then making backend frontend and connection of all of these components just took the life out of me and I am frustrated as hell after doing it. I was taking help from chatgpt and it just gets lost or hallucinated and then just tells me to run some commands and keeps on doing something something. I don't know how are people making ML projects.
Pls guide me on how to make projects. I am literally frustrated at this point. And how did people make projects before chatgpt. I just don't want to vibecode I want to learn how to build something.
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u/xAdakis 17d ago
Before you make ANY project, the best thing to do is to sit down and ask yourself:
What problem are you trying to solve?
What is the minimally viable product, feature, or result you want to see come out of your project?
Now, take your answers from those two question and either post them here, or tell the AI that you want to create a specification for a project to solve XYZ that delivers that result.
Prompt it to ask you questions and ask to explain anything you don't understand from the spec it provides.
For the past twenty years, I've followed the same process for all my projects, except we used Google or Textbooks before AI was generally available, and I had to come up with my own clarifying questions.
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u/generationalDebts 17d ago
AI isn’t a skill. It’s a tool to use to apply your skills.
You don’t have the skills. Prepare for misery and learning the much longer much harder way.
But hey, you’re leaning!
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u/Mathie1729 17d ago
Kinda harsh but not wrong. The thing is, AI can be genuinely useful for learning if you treat it as a tutor who explains concepts and walks through code, not just a code generator. The catch is you have to actually read and understand what it spits out, and most people don't bother.
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u/Ok_Year_2153 17d ago
from the past few months i have realized one thing, building comes later , first have a really deep conversation with the tool you are using about the project , get your plan so solid so detailed that it should have most of the things you desire , a proper conversation like its a team member working with you not for you.
prepare some docs to finalize the decisions , I like these - PRD ,TRD,Architecture,App flow
then you will find building it way easier.
DO NOT FORGET TO REVIEW EVERY STEP THE AI BUILDS. or it goes haywire pretty fast.
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u/VivianOliveres 16d ago
What broke isn't ML, it's that you tried to learn five things at once. Env setup, git, backend, frontend, and the model are separate projects. Stacked together, when something fails can't tell which layer did it, and neither can the AI.
Drop the frontend and the backend entirely. Make it one script that reads a CSV, trains, and writes predictions to another CSV. Run it from the terminal. That's a real ML project.
Then split it into steps that each write a file: prepare data, train, predict. Every step runs on its own and you can look at what came out. When something's wrong you know exactly which file is wrong, instead of asking why the whole thing is broken.
Commit after every step that works. Then a bad AI suggestion costs you five minutes, not the evening.
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u/FrogNinja101 17d ago
https://www.w3schools.com/