Ideation & Initial Code Generation - What began just as school project, didnt thought to be too harsh, even using Ai to assist.
I had this idea to build Self driving car simulation, in which I researched and found we can use reinforcement algoritmns and chose Streamlit for Frotend, then finalised the plan

Tech Stack : - Python
I used Gymnassium - Highway env for Highway Environment, SAARS and DQN for learning and training model. The model is trained using State - Action - Reward system, with control of location thrust, speed lane and more.

There was no novelty just to write it, then I chose streamlit for the visualization of training but turned out to be my biggest mistake, started scaffolding the project, building helper function and script for training, start datbase and Q learning table.

Everything was good, then streamlit code for frontend the challenge I faced was, errors and not able to control environment and controls.

then shifted to native python shell, and optimized gui controls, code shortening, documentations for quick start, control and journals. These are the major parts I did. Almost had 40 + commits unlimited brain storming, decision making still model needs improvement, but I think its NERDEST.

What started as simple prompt journey taught several things, git merge conflicts to logical headache what to do now, at the end everything works fine button everything working and code is structured without AI slop.

If you are reading till now, leave a feedback for me to improve, I know its just a start but small steps count. Whoever is reading this, GOD BLESS YOU.