My Journey with AI — How I Started
I remember the moment when I first saw ChatGPT generate code. I was just a kid back then, sitting in front of the screen with my jaw dropped. I thought to myself: “This will change everything.” And I wasn’t wrong.
The “Aha” Moment
It was 2023. I already had two years of Python experience under my belt — I started coding in 2021, as a kid. But when I discovered AI, it was a whole different level. It all started with a simple question — how does it work? How can a model understand context, generate meaningful answers, and even write code?
I started digging. First YouTube, then documentation, and then… git init.
First Steps
My initial experiments with AI looked something like this:
from transformers import pipeline
classifier = pipeline("sentiment-analysis")
result = classifier("I'm learning AI and it's amazing!")
print(result)
# [{'label': 'POSITIVE', 'score': 0.9998}]Simple code, but when I saw the result — I felt I had found my path.
What Drives Me
Three things keep me on course:
- Continuous growth — AI changes every week, there’s always something new.
- Practical applications — from chatbots to data analysis, the possibilities are endless.
- Community — people in the AI world are open and willing to help.
What’s Next?
Currently, I’m focusing on:
- RAG (Retrieval Augmented Generation) — connecting LLMs with databases.
- Fine-tuning — adapting models to specific tasks.
- AI Agents — building autonomous agents with LangChain.
“The best time to plant a tree was 20 years ago. The second best time is now.”
And that’s exactly how I approach learning AI. I’m not an expert, but I learn every day. And that is beautiful.