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A developer’s honest journey into the world of AI, tools, and tiny agents.
🧑💻 Full Stack Developer | JavaScript & GenAI Enthusiast 🚀 7+ years building scalable web apps with React, Node.js & PHP 💡 Exploring GenAI, Microservices, and Clean Code Principles 📚 Blogging my dev journey, lessons learned, and side experiments ♟️ Chess lover | Vegetarian foodie | Life-long learner
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"From Developer to AI Explorer" is a series that follows my journey as a full-stack developer diving into the world of Artificial Intelligence (AI).
Keep Your Code Flexible — Add New Stuff Without Messing Up Old Logic
One class. One job. One reason to change
What Are AI Agents? AI agents are smart software systems that can work independently. They can plan, make decisions, and work with other agents without constant human guidance. Examples include AutoGPT and BabyAGI. Benefits Flexibility: Agents ...
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Real-time + Horizontal Scalability Introduction When I first started building this chat app, there was one requirement I had in mind: it has to be real-time, scalable, and easy to scale up. Sounds easy—until you introduce multiple servers to the mix...
As a full-stack developer, I spend hours every day writing code, fixing bugs, testing features, and managing tasks. Somewhere along the way, I realized I was repeating myself—writing similar functions, Googling the same snippets, and setting reminders for routine tasks.
At the same time, I kept hearing things like:
“AI will take developer jobs.”
“If you don’t learn AI now, you’ll be irrelevant tomorrow.”
“The future belongs to AI—developers who don’t adapt will be left behind.”
Honestly, it was overwhelming. I wasn’t a data scientist. I am just a simple developer.
I don’t know what is models, LLMs, GenAI. But I knew how to build things. So I decided to stop overthinking and just start exploring.
I didn’t know where to start. With a lot of enthusiasm and curiosity, I just started. As any developer, I go to Google, YouTube, and ChatGPT to help me learn AI.
It is not easy… there was so much information, tons of articles, but most of it was packed with heavy terms like transformer, tokenization, Ollama, Hugging Face, fine-tuning RAG, and so on.
My goal wasn’t to build the next ChatGPT; I just wanted to understand the basics. What exactly is GPT? What is OpenAI? Everyone kept saying "AI, AI, AI," but I needed to know the fundamentals first.
That’s where my journey truly began.
Once I started, I realized that to build anything useful, I first needed to understand some core concepts. It was shocking, but true—I finally got what tokenization, transformers, and self-attention actually mean.
I used to thinkg ChatGPT and the OpenAI API would give the same answer to simple questions, like “What’s the weather in Delhi?”
ChatGPT gave me the answer. But the OpenAI API said... nothing useful. Why?
🧠 ChatGPT is like a smart robot with internet and extra tools.
📦 OpenAI API is like the same smart robot, but without internet or tools.
In simple terms, ChatGPT is like a brain with a full working body — it can think and take action. It can search the web, do calculations, read files — just like a body helping the brain get things done.
But the OpenAI API is just the brain.
It’s super smart and can think really well, but it can’t do anything by itself.
If you want it to act — like search the web or get the weather — you have to build the body around it..
So that’s how my AI journey started with small steps, a curious mind, and a strong developer instinct.
From feeling overwhelmed by AI buzzwords to understanding how tools like ChatGPT actually work
And trust me, if I can do it, you definitely can too.
In the next post, I’ll break down one of the most basic but powerful concepts in AI:
What is tokenization?
(Hint: It’s like teaching a computer how to read!)