AI Foundation for Developers – LLM & GEN AI Step-By-Step | Spring AI Prerequisites

If you’re a developer — Java, Python, C#, or any language — and want to start building AI-powered applications, this video is your complete foundation.

In this session, I will explain everything you need to know before integrating AI into your application using Spring AI or OpenAI APIs.

By the end of this video, you’ll clearly understand what Generative AI (Gen AI), LLMs, GPT, Tokens, Transformers, and Roles actually mean — so you can follow the upcoming coding tutorials confidently.

What You’ll Learn?

0️⃣ What is Generative AI – and how it can generate text, images, audio, or even code.
1️⃣ Difference between LLM (Large Language Model) and Diffusion Model (for images/videos).
2️⃣ What is GPT (Generative Pre-trained Transformer).
3️⃣ How Transformers predict the next word using “Attention Is All You Need.”
4️⃣ How AI models like ChatGPT, Gemini, and Claude work internally.
5️⃣ What are Tokens and why you get billed per token when using OpenAI APIs.
6️⃣ How to connect to OpenAI endpoints using Postman and authenticate via API Keys.
7️⃣ Understanding Chat Completion API → v1/chat/completions.
8️⃣ The concept of Messages[ System, User, and Assistant ] roles in ChatGPT requests.
9️⃣ Model comparison: GPT-5 Nano, Mini, Pro, their pricing, speed & reasoning ability.
🔟 What is a Context Window, Knowledge Cut-off, and Reasoning Token Support.


🕓 Chapters

00:00 – AI Foundation
01:07 – What Is Generative AI (Gen AI)?
02:22 – Understanding Large Language Models (LLMs)
03:00 – LLM vs Diffusion Models – Text vs Image Generation
06:08 – GPT Explained → Generative • Pre-Trained • Transformer
09:06 – How LLMs Predict Text Step by Step
14:09 – Chat Completion Concept
19:44 – What Are Tokens in AI?
28:49 – Usage and Billing Process
33:20 – Attention Is All You Need – Transformer Mechanism
36:43 – Real-World LLM Examples → OpenAI, Gemini, Claude
40:28 – Choosing the Right AI Model (GPT-5 Series)
42:13 – Understanding Reasoning Tokens
43:11 – GPT Speed, Cost, Input & Output Explained
46:56 – How AI Models Use Context Windows
49:09 – Understanding Knowledge Cut-Off
50:15 – OpenAI Platform Tour → Models & API Overview
55:00 – Chat Completion API Deep Dive (v1/chat/completions)
57:22 – Running Chat Completion API on Postman
1:00:27 – OpenAI Authentication → API Key & Bearer Token
1:04:44 – Postman + OpenAI API Testing
1:10:01 – Messages & Roles in ChatGPT
1:13:14 – System, User & Assistant Roles Explained
1:26:39 – Response JSON Breakdown (ID, Model, Finish Reason)
1:28:47 – Prompt vs Completion Tokens & Billing
1:29:23 – OpenAI Tokenizer Demo
1:35:58 – Developer Mindset for AI Integration
1:37:11 – Welcome Spring AI (Spring Boot Introduction)
1:39:00 – Conclusion & Next Video Preview

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⚙️ Tech Stack Covered
Postman API Testing
OpenAI API Endpoints

related :
Java + Spring Boot
Spring AI Integration


🚀 Next Video
➡️ Integrating ChatGPT with Java Spring Boot using Spring AI
Learn how to make real-time API calls, send messages programmatically, and handle responses in your backend.

#springai #genai #llm #aifordevelopers #openai

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