AI Fundamentals
From Tokens to Intelligence: How Large Language Models Really Work
Large Language Models
16 June 2026• 5 min read
Written by
Kinjal Tiwari
LinkedIn- #prompt
- #LLM
- #SFT
- #Deep Learning
Next step
Ready to go from reading to building?
Guides get you started. Our live AI Engineer Bootcamp gives you mentor feedback, sprint-by-sprint projects, and a portfolio you can defend in interviews.
Related resources
Essential AI Papers & Resources for Modern AI Builders
Explore the papers and resources that shaped modern AI. From the Transformer architecture to GPT-3, chain-of-thought prompting, and the official LangChain and LangGraph docs, this curated reading list will help you build a stronger foundation as an AI engineer.
LangChain vs LangGraph Explained: Workflows, Agents, and Real-World Use Cases
Learn the key differences between LangChain and LangGraph, two powerful frameworks for building AI applications. Discover when to use simple chains, when to build autonomous agents, and how to choose the right tool for your workflow, scalability, and complexity needs.
Prompt Engineering Fundamentals: The Skills Every AI Builder Needs
Why do some people get amazing results from AI while others don't? The difference is often prompt engineering. Learn how to guide LLMs, improve reasoning, enforce structure, and consistently generate better outputs using the techniques professionals rely on every day.