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AI Fundamentals
Tokens, context windows, and temperature — not as definitions, but as the mental models you'll use every time you write a prompt or debug a model call.
Written by
Pratyaksh Singh
LinkedIn
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.
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.
Read →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.
Read →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.
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