Understanding Tokens and Context Windows

Tokens are the fundamental building blocks of Large Language Models (LLMs). At their core, LLMs function as chat completion systems that predict the next sequence of text based on the input provided. This text is broken down into small units called tokens.
Tokens are the basic unit of processing in LLMs. Whether you're chatting with an LLM or using advanced AI agents, everything — from input to output — is calculated and billed in tokens.
The context window refers to the maximum number of tokens (input + output) that an LLM can process in a single request. Understanding tokens and context windows is crucial because every token comes with a cost. Without being context-aware, it's easy to waste both tokens and money.
With a few simple optimizations, you can significantly reduce token usage and enjoy a smoother, more efficient experience when coding with AI agents.
Mastering tokens and context windows will not only help you save money but also enable you to write more precise, effective prompts — allowing you to get the most out of every interaction. Find out more in the full article below;
https://developer-chris.com/blogs/tokens-context-windows-and-cost-in-ai-assisted-coding