Inside a Tokenizer’s Head: Why Your LLM Prompt Isn’t What You Believe It Is
Last Updated on October 15, 2025 by Editorial Team
Author(s): Dr Abdullah Azhar
Originally published on Towards AI.
Inside a Tokenizer’s Head: Why Your LLM Prompt Isn’t What You Believe It Is
I recall being gaslighted by an LLM for the first time.
The article explores how large language models (LLMs) interpret prompts differently from human language, focusing on the importance of understanding tokenization, which involves breaking down words into tokens that the model processes. It discusses the nuances of how language prompts are tokenized, the implications of misinterpretation, and how understanding these principles can enhance prompt engineering for better results when interacting with these models.
Read the full blog for free on Medium.
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