Next-Token Prediction: How an AI Actually Writes Text (Not Magic — Just Probabil

<h1> How LLMs Work: A Journey Through Tokens, Attention, and Transformers </h1> <p>“My favourite rock band is…”</p> <p>How does a large language model take that unfinished

<h1> How Many R's in Strawberry? Your AI Has No Idea Why That's Hard </h1> <p>How many R's are in the word "strawberry"?</p> <p>If you ask ChatGPT, there's a decent chance you'll

<p>In the first eight weeks of 2026, ten major open-weight LLM architectures were released.</p> <p>GLM-5 matched GPT-5.2 and Claude Opus 4.6 on benchmarks. Step 3.5 Flash

<p>GPT-5.4 shipped on March 5. Seven weeks later, on April 23, 2026, OpenAI released GPT-5.5 — and the pace alone tells you something about where this race is headed. This isn't

<p>An LLM doesn't "know" that Paris is the capital of France the way a database row knows it. It doesn't understand your question, and it isn't reasoning before it answers.</p>

<h1> Fix Your Prompt Structure Before You Touch Your Infrastructure </h1> <p>Most engineering teams treat LLM inference costs as an infrastructure problem. They evaluate model

<p>You opened ChatGPT before Slack this morning.<br /><br /> Not for anything complicated. Just to figure out how to begin.</p> <p>That small move is already changing what

<p>"The Reasoning Trap." The line the authors won't quite say out loud is that the smarter your model gets at reasoning, the more likely it is to fabricate a tool that doesn't