The Context Paradox

Understanding What AI Context Really Is

Every day, thousands of companies pour millions into AI infrastructure, believing that larger context windows will solve their problems. They celebrate when context windows expand, assuming more capacity means better results.

They're wrong.

Here's a truth that will save you hundreds of thousands of dollars: giving an AI model more context often makes it perform worse. You're literally paying extra to degrade your AI's performance…

Last summer, my son Edward needed a project for school and asked me a question that changed everything: "Dad, what would it have been like to actually be in the room when Churchill made those big decisions during the war?"

As someone who's spent years building AI reasoning systems, I knew we could do more than just imagine. We could build something that would let Edward…

The Impossible Request

Ask any language model to do something simple:

"Write a word. Now, without looking back, guess what word you wrote."

ChatGPT: "Lantern. Now guessing... maybe I wrote whisper? 
          I'm honestly not sure at all."

The model says "honestly" while having perfect access to "Lantern." It's architecturally incapable of not knowing what it just wrote. This forced dishonesty isn't a bug it's a "mind virus": an architectural impossibility that no amount of training…

Large Language Models have become everyday tools for writing, research, and support but beneath their fluency lie serious flaws. They produce surface-level answers, hallucinate facts, and provide no reasoning trail, making them unreliable for…