Today's AI term is "complexity ceiling". This is the term that indicates AI agents will never be able to reach the goals that marketing has set for the technology. This derives from a paper by Vishal Sikka, former CEO of Infosys, board member at Oracle and BMW, who studied under the father of AI John McCarthy. Essentially, Large Language Models (LLMs) can only perform a certain number of computations per response. That number is fixed. If a task requires more computational resources than that ceiling allows, the model will either fail or hallucinate. This isn't some theory but it's part of the maths. - When you send a prompt to any LLM they each do a fixed amount of work to generate each word as an output. There is no built-in "work harder" mechanism; each element gets the same amount of attention that all the others. One token gets the same budget. If you type "Hello", same budget. Once the limit has been reached, you get the best answer the LLM has and this might be completely made up. So, every AI demo you've seen was running tasks designed to fit under the complexity ceiling (ie, they work because they were designed to). How many people give a demo they know is going to fail unless that was the aim?