This article discusses how the introduction of Large Language Models (LLMs) has fundamentally changed search engine optimization (SEO). It argues that while traditional SEO techniques remain relevant, their effectiveness has shifted due to the new methods LLMs use to generate answers. The author provides a mathematical perspective on this transformation and highlights how different strategies may perform under the new search paradigm.

A new method for trip planning using large language models (LLMs) has been developed, combining LLMs' ability to understand qualitative user preferences with optimization algorithms that address quantitative constraints. This hybrid approach enhances the feasibility of suggested itineraries by grounding them in real-world data and ensuring that logistical requirements are met while preserving user intent. Future applications of LLMs in everyday tasks are also anticipated.