When I first encountered Unix, I was intrigued by its minimalist approach compared to the colorful but fragile Windows 3.1. The blinking command-line cursor initially seemed daunting, but it soon became a playground where I could exercise self-efficacy. Learning about POSIX standards, GNU tools, and the pioneering hackers who made this software freely available deepened my appreciation for Unix-like systems.

Over the years, I've remained an avid Linux user, drawn by its flexibility and the ability to mold it like digital clay. Command-line tools, though decades old, still work remarkably well. For instance, extracting domain names from Python files using rg, grep, awk, and sort demonstrates the power of combining simple tools that adhere to the Unix philosophy: write programs that do one thing and do it well, work together, and handle text streams as a universal interface.

Interestingly, large language models (LLMs) embody this philosophy. They present a simple input box, daring users to dream big, much like the Unix prompt. Instead of needing to know complex shell commands, users can now ask an LLM to translate natural language queries into shell scripts. While LLMs are not perfect—sometimes lacking context or producing platform-specific commands—they understand that text is the universal interface. This shift from GUIs back to text-based interaction vindicates the Unix approach, proving that Unix won in the age of AI.