ChatGPT as the Original AI Error (paulkedrosky.com)

An influential critique argues that ChatGPT’s greatest contribution may also be its original error: turning AI into “chat” first and foremost. Because humans equate human-like conversation with intelligence—rooted in our evolutionary obsession with speech—chat interfaces achieved explosive adoption (ChatGPT became the fastest‑growing consumer tech product). But that conversational instinct has led companies to bolt chat UIs onto products where they add little value or create friction, from sales tools to factory equipment, simply because chat is seductive, not necessarily useful. Technically, the piece reframes LLMs as grammar engines that predict likely tokens rather than minds that “understand” people. That suggests a more powerful, less glamorous frontier: machine‑to‑machine communication across thousands of rigid machine languages and protocols. Use cases like procurement systems negotiating supplier formats, logistics address alignment, and financial identifier validation reward speed, accuracy, and strict grammars over fluency or charm. The implication for AI/ML practitioners is practical: stop defaulting to chat as the UI; design LLM integrations that exploit structured token prediction for backend automation, protocol translation, and invisible infrastructure—boring, invisible, and ultimately indispensable work.