Why Does the AI Field Keep Reinventing Things We Already Knew? A Case for Treating AI Like a Person
Prompt engineer. Context engineer. Spec-driven development. Harness. Loop engineer. Context minimalism. Tokenmaxxing.
A new term lands every week. The smartest people in tech are pouring into AI, and ideas collide fast — CTOs taking IC roles at Anthropic, researchers shipping frameworks before the last one has been absorbed. The vocabulary is exciting. It's also exhausting. And some of it turns out to be wrong.
Tokenmaxxing already showed cracks. Process-heavy agent frameworks are losing ground. Every few months something that felt foundational quietly gets replaced.
I kept looking for the underlying logic. What actually persists? Then a friend said something that stopped me mid-scroll.
"Treat AI as labor. Instead of inventing new concepts for something entirely unprecedented and making it increasingly complex, design your verification and management methods according to how you'd manage people."
That one sentence turned out to explain almost everything.