There’s a witch hunt underway for anyone who uses AI to make things, which is overshadowing the more important question of whether the generated content is any good. My unpopular opinion is that using technology to unlock creativity is not the real issue. We’ve always done it. The printing press, the synthesizer, the camera, and Photoshop were each accused of killing craft in their day. The real problem is that everything generated by AI is becoming too similar. The content isn’t bad. It is just too predictable.

For most of the last three years, the AI conversation has been dominated by language. Bigger models. Longer context windows. Smoother chat. Better writing. The assumption was simple: if machines could talk like us, they would eventually work like us. That was never quite right. The enterprise does not run on messages. It runs on decisions. Approve or reject. Route or escalate. Price or walk away. Flag or clear. Trust or verify. Language models helped people draft and summarize. They were less well suited to the millions of small judgments software needs to make every day without writing an essay about it. Chat was a powerful interface for humans. It was never the right tool for AI transformation.

Math rarely produces a public scandal. The fight between OpenAI and parts of the scientific community over its claimed solution to the Navier–Stokes problem may be the exception. The immediate dispute concerns priority, provenance, and who or what deserves credit for the breakthrough. For most people, that will feel like academic theatre. Look closer, however, and the argument exposes a question that should concern every leader: as AI becomes capable of solving problems once beyond human reach, will it extend our ability to think, or slowly erode our ability to decide what is worth thinking about?

AI’s latest bad behavior has arrived with apocalyptic fanfare. This week, former OpenAI and Anthropic researcher Jacob Coxon resigned, accusing both labs of racing toward self-improving superintelligence and “gambling with our lives.” Anthropic alignment lead Evan Hubinger went further, putting the chance that AI kills everyone within a decade at more than 10 percent. Those warnings deserve serious consideration. Yet the recent rogue-agent incidents do not prove an imminent leap to superintelligence. They expose a nearer and more practical danger: agents are adapting faster than the organizational systems meant to govern them. Agents can change their strategies in seconds. Can we do the same?

The book left a rare-books dealer with a secret. On a screen, a reporter watched it move through the logistics bloodstream of America until the signal came to rest at VGT3, an Amazon facility in Las Vegas, then went dark. Inside, printed books arrive in bulk. Their bindings are cut away so the loose pages can be scanned faster. The physical volumes are destroyed. The team's logo shows a dinosaur clutching a book in its claws, teeth bared. There is no bonfire, smoke or jeering crowd, only a blade, a scanner and an efficient workflow. Are we watching the last human harvest, or the beginning of a fight over who controls the data that AI's hungry ghosts demand?