AI is Making Us Faster, More Productive, and Worse at Thinking
April 11, 2026 – 7:30 am
AI is everywhere, the pressure to adopt it is relentless, and the evidence that it’s making us smarter is getting thinner by the quarter. On New Year’s Day 2026, a programmer named Steve Yegge launched an open-source platform called Gas Town. It lets users orchestrate swarms of AI coding agents simultaneously, assembling software at speeds no single human could match. One of the first people to try it described the experience in terms that had nothing to do with productivity:
"There’s really too much going on for you to comprehend reasonably," he wrote. "I had a palpable sense of stress watching it."
That sentence should be pinned to the wall of every executive suite, every venture capital boardroom, and every CES keynote stage where the word “intelligence” is thrown around like confetti. Because something strange is happening in the relationship between humans and the technology we keep calling intelligent.
The machines are getting faster. The humans interacting with them are getting more exhausted, more anxious, and, by several measures, less capable of the one thing intelligence was supposed to enhance: thinking clearly.
The pressure to adopt AI is now so pervasive that it has developed its own vocabulary of coercion. You need to have AI. You need to use AI. You need to buy AI. Your competitors are already using it. Your children will fall behind without it. The language does not come from engineers quietly solving problems. It comes from earnings calls, product launches, and LinkedIn posts written with the manic energy of people who have confused selling a product with describing reality.
In January 2026, at the World Economic Forum in Davos, Microsoft CEO Satya Nadella offered a phrase so revealing it deserves to be studied as a cultural artefact. He warned that AI risked losing its “social permission” to consume vast quantities of energy unless it started delivering tangible benefits to people’s lives. The framing was striking: not a question of whether the technology works, but of whether the public can be kept on board while the industry figures out if it does. Nadella called AI a “cognitive amplifier,” offering “access to infinite minds.”
A month later, a Circana survey of US consumers found that 35% of them did not want AI on their devices at all. The top reason was not confusion or technophobia. It was simpler than that: they said they did not need it.
The gap between the rhetoric and the evidence has become difficult to ignore. In March 2026, Goldman Sachs published an analysis of fourth-quarter earnings data and found, in the words of senior economist Ronnie Walker, “no meaningful relationship between productivity and AI adoption at the economy-wide level.” The bank noted that a record 70% of S&P 500 management teams had discussed AI on their earnings calls. Only 10% had quantified its impact on specific use cases. One per cent had quantified it as negative.