Claude Code (Anthropic’s agentic coding tool) now has run-rate revenue above $2.5 billion, having more than doubled since the beginning of 2026. Business subscriptions have quadrupled since the start of the year, and enterprise use has grown to represent over half of all Claude Code revenue.
Software engineers have always been the rate-limiting factor for every startup I’ve invested in. You can never hire enough. The Fortune 500 barely gets any – they all flow to Silicon Valley. Now you can buy intelligence on a metered basis. Pay per token. No recruiting, no vetting, no retention, no equity. Just intelligence as a utility. Consumers pay $20/month. Enterprise power users pay $200/month. And companies are spending millions per year because the ROI is there.
In academia, to use AI marks you in the same way as voting Brexit, or insisting on the reality of biological sex: you are someone who lacks discernment, who isn’t a member of the tribe.
…The academy’s refusal to even consider how to positively incorporate AI is a form of gatekeeping. My colleagues wish to insist that academics alone are the legitimate purveyors of knowledge. This is apparent from their tone, a mixture of moral panic and wounded authority, which seems clerical in nature. “I can’t trust students.” “My judgement is under siege.” “Why teach at all?”
The Conference on College Composition and Communication, the primary professional organization for writing educators, just passed a resolution affirming the right of students and faculty to categorically refuse the use of generative AI in the classroom. The productivity benefits of the technology are dismissed as unsubstantiated claims; adoption is characterized as corporate intrusion by Big Tech. Members are instructed to reject the workforce preparation justification, insisting instead that the writing classroom must remain a space for processing feelings and engaging in civic participation.
Victoria Oldemburgo de Mello and others write,
Our research reveals that for a meaningful segment of the public, resistance to AI is moral in nature: a conviction that AI use is fundamentally wrong, not merely impractical. This moral opposition generalizes across applications and predicts real behavioral reluctance to use AI even when it would be personally advantageous. These findings reframe AI adoption as a challenge that cannot be solved through technological improvement alone, pointing instead to the need for strategies that engage the moral dimensions of public attitudes.
Pointer from Tyler Cowen. I see a lot of intense negativity toward AI. There are legitimate criticisms to be made, but most of the complaints come across to me as not well informed. People see AI as “not creative,” whereas I see creativity as searching the “adjacent possible,” and AI can do that at least as well as humans. People see AI as undermining literacy, when I think that other uses of the Internet are more harmful.
I asked Claude if the automobile caused a similar reaction in its early days. The conclusion:
So in short: yes, the auto backlash was intense and widespread, particularly in the 1900s–1920s. But it was arguably more reactive (responding to visible carnage on streets) whereas AI anxiety today is more anticipatory — trying to reason about harms before they fully materialize.
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You should review SarbOx before deciding that corporate America is going to use AI to develop one-off apps, let alone one integrated into highly regulated/audited systems.
https://www.metricstream.com/insights/sox-it-controls.htm
The CEO is technically risking jail time for violations.
Bad arguments against AI do not make it good. Pointing out the bad arguments against AI is a rather weak endorsement of AI.
It is worth pointing out that the value of AI for production is very different from its value in education. Yes, education is a product. Yes, applied learning (such as for software development) has value. But general learning is a tricky thing. I'm aware of no studies proving technology, beyond writing and maybe calculators, advances learning. The best evidence, which I have doubts about, suggests it retards learning more than it helps. Should we expect different from AI? Caution seems advisable. It seems the conservative approach.