AI Mania Is Breaking Corporate Decision-Making: Billion-Dollar Strategies Written Without Ever Opening ChatGPT

Consultant Nik Suresh's essay "AI Mania Is Eviscerating Global Decision-Making," about how the hype around artificial intelligence is breaking decision-making at large companies, spread across Hacker News and reached developer Simon Willison on July 19, 2026. Suresh's central claim: multibillion-dollar AI strategies are often written by executives who have never opened ChatGPT themselves.

A $2 billion strategy without ChatGPT

Nik Suresh, who advises large corporations, cites an extreme case: an executive admitted he had never in his life used ChatGPT or any other AI tool. He said this immediately after releasing a technical strategy, built entirely around AI, for an organization with more than $2 billion in revenue. The essay is assembled from anonymous stories that engineers and managers inside "overexcited" companies tell the author.

"In one extreme case, an executive admitted he had never in his life used

ChatGPT or any AI tool, immediately after preparing a technical strategy for an organization with more than $2 billion in revenue, built entirely around artificial intelligence." — Nik Suresh, essay "AI Mania Is Eviscerating Global Decision-Making"

Key episodes Suresh describes:

• An AI strategy for a company with $2 billion+ in revenue, written by a person who had never sent a single prompt to a model
• "Token leaderboards": metrics that reward employees for making more calls to AI
• Client claims of "100x" productivity gains that nobody dares to challenge
• Engineers running AI on tasks they know are pointless, just to tick a box

Why nobody pushes back on the hype

The silence rests on fear of losing a contract, not just on marketing. Suresh asked a skeptical vendor executive why absurd promises get repeated without objection. The answer was not about "sales noise": executives on the client side had themselves publicly claimed 100x productivity gains.

"If someone on the vendor side said such a gain was implausible, it

would undermine the client executive's authority, be taken as an attack — or heresy — and could lead to termination of the enterprise contract." — from Nik Suresh's essay

The logic is simple: sinking an enterprise contract over an argument about something that doesn't affect the company's mission is a quick way to lose your job. As a result, an honest assessment of what AI actually delivers becomes disadvantageous to everyone in the deal at once, vendor and customer alike.

What happens to engineers

The pressure of the hype trickles down and turns into a simulation of work. One engineer described how, at a company with a "token leaderboard," he pulls a parallel copy of a working Go repository and orders AI to rewrite the whole thing in Zig. He works on something else in the meantime, doing it only to keep his numbers up on paper and hold on to his spot.

This scenario is a direct consequence of metrics that measure activity rather than results. When a KPI is tied to the number of tokens burned rather than to working code, employees rationally start wasting resources: the system rewards the volume of calls to the model, not the value they produce.

What this means

The problem is not the models themselves but how organizations make decisions under pressure from fashion. When a $2 billion strategy is written by someone with no hands-on experience, criticism is punished with the loss of a contract, and metrics reward token consumption, the company is optimizing for hype, not for results. Suresh's essay is a reminder that a grown-up conversation about what AI actually delivers is, for now, losing out to the fear of looking like a skeptic.