The Youngest Gen Z AI Builders Say Companies Will Soon Run Themselves. Their Own Generation Is Getting Angrier.

A thread about San Francisco's AI kids

An X post from that circulated this week described talking with the Gen Z engineers and founders working at the edge of AI in San Francisco. The author said those conversations can break your mind a little bit, that major outlets are nowhere near repeating what these builders believe, and that the author is starting to think they're correct.

Replies split along familiar lines. Several people asked for specifics and called the post hype. One wrote that AI began running entire companies a year ago. A follow-up in the thread answered the doubters by arguing that the conditions these predictions depend on keep being met.

For enterprise leaders, the thread matters less as a forecast than as a look at the people who will soon join their engineering, data and product teams. Survey data suggests those people do not share a single view of AI.

Adoption has stalled outside the frontier

Some measures do show young people moving first. A February survey of 1,448 U.S. adults by the browser company Shift found that 47% of 18- to 24-year-olds now start searches with an AI tool, while 58% of all Americans still begin with a search engine. Daily use was highest among 25- to 34-year-olds, at 43%, compared with 32% across all ages.

The wider generation looks different. Gallup, the Walton Family Foundation and GSV Ventures surveyed 1,572 Americans aged 14 to 29 between February 24 and March 4. Twenty-two percent use AI daily and 29% use it weekly, roughly the same share as in 2025.

Attitudes fell over the same period. The share who said AI makes them excited dropped from 36% to 22%, and the share who felt hopeful fell from 27% to 18%. The share who said it makes them angry rose from 22% to 31%.

Gallup senior education researcher Zach Hrynowski told Axios that the oldest respondents were the angriest and tied that to AI's effect on entry-level jobs. Shift found a similar reaction among younger adults, with 34% of 18- to 24-year-olds saying AI is already far too dominant.

Payroll data points to the same pressure. Stanford Digital Economy Lab researchers Erik Brynjolfsson, Bharat Chandar and Ruyu Chen revised their "Canaries in the Coal Mine" paper in August using ADP records through June 2026. Employment of 22- to 25-year-olds in AI-exposed occupations now sits 19% below where it would be if it had kept pace with less-exposed peers, and the gap has widened since the researchers first reported it in August 2025. The authors found no economy-wide displacement and said the decline comes mainly from companies hiring fewer young workers, not from layoffs.

Gallup also found that attitudes track closely with how often people use AI. Daily users reported more curiosity, excitement and hope than weekly users, which puts the heaviest users much closer to the builders described in the thread.

What the insiders expect

In the original post, @carrynointerest said the young builders' views go far beyond anything in mainstream coverage and listed three of them. Most are convinced the AI labs are entering a 15- to 20-year cycle of dominance. They expect that everything that can be farmed for tokens, which they call a "sensor," will be. And they believe AI will run entire companies in the near future.

Replies challenged each point. One said anyone using the 15- to 20-year figure is misleading people. Another argued the opposite of lab dominance, predicting the labs will be commoditized, broken up and bought by the big tech companies, with Google winning in the dullest way possible. Someone else pushed the company claim further and predicted AI would run the IRS and eventually the rest of government.

A reply about compute raised a separate point. It argued that the U.S. national security apparatus has far fewer GPUs than the Magnificent Seven tech companies. If capability keeps scaling with compute, that gap would leave a handful of private firms with more AI capacity than the government.

What distinguishes this group is its starting assumption. Most public debate still centers on whether AI will reshape business. The builders in the thread take that as given and focus on what comes after. Because they work with new models as soon as they ship, their expectations follow current capability rather than older expert forecasts.

The thread's claim that these predictions keep coming true has some support in company financials. Epoch AI estimated in May that Anthropic and OpenAI bring in roughly $9 million and $5.5 million in revenue per employee, more than any public tech company on the Forbes Global 2000. Apple's most recent 10-K works out to about $2.5 million per employee, and Google's to about $2.1 million. Neither lab is run by AI, but both are producing revenue at a scale that used to require far larger workforces.

Why enterprises won't hand over the keys yet

The strongest pushback in the thread came from people describing constraints that enterprise leaders deal with every day.

One reply argued that capability and adoption are separate problems. Companies are unlikely to give autonomous systems open access to proprietary data, intellectual property and critical processes while regulation, liability and security questions remain open. Another asked who would insure a company run by AI. A third predicted that the first AI-run company to fail because of a hallucination would set the idea back for everyone.

The insurance question already has a partial answer. In May 2025, insurers at Lloyd's of London began underwriting policies from the Y Combinator-backed startup Armilla that cover legal claims when an AI tool underperforms. The policies pay out only when a system falls well below its original performance benchmark, and one underwriter said it would turn away systems it judged too error-prone. Companies already running heavy automation are drawing similar lines. Coinbase pulled one category of support case back to human specialists after its agent gave customers accurate answers about mistakes they could not undo.

Others questioned where the predictions come from. One reply said they sound like the views of people who have only run tech startups, and that large non-tech companies have so far deployed little beyond customer service chatbots. Another user answered that this criticism reflected 2023 conditions.

A more measured reply accepted the end state and questioned the timeline. It argued that hard-asset and physical-service industries have fewer feedback loops and slower iteration cycles, which makes them harder for AI systems to improve within. On that view, software-heavy functions would be automated first, and operations tied to physical goods would follow much later.

What this means for the workforce enterprises are hiring

Coverage of Gen Z and AI tends to treat the generation as either enthusiastic adopters or resentful skeptics. The Gallup data indicates that both groups exist and that the main dividing line is how often someone uses the tools. Casual users report more concern about jobs, and daily users report more optimism.

For hiring managers, that means new graduates will arrive with very different expectations. Some will push to automate work that current processes still route through people. Others will be wary of AI and what it means for their careers, and they are applying into a market where 46% of employers already use AI to read resumes. McKinsey's projection that 11 million U.S. workers will have to start over by 2035 suggests that tension will last.

The San Francisco builders may be early on autonomous companies, and the skeptics may be right that liability will slow things down. For enterprises, the more pressing fact is already in the payroll data. The workers most eager to hand their jobs to AI are the youngest ones, and they belong to the same age group whose entry-level openings are disappearing fastest. Many companies are now hiring people who will spend their first years automating the jobs their predecessors started in.