An Interview with an xAI Engineer

We called at midnight on a Sunday. The office behind him was lit like noon and full of voices.

Based on an interview with an AI engineer at xAI, who asked not to be named.

Leaving big tech for the underdog

He joined a large US tech company in 2020, early in its AI push, and spent about three years on agents and tool calling. He trained models and built agent loops. Then xAI called.

What decided it was the talent density. His prospective manager was a well known deep learning researcher who built one of the optimizers now used in nearly every large model training run. The offer beat the other labs, and there was the specific energy of a challenger moving fast.

The density was real once he arrived. His previous company was full of people from Stanford, MIT, and Harvard, but he said the intensity there did not come close to what he found in San Francisco.

One surprise was that age carried no weight. People much younger than him were leading, and they were genuinely good. It convinced him that leaning on seniority was a mistake. He pointed to a broader pattern: senior engineers at strong companies now take non-senior roles at companies closer to the frontier, on the theory that proximity to the work matters more than the title.

What the hours actually look like

The call happened past midnight on a Sunday, his time. The office behind him was lit like noon and full of conversation.

China has 996, meaning nine to nine, six days a week. He said the Valley right now runs harder than that. Weekend work is assumed, and team meetings were on the calendar for 3pm on both Saturday and Sunday.

"Everything except breathing is work time."

San Francisco is expensive enough that losing a job there threatens your ability to live there at all. That pressure compounds the pace. Underneath it is a shared belief across every lab: fall behind now in AI and there is no path back.

The weekly meeting

Nearly every team at xAI meets Elon Musk in person once a week. During the stretch when he was focused on xAI, some teams briefed him three times a week.

Asked what he is like up close, the answer was direct. Scarier than he looks in the press. The style is less consensus-building executive and more set-the-direction-and-push. He did not frame that as purely bad. Small fast organizations often move better on strong direction than on democratic agreement, and that method produced two very hard companies.

The message pushed hardest across the org was usefulness. If the AI is not useful it does not matter. Not novelty, not surprise, but something that actually helps in someone's work or life. Anything not connected to that gets cut, and that became the judgment criterion for every team.

His technical depth was real. He enjoys engineering conversations and digs into anything that sounds soft. Report that a training run takes a hundred hours and the response comes back:

"Why does it have to be a hundred hours? There is an improvement somewhere. Get it to twenty."

There were costs too. AI is unlike ordinary engineering in that research needs slack. Building models, cleaning data, and running training all require patience, and patience was in short supply.

A cofounder who worked closely with him left a line that stuck. Musk cares less about whether a decision is right today and more about eventually. Things that look wrong in the moment have a track record of arriving. The irony is that the cofounder left the company not long after saying it.

Macrohard

The project announced earlier this year had actually started the previous September as xAI's first. The name was a swing at Microsoft, and the goal was to control a computer with AI.

The instruction was specific: build it on the same model architecture as the self-driving stack. In his view, operating a computer was the same problem as driving, and easier, since a mistake behind the wheel can kill someone and a mistake on a screen cannot.

The team disagreed. Roads are standardized. Follow the lines, stop on red, go on green. There is not much planning or reasoning involved. Operating a computer is different: pressing the button is not the hard part, knowing why that button and what follows from it is. They argued it was a fundamentally different problem.

After several months of work, Macrohard moved to Tesla.

A lab losing people

xAI's position is not comfortable. Most cofounders are gone, many lead researchers have left, and departures continue. AI is a field where you cannot compete without people.

He gave two reasons the hiring still works. One is that the intensity does not register from the outside no matter how it is described. The other is that working face to face with someone like that is rare enough to be worth something on its own.

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