After Ten Years at Google, He Decided to Go Start Something

Huang graduated from Peking University in 2014 and joined Google, landing in London because of visa timing. It was the golden age of big-tech food: sushi every day in the cafeteria, and grilled steak, pork chops, and lamb chops in the evening, sometimes even venison. Ten years later he left and started a company. The first direction was an AI version of TikTok, with everything generated by AI; they worked on it for a while and gave up, because they didn’t believe anyone would actually use it. Then in early 2026 a product called moltbook had its moment doing the same thing. The team is small now: after AI arrived, the company trimmed a lot of people, interns especially, because if someone can’t own a piece of work end to end, the friction of communicating with them isn’t worth it compared to just using AI. When I asked him what mattered most in two years of building, he said it’s the team’s end-to-end response speed: find a problem in the morning, propose a fix at noon, ship it in the afternoon, then immediately collect real user feedback, a full product loop closed in a single day.

The cafeteria at Google London used to have sushi every day, and in the evening there was grilled steak, pork chops, and lamb chops, sometimes even venison.

In 2014, Huang graduated from Peking University, applied for a software engineer role at Google from China, and got the offer. Because of his visa, he landed first at Google in the UK. Those were the golden years of big-tech food, right up until Pichai became CEO and the cafeteria went into a straight-line decline. Later he had the chance to transfer back to headquarters, so he went to Silicon Valley, and found that in the restaurants everyone was talking about total comp, about houses, about their kids’ schooling.

He thought life in London was more interesting, so he came back.

In 2024, he left the employer he had been with for a full decade and started a company. His mindset at the time was to give it a shot: even if it didn’t work out, going back to China afterward to spend time with his parents would be fine too.

But the longer he worked on it, the more serious it got. He didn’t want to give up easily, and couldn’t.

When he first started out, the story he told investors was an AI version of TikTok, with all the content generated by AI. They worked on it for a while, then dropped it. They didn’t believe anyone would actually use it.

By early 2026, a product called moltbook had a moment of popularity doing something similar. Huang was a little taken aback, and what he felt then was: “The world is one giant amateur operation.”

Sure enough, before long nobody was talking about moltbook anymore.

Over two years of building, the product direction changed many times. Right now the focus is on an email app. After AI arrived, the company trimmed a lot of people, interns especially. In their CTO’s words: “If a person can’t own a piece of work end to end, and communicating with them takes more than handing off a task once, then given that communication friction, you may as well just use AI.”

So the team is small, and everyone owns their own piece end to end.

I asked him what he thought mattered most across two years of building.

He said it’s the team’s end-to-end response speed.

An investor had told him about Airbnb: even at a certain scale, that company could still find a problem in the morning, meet at noon to propose a fix, build the change in the afternoon, and then immediately collect real user feedback to judge whether the change was right. A complete product loop, closed in one day. End-to-end response speed is an enormous competitive advantage.

I agree with that, except end-to-end is easy to say. Many products can’t even get decent user feedback in their early days, and real feedback from the market is a precious thing.

He went on: “We’re working on finding that loop. It should be soon.”