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A “10x engineer” isn’t cool anymore. You know what’s cool? A “100x engineer.”
As the Silicon Valley saying goes, the “10x engineer” is capable of producing 10 times the work of their colleagues, developing projects and writing code at a quicker pace.
In the age of AI, a top-end engineer’s multiplier is itself getting a multiplier, according to Surge CEO Edwin Chen.
Chen boot-strapped his way to $1 billion in revenue. The CEO of Surge self-funded his company, taking no VC money — though he’s now reportedly looking to raise up to an additional $1 billion in capital. On the 20VC podcast, he said a “100x engineer” is now possible — and could help lean startups reach new heights.
“Already you have a lot of these single-person startups that are already doing $10 million in revenue,” Chen said. “If AI is adding all this efficiency, then yeah, I can definitely see this multiplying 100x to get to this $1 billion single-person company.”
Efficiency gains can be vital to startups looking to stay lean. Chen said that Surge was already “so much more efficient” than its peer companies like Scale AI, Surge’s biggest data labeling rival, which reportedly brought in $870 million in 2024 after multiple rounds of funding. Chen also said that Surge’s lack of a sales or PR team helped keep it lean.
While the “10x engineer” dates back to a 1968 study about programming performance, the term was later popularized among Silicon Valley executives. In his book “Zero to One,” Peter Thiel coined the “10x improvement” rule, claiming that startups needed to improve on existing alternatives by a factor of ten.
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Chen is a believer in the “10x engineer.” Some are 2-3x faster at coding, or work 2-3x harder, or have 2-3x less side tasks, he said. Multiplied together, engineers can reach 10x productivity.
“2-3x is often actually an understatement,” Chen said. “I know people who literally are five times more productive coders than anybody else.”
The advent of generative AI and coding tools supercharges Chen’s math: “Add in all the AI efficiencies that you get. You just multiply all those things out and you get to 100,” he said.
Agentic AI coding tools have taken over much of software engineering, writing code for developers, sometime with minimal human editing necessary. But these tools still need a prompt, which Chen said makes them most useful to those who have high-level ideas.
“It often just removes a lot of the drudgery of your day-to-day work,” Chen said. “I do think it disproportionately favors people who are already the ’10x engineers.'”
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