Main image of article Netflix CEO Explains Why He Pays Technologists Huge Salaries

For years, Netflix has maintained a reputation as a company that pays its technologists huge salaries. Data has backed up that assertion; for example, crowdsourced compensation numbers from suggest that Netflix’s software engineers can make nearly half a million dollars per year, well ahead of what they might earn at rivals such as Disney and Amazon. Why does the company pay so much?

In a posting on CNBC, Netflix CEO Reed Hastings walked through his reasoning, which is pretty straightforward: During Netflix’s relatively early days, he came to believe that “the best programmer doesn’t add 10 times the value” but “more like a 100 times.”

Moreover, Hastings thinks that an exceptional technologist’s abilities extend beyond coding or debugging faster than an “average” colleague: It’s also about the ability to tackle more abstract problems. “The reason the rock-star engineer is so much more valuable than his counterparts isn’t unique to programming,” he wrote. “The great software engineer is incredibly creative and can see conceptual patterns that others can’t.”

The focus on exceptional performers (and the budget they consume) also forces Netflix to embrace a “lean” workforce: “Managing people well is hard and takes a lot of effort,” he added. “Managing mediocre-performing employees is harder and more time consuming. By keeping our organization small and our teams lean, each manager has fewer people to manage and can therefore do a better job at it.”

Netflix has enjoyed a stratospheric rise over the past several years, coupled with burgeoning revenue. Hastings feels that those bottom-line results prove his theory correct. However, there’s a lot of debate in the tech industry about whether exceptional developers and engineers are actually multiple times more effective than other colleagues. 

Back in 2017, a developer named Jonathan Solorzano-Hamilton wrote a Medium posting that went super-viral within the tech industry. In that posting, he described working with an enormously talented developer (dubbed “Rick”) who did everything from architecting software products to solving troublesome bugs. There was just one little problem: Despite working around the clock, Rick became the organization’s bottleneck, refusing to accept help from a team who couldn’t possibly understand his “genius” work.

As Solorzano-Hamilton wrote: “I dove into the source code. Rick was right: no-one could possibly understand what Rick had created. Except for Rick. It was a reflection of the workings of his own mind. Some of it was very clever, a lot of it was copy-pasta, it was all very idiosyncratic, and it was not at all documented.”

Eventually, Rick snapped. Once he departed the company, the team of supposedly “mediocre” engineers redid his work to make it more elegant and efficient: “We didn’t have any mad geniuses building everything from scratch. But our productivity was never higher.”

Sure, Solorzano-Hamilton is just telling his personal story—but as one Fast Company article breaks down, the tech industry is filled with geniuses who thought they were infinitely better than the technologists around them… only for reality to come crashing in, either via blown deadlines or a broken software product. An exceptional developer is great, in other words, but their presence alone won’t magically solve issues or complete projects.

If you have the time, this Hacker News thread is also worth reading, because it neatly reveals the arguments for and against the “myth of the 10x developer.” Supporters of the theory like to point out (as Hastings does, in his CNBC article) research studies from the 1960s that show how skilled programmers are supposedly orders-of-magnitude more effective than their “average” colleagues. Meanwhile, many of the detractors don’t disagree that ultra-skilled developers and engineers exist—but their productivity hinges on a variety of other factors, including the skill of their team and the functionality of the overall company.

In any case, Hastings has leaned hard into this theory to justify paying his technologists huge sums of money. And so far, Netflix’s results seem to support his ideas. But with a variety of rivals entering the streaming space, including Disney and Apple, he’s also facing a new era of competition that will test his model.