Gustav Söderström, Spotify's co-CEO, told investors on February 10 that the company's most experienced engineers "have not written a single line of code since December." They only generate code and supervise it. The tool doing the writing is Honk, an internal system built on Anthropic's Claude Code.
The workflow goes like this: an engineer on a morning commute opens Slack on their phone, tells Claude to fix a bug or add a feature to the iOS app, and gets a compiled version pushed back to them on Slack to test. If it passes, they merge to production. All before arriving at the office.
Söderström framed it as the beginning of something enormous. Software companies, he said, "will start producing enormously more amount of software." Spotify shipped more than 50 new features in 2025 — Prompted Playlists, Page Match for audiobooks, About This Song. Fourth quarter numbers backed up the optimism: 751 million monthly active users, 290 million premium subscribers, €701 million in operating income.
The market heard a company running faster than ever. Developers heard something different.
The Assembly Line
Within 48 hours of Söderström's statement, the quote had 14,275 upvotes on Reddit's r/technology. The consensus wasn't admiration.
Honk currently merges more than 650 agent-generated pull requests per month. That means Spotify's senior engineers spend their days reviewing machine output — reading code they didn't write, checking logic they didn't design, approving changes to systems they used to build by hand. Software engineer Siddhant Khare described the experience as "AI fatigue," likening the role to being "a judge at an assembly line."
The skepticism isn't theoretical. Research shows code churn increases 39% in AI-heavy codebases — more code written, more code rewritten, more code thrown away. A separate study found 88% of developers reported negative side effects from using AI tools, with 53% calling the generated code unreliable despite appearing correct. An Anthropic study from January 2026 found developers using AI scored 17% lower on comprehension tests, even as they completed tasks faster.
Faster and worse is a specific kind of improvement.
The People Who Aren't There
There's a detail Söderström didn't mention. Between 2023 and 2025, Spotify cut roughly 20% of its workforce — about 1,500 people. CEO Daniel Ek later admitted the layoffs "disrupted operations more than anticipated."
So the timeline reads: fire a fifth of your company, then announce the remaining engineers don't write code anymore. The unstated question is whether the engineers who lost their jobs were replaceable because of AI, or whether the engineers who stayed became supervisors because there was no one left to do the hands-on work.
Spotify isn't saying. But the sequence matters. When Söderström tells investors his best developers only supervise AI, he's describing a company that simultaneously reduced its human capacity and increased its dependence on a tool that, by multiple studies, produces code that is faster to ship and harder to trust.
The Copyright Hole
There's a quieter problem nobody on the earnings call mentioned. The U.S. Copyright Office has ruled that only works created by humans can be copyrighted. If Spotify's best engineers genuinely "have not written a single line of code" — if the code was generated by Claude and the humans only reviewed and approved it — the copyright status of Spotify's codebase is legally ambiguous.
This isn't an edge case. It's 650-plus pull requests a month of code whose authorship an engineer could truthfully deny under oath. No company has tested this in court yet. Spotify may not want to be the first.
What the Earnings Call Actually Said
Strip the press coverage and read what Söderström described. He didn't say AI is better than his engineers. He said his engineers are doing a different job now — one where they issue natural language instructions and approve results. The developer didn't disappear. The developer became a manager of something that writes code the way a junior developer might: quickly, confidently, and with a reliability rate that demands constant supervision.
That's not a breakthrough in how software is made. That's a change in who does the reviewing. And it answers a question nobody on the call asked: if senior engineers now spend their time supervising AI output, who's building the deep expertise that made them senior in the first place?
Spotify can't train new senior engineers by having them watch Claude. But it can report to investors that development velocity has never been higher. The gap between those two facts is where the risk lives.
Spotify paid out $11 billion to artists in 2025. It did not disclose how much of its product was built by a system that cannot own what it creates.
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