Spotify's Best Engineers Haven't Written a Line of Code Since December

During Spotify's Q4 2025 earnings call on February 10, co-CEO Gustav Soderström made a statement that set the developer internet on fire:

"When I speak to my most senior engineers - the best developers we have - they actually say that they haven't written a single line of code since December. They actually only generate code and supervise it."

The claim went viral within hours. The TechCrunch article drew thousands of comments across Reddit, Hacker News, and Slashdot. Developers are divided between those who see the future arriving on schedule and those who see corporate delusion dressed up as innovation.

What Actually Changed

Soderström described Christmas 2025 as a "singular event" in AI productivity, when Anthropic's Claude Opus 4.5 became available. He used uncharacteristically romantic language for an earnings call: developer-AI relationships had "crossed the threshold" and "things just started working."

The commute scenario he described sounds like science fiction:

"An engineer at Spotify on their morning commute from Slack on their cell phone can tell Claude to fix a bug or add a new feature to the iOS app. And once Claude finishes that work, the engineer then gets a new version of the app, pushed to them on Slack on their phone, so that he can then merge it to production, all before they even arrive at the office."

But behind the headline is a seven-year infrastructure story that most coverage has ignored.

Inside Honk: Spotify's Coding Agent

The system making this possible is called Honk, and it did not appear overnight. It sits atop three layers of infrastructure Spotify has been building since 2020:

Spotify's engineering team published a detailed three-part blog series (November-December 2025) explaining how Honk works. The architecture is more careful than "just ask Claude to write code":

• The agent runs in sandboxed containers with restricted permissions, few binaries, and virtually no access to surrounding systems
• An LLM-as-judge layer evaluates every proposed diff against the original prompt, vetoing approximately 25% of changes
• When vetoed, agents successfully course-correct about 50% of the time
• Sessions are capped at 10 turns with 3 retries
• Each prompt targets one change only - combined changes exhaust context windows

What It Handles

Honk is not writing greenfield features from scratch. The task types are specific and well-scoped:

• Language modernization (Java records conversion)
• Dependency upgrades with breaking changes
• UI component migrations
• YAML/JSON configuration updates
• Architecture decision record generation

Chief Architect Niklas Gustavsson confirmed Claude as their "model of choice," noting that Spotify adopted Sonnet 4.5 as their default because it "currently leads on the metrics that matter for fleet-wide engineering at scale."

The Numbers

Those R&D savings land differently when you remember the context. Spotify has cut roughly 27% of its workforce since 2023 - approximately 2,300 jobs across three rounds of layoffs. Peak headcount was around 9,800; current staffing sits near 7,000.

The financial results are strong. Q4 revenue hit EUR 4.53 billion (up 13% constant currency), operating income rose 47% to EUR 701 million, and net income tripled year-over-year to EUR 1.17 billion. The stock jumped 14.75% on earnings day.

The Developer Backlash

The Reddit thread in r/technology drew 14,275 upvotes and 2,377 comments within 48 hours. The sentiment was overwhelmingly skeptical.

The most common criticism is the "whack-a-mole" problem - AI fixes one bug but introduces two more because it lacks holistic codebase understanding. Developers on Hacker News questioned how "best" was being measured: one commenter reframed it sarcastically - "developers who stopped coding are 'the best,' implying those still coding are less efficient."

The commute example drew particular fire. Multiple commenters flagged it as normalizing uncompensated labor. One Slashdot user called it "dystopian" - arguing it suggests forced office presence despite remote capability combined with an expectation to work during transit.

"Please don't work during your morning commute," one highly-upvoted comment read.

Others questioned how experienced engineers could approve code pushed via Slack on a phone without proper review. "This is the equivalent of a manager claiming zero bugs - met with laughter," wrote one Slashdot contributor.

The Research Backing the Skeptics

The skepticism has empirical support:

• Developers using AI coding tools scored 17% lower on coding comprehension tests despite completing tasks faster (January 2026 study)
• 45% of AI-generated code contains security vulnerabilities in the OWASP Top 10 (Veracode report)
• Code churn increased 39% in AI-heavy codebases (GitClear)
• A report titled "4x Velocity, 10x Vulnerabilities" from Apiiro quantified the tradeoff

Microsoft, which estimates 20-30% of its code is now AI-generated, appointed former EVP of Security Charlie Bell as a "quality czar" in February 2026 to address growing concerns.

The Nuanced Take

The most insightful analyses pointed out what Soderström's headline obscures: "not writing code" does not mean "not working." The role has shifted from typing syntax to specifying requirements clearly enough that AI can implement them correctly, then validating the output.

And Spotify's infrastructure - not the AI model - is the actual competitive advantage. The seven years spent building Backstage, Fleet Management, and comprehensive testing pipelines is what makes AI-generated code safe to ship. Most companies lack this foundation.

As one analysis put it: "When execution becomes cheap, strategy becomes the bottleneck."

The Product Quality Question

Critics point to Spotify's track record:

• Car Thing (2022): hardware product bricked via firmware update, cost $31.4 million, triggered a class action
• HiFi audio: announced in 2021, still unshipped five years later
• Two major outages in 2025
• Android app freezing and podcast crashes reported in late 2025
• 2024 Wrapped: backlash for AI-generated podcast content dismissed as "cringey" and "soulless"

If AI-generated code is so productive, the argument goes, why hasn't product quality improved proportionally?

What the Market Is Missing

The real story is not whether Spotify's developers write code. It is the economics. Spotify reduced R&D spending by 23% year-over-year while shipping more features and growing revenue 13%. If that ratio holds - and if other companies can replicate it - the implications for developer employment are significant.

Soderström was explicit about the stakes:

"There is going to have to be a lot of change in these tech companies if you want to stay competitive, and we are absolutely hell-bent on leading that change."

Spotify is not the only company moving this direction. Klarna deployed an AI customer service agent handling 65% of inquiries without human intervention. Duolingo replaced contract workers with AI. Stripe's AI Minions now ship 1,300 PRs per week. The pattern is consistent: automate, reduce headcount, maintain or increase output.

Whether this is progress or a race to the bottom depends on where you sit. But the numbers do not lie: two-thirds of Spotify's staff opted into Claude Code voluntarily. Whatever the internet thinks, the people inside the building are voting with their workflows.

Sources:

• Spotify says its best developers haven't written a line of code since December - TechCrunch
• Spotify says its top engineers haven't written code in months - TechSpot
• Spotify's Best Developers Haven't Written Code Since Dec - Slashdot
• Frustrated with Spotify updates? Take a guess who's to blame - Android Authority
• Spotify AI says its top software engineers no longer write code - HR Grapevine