The software industry doesn't agree on much. Tabs versus spaces, monoliths versus microservices, whether stand-ups are useful or performance art—pick a topic and you'll find engineers ready to die on both hills. But for about forty years, we had one consensus: lines of code is a terrible metric.
Dijkstra called it "a very costly measuring unit because it encourages the writing of insipid code." Lines are spent, not produced. Bill Gates compared measuring programming progress by lines of code to measuring aircraft building progress by weight. Ken Thompson said one of his most productive days was throwing away a thousand lines.
In 2009, Tom DeMarco—the man who wrote "you can't control what you can't measure"—formally retracted the statement. Software projects, he concluded, are fundamentally experimental; the important goal is transformation, not control. By 2023, Kent Beck was calling LOC "an input metric"—the worst category. "Only use it if you have nothing else to measure success with."
That was the consensus. Settled. Done.
Then AI showed up, and we brought it back.
The Resurrection
Every major tech CEO is now competing on what percentage of their code is written by AI. Watch the progression.
Sundar Pichai told investors in October 2024 that 25% of Google's new code was AI-generated. By mid-2025, that number climbed past 30%. Satya Nadella said "maybe 20%, 30%" of Microsoft's code is now written by software. Mark Zuckerberg predicted AI would handle half of Meta's development within a year. And Dario Amodei predicted 90% of code would be AI-written within six months; when the deadline passed, he revised the claim to "70, 80, 90% of the code written at Anthropic is written by Claude."
Twenty-five percent. Thirty percent. Fifty percent. Ninety percent. The numbers only go up, and they're presented as achievements—on earnings calls, in press releases, at conferences. Nobody is reporting "percentage of bugs introduced by AI-generated code" or "percentage of AI code that survived review unchanged." Nobody is mentioning how much of that generated code was thrown away, reworked, or never deployed. The headline metric is volume. LOC by another name.
The tooling reinforces it. GitHub Copilot's dashboard shows "Total Lines Suggested" and "Total Lines Accepted" as primary metrics. Cursor tracks lines added per user, reporting a 28.6% increase following adoption. The industry generated 256 billion lines of AI-written code in 2024 alone. That number is treated as progress.
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