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TL;DR: Write As Little Code As Possible and Agentic Coding
Agentic coding tools have collapsed the friction of producing plausible software; output is no longer an issue. However, they have not collapsed the friction of knowing what is worth building, whether it fits the system, or whether users will change their behavior because of it, the much-desired outcome. When generating plausible code becomes cheap, every hour spent building the wrong thing becomes waste that can now be produced at scale. Discovery, validation, product judgment, and verification are what stand between your team and creating expensive waste at high-speed.
Thesis : AI made generating code cheap enough that weak product judgment can now scale. That is the problem this article addresses.
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🇩🇪 Zur deutschsprachigen Version des Artikels: ‘Schreiben Sie so wenig Code wie möglich’ war schon immer der Punkt. KI hat ihn nur dringend gemacht.
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The Bottleneck Was Never Typing Speed
Years ago, serving as an agile coach on an ambitious project of a large utility company, I shared with the engineers something they did not want to hear: I did not want them to write as much code as possible. I wanted them to write as little code as possible, just enough to solve the customer’s problem.
That required knowing what the problem actually was. So I asked them to join product discovery, sit in user interviews, and watch real people struggle with real workflows. Some of them resisted: they were more interested in solving puzzles, and writing code felt productive. In comparison, sitting in interviews felt like a waste of their time. But the engineers who showed up learned what "enough" meant. They stopped guessing what users needed, started watching what users actually did, and shipped useful features. The ones who stayed at their desks shipped "tickets."
Recently, someone on LinkedIn called "write as little code as possible" a wonderful aphorism. I consider it less an aphorism than a critical engineering discipline. And in 2026, it has become the single most urgent discipline in software development.
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