Running on a treadmill at the gym at least burns a few calories; but sprinting on an AI coding treadmill is more likely to leave you exhausted, uncertain, and buried in technical debt.
“I wrote two thousand lines of code with AI today!” may be the most addictive temptation facing developers right now.
After analyzing more than 200 million lines of code , the software analytics team GitClear found that the real thing exploding after the spread of AI was not quality refactoring, but “code churn.” The proportion of freshly written code that is repeatedly overturned, modified, or simply deleted within two weeks has reached a historic high.
In physics, Brownian motion describes pollen particles being violently battered by water molecules from every direction, producing intense, random movement. But if you extend the time frame and calculate the vector, the probability of moving in any direction is equal, so the “average displacement” is actually zero.
The Turing Award-winning computer science pioneer Edsger W. Dijkstra offered a similar warning in a famous 1988 memorandum :
“If we wish to count lines of code, we should not regard them as ‘produced assets’ but as ‘spent costs.’”
AI really does let us produce (squander) code at ten times the speed, but unfortunately, it has not bought you ten times the distance forward.
As we gradually see this frantic running in place for what it is…