
Metrics, Intent, and the Drift Problem in AI-Assisted Development
8 min read
In my news feed, I recently saw a post from TechCrunch that talked about "tokenmaxxing" and how the use of LLM token usage as a metric for developer productivity wasn't having the desired effect. The article pointed out how various metrics over the years have been varying degrees of ineffective when it came to quantifying how productive developers were being. Other metrics included the number of lines of code (LoC) added to a project, the number of commits pushed to a repository, code acceptance rates, and many more.
The goal with these metrics is to find some way that the value of a developer can be reduced to a number that can be easily compared to other numbers. These numbers can be added to a spreadsheet, tracked over time, turned into graphs, and presented as objective signals of progress.
That approach is understandable, but it's also incomplete.


