AI Build Traps: Usage, Output, and Outcomes (How perverse incentives around token usage create cobra farms)

Organizations have long struggled with answering the question: "How do we measure developer productivity?" In the past, some organizations have taken to measuring lines of code produced per engineer. Others have measured the number of tickets closed. Others measure the number of pull requests (PRs) merged. And now in the age of AI, we've started measuring token usage. Proxy metrics The problem with all of these metrics is that they're not actually measurements of developer productivity — they're proxy metrics. And with any proxy metric, once you start measuring something, that metric becomes the goal. This is especially true if that metric has financial incentives or performance ratings tied to it. Measuring lines of code? Great, engineers will start writing overly verbose PRs in order to write more lines. Goodbye concise functions and reusable code. Measuring number of tickets closed? Great, engineers will start creating tickets for everything , and they'll break tasks down into the s