Measuring hidden costs of AI-assisted software development
Overview
James Shore argues that AI-assisted software development has unintended costs, including code that is harder to maintain, developer burnout, and lock-in from token costs, and that these have real economic impact.
His republished Successful Software post, carried by O'Reilly Radar, proposes cost of change as the central measure. Shore suggests tracking it through value-add percentage, DORA metrics, and token usage. He says these indicators are noisy and lagging, so decisions will have to rest on judgment informed by them.
Written by AI from the articles below · updated Nov 11, 11:18 AM ET
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- O'Reilly RadarBlogMeasuring AI's unintended consequences on maintainability, burnout, and lock-in
AIJames Shore's Successful Software blog, republished on O'Reilly Radar, argues that AI's unintended consequences such as harder-to-maintain code, burnout, and token-cost lock-in have real economic impact. The article proposes cost of change as the central measure, tracked through value-add percentage, DORA metrics, and token usage. It says these indicators are noisy and lagging, so decisions will rest on judgment informed by them.
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