James Shore proposes randomized with-AI and without-AI tests to measure AI's software productivity
Overview
James Shore, writing in O'Reilly Radar, argues that AI's effect on software productivity cannot be measured by delivery speed, estimates, or story counts.
He defines productivity as value produced divided by money spent, and says delivery speed is only one part of that. His proposed method compares each team with itself, using randomized, interleaved tasks done with AI and without it. This is part 2 of his series.
Written by AI from the articles below · updated Nov 4, 7:41 AM ET
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Developments
2 developments
- Nov 4, 6:54 AM ET · 1 articleMeasuring AI's impact on software delivery speed requires controlled comparisonsO'Reilly Radar: Measuring AI's impact on software delivery speed requires controlled comparisons
- Oct 28, 6:54 AM ET · 1 articleAre you getting your money's worth from AI? James Shore outlines how to measure itO'Reilly Radar: Are you getting your money's worth from AI? James Shore outlines how to measure it
Article timeline
The articles in this story. Times are ET.
- O'Reilly RadarBlogMeasuring AI's impact on software delivery speed requires controlled comparisons
AIJames Shore argues that delivery speed is only a component of software productivity, which he defines as value produced divided by money spent. He says estimates and story counts cannot show whether AI makes teams faster, so teams should be compared to themselves using randomized, interleaved with-AI and without-AI tasks. This is part 2 of his series, published on O'Reilly Radar.
- O'Reilly RadarBlogAre you getting your money's worth from AI? James Shore outlines how to measure it
AIJames Shore's essay series argues engineering leaders need hard data on AI's costs and benefits before cutting staff budgets. He cites a CIO who measured a 2.1x productivity gain while top AI users spent $21,000 per month on tokens. The series covers delivery speed, unintended consequences, business outcomes and a CFO note, and warns against measuring lines of code or pull requests.
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