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Factory’s Matan Grinberg and Eno Reyes Unleash the Droids on Software Development
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Focus on Organizational Metrics for AI Products
Organizations should focus on organizational metrics rather than specific AI product metrics to demonstrate success to executive teams effectively. Auto-complete acceptance rates, although considered a success metric for AI products like CoPilot, might not resonate with executives who are focused on business objectives. The use of auto-complete tools can lead to increased code churn by 20 to 40%, impacting the overall efficiency. A holistic approach involving org-wide metrics such as cycle completion speed and code churn across repositories provides a better understanding of performance. By emphasizing saving engineering time, increasing speed, and improving code quality, organizations can align with engineering leaders on goals. Engineering velocity, as the main metric encompassing these aspects, serves as a key indicator for enhancing overall productivity and efficiency in organizations.
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