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¡Hola, soy DORA. Why hasn't AI improved my metrics?

Despite AI tools accelerating code generation, DORA metrics like deployment frequency and lead time have not improved because the focus has shifted to specification and review, leaving overall throughput unchanged. This article examines the impact of AI workflows on traditional measurements and suggests adopting more comprehensive metrics such as cycle time variants, SPACE, and DevEx.

SourceHacker News AIAuthor: gpi
¡Hola, soy DORA. Why hasn't AI improved my metrics?
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Under the source content permission, this page provides an editorial summary, key points, and a link to the original article.

Key points and analysis

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Key points

  • AI speeds up coding but DORA metrics remain stagnant; change failure rate even worsens.
  • Effort shifts from coding to specification and review, creating new bottlenecks.
  • Work unit size increases, raising review cognitive load and failure surface.
  • Complement DORA with cycle time variants, SPACE, and DevEx for better insights.

Highlights and analysis are generated automatically and may contain errors. Check the original source.

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