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Does tenure change how developers benefit from AI tools?

Laura Tacho

CTO

Tenure has long been a predictor of productivity. Developers who know the product, codebase, and organizational processes typically ship more code than recent hires. But with AI tools now deeply embedded into engineering workflows, does that still hold true?

To investigate, I analyzed data from 16,301 developers across enterprises with 500+ engineers. Over 80% of these companies are large multinationals, spanning both tech and non-tech industries.

Weekly PR Throughput by hiring date and AI adoption level

What the data shows

For non-AI users, the traditional pattern holds: developers with longer tenure (hired before 2024) ship more pull requests per week than recent hires.

But once AI enters the picture, the story changes:

  • Light AI use: Recent hires with only occasional AI use actually ship fewer changes than their tenured peers, suggesting that dabbling with AI without deep organizational context can be a drag on throughput.
  • Moderate AI use: Throughput looks similar to non-AI users, showing that modest adoption does little to change outcomes.
  • Heavy AI use: Developers who use AI daily, regardless of tenure, have the highest throughput by far. Even recent hires with daily AI use outpace tenured developers who don’t use AI.

What the data doesn’t show

PR throughput is just one dimension. As the AI Measurement Framework and DX Core 4 emphasize, productivity must be evaluated holistically: speed, quality, developer experience, and innovation time.

This dataset doesn’t tell us:

  • How quality changes with AI (are faster PRs leading to higher change failure rates?)
  • Whether developers are spending less time fixing bugs
  • How developer experience is being impacted

Takeaways for leaders

  • Tenure + AI is a multiplier. Developers with deep product knowledge get the most out of AI, but even without tenure, AI helps new hires ramp faster.
  • Heavy adoption drives real gains. Occasional AI use doesn’t move the needle. Teams see the impact when AI is part of daily workflows.
  • Look beyond throughput. Measuring only speed can mislead. To see the full impact of AI, leaders must also track quality, experience, and innovation.

AI doesn’t erase the value of tenure, but it does accelerate the pace at which new hires can catch up.

 

 

 

 

 

 

Published
August 20, 2025