Curiously, senior developers embrace AI coding tools more than juniors

A new survey by cloud services platform Fastly reveals that senior developers are embracing AI coding tools more enthusiastically than their junior counterparts, with over 70% reporting that AI makes programming significantly more enjoyable. The findings challenge assumptions about generational tech adoption, showing experienced programmers are leading the charge in AI-assisted development while maintaining critical oversight of machine-generated code.

What you should know: Senior developers with over ten years of experience are using AI tools strategically to enhance productivity while leveraging their expertise to catch potential flaws.

• About one-third of senior developers now produce more than half their finished work through AI code generation, compared to just 13% of developers with less than two years of experience.
• Senior engineers spend extra effort reviewing machine-created code for errors, demonstrating a calculated approach rather than blind reliance on automation.
• Fewer than half of junior developers felt AI coding sped up their work, with many preferring to hand-craft solutions themselves.

Why this matters: The survey suggests AI coding tools are recreating the satisfaction that originally drew many programmers to the field, particularly for experienced developers juggling multiple responsibilities beyond pure coding.

• Austin Spires, senior director of developer engagement at Fastly, explained that senior engineers “don’t write code all day” and are often expected to handle testing, architecture, and mentoring tasks.
• Using AI to prototype quickly can recreate the “fun dopamine hit” that attracted many developers to programming initially.
• This pattern allows experienced developers to focus on higher-level responsibilities while maintaining the creative aspects of development.

The environmental divide: Senior and junior developers show stark differences in awareness about the energy costs of their code.

• 80% of older coders said they considered the energy impact of their work, compared to barely half of younger developers.
• Nearly one in ten junior developers admitted they had no idea how much power their code consumed.
• The lack of transparency around AI tools’ carbon footprints compounds this knowledge gap.

What they’re saying: Industry experts see this generational difference as reflecting varying levels of experience with broader system impacts.

• “There’s not a lot of incentive for AI coding tools to disclose what the carbon footprint of these tools are,” Spires noted.
• “More senior engineers understand the second and third effects of their code in how it relates to users and how it relates to their community. And I think it’s just a matter of time before junior developers start to understand those ramifications a little bit further.”
• Spires described junior developers’ preference for handwritten code as “heartening,” suggesting less experienced programmers still value traditional development craftsmanship.

The big picture: The research indicates that senior engineers are setting the tone for AI adoption in software development, blending efficiency gains with cautious oversight as the industry navigates this technological shift.