Senior developers lean on AI coding tools while double-checking machine flaws, report claimsMore than 70% say AI makes coding significantly more enjoyableJunior programmers prefer handwritten code despite pressure to embrace automation<\/p>\n
Software development has always reflected generational shifts, from handwritten scripts to cloud platforms, with the latest movement now to AI tools<\/a> generating code.<\/p>\n A recent survey by cloud services platform Fastly<\/a> suggests the divide between younger and older developers is not as clear as some might assume.<\/p>\n <\/p>\n Instead of resisting automation, many senior engineers appear to be embracing it in ways that highlight both their experience and their priorities.<\/p>\n You may like<\/p>\n Older coders take the lead<\/p>\n The poll reveals a slight majority of those with more than ten years in the field report that AI-assisted coding helps them deliver software more quickly.<\/p>\n At the same time, they acknowledge spending extra effort reviewing for machine-created flaws.<\/p>\n This pattern points less to overreliance and more to a calculated use of automation in line with their broader responsibilities.<\/p>\n One of the study\u2019s more striking findings is that about a third of senior developers are producing more than half of their finished work through AI code generation.<\/p>\n By contrast, only 13% of those with less than two years\u2019 experience reported a similar level of use.<\/p>\n Austin Spires, senior director of developer engagement at Fastly, explained senior engineers \u201cdon\u2019t write code all day,\u201d and are instead often expected to juggle testing, architecture, and mentoring tasks.<\/p>\n Using AI to prototype quickly, he suggested, can recreate the \u201cfun dopamine hit\u201d that drew many developers to programming in the first place.<\/p>\n This does not necessarily mean that younger coders are being left behind; fewer than half of them felt that AI coding sped up their work, with many preferring to hand-craft solutions themselves.<\/p>\n Spires described this as \u201cheartening,\u201d suggesting that less experienced programmers still value the craftsmanship of traditional development.<\/p>\n Across all age groups, more than 70% of respondents said AI systems made their jobs more enjoyable, with over 30% calling the effect \u201csignificant.\u201d<\/p>\n Yet the study also revealed differences in how generations approach the environmental impact of software.<\/p>\n 80% of older coders said they considered the energy costs of their work, compared to barely half of younger developers.<\/p>\n Nearly one in ten admitted they had no idea how much power their code consumed.<\/p>\n “There’s not a lot of incentive for AI coding tools to disclose what the carbon footprint of these tools are,” Spires added.<\/p>\n “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.”<\/p>\n While developers may be testing prototypes on high-end workstations<\/a> or even on laptops for programming<\/a>, the larger consequences of widespread automation remain uncertain.<\/p>\n For now, the research suggests that senior engineers are setting the tone, blending efficiency with caution as they navigate an evolving coding culture.<\/p>\n