- Senior developers rely on artificial intelligence coding tools, while double verification machine failures, the report states
- More than 70% say that AI makes coding significantly more pleasant
- Junior programmers prefer hand written code despite the pressure to adopt automation
Software development has always reflected generational changes, from hand -written scripts to cloud platforms, with the last movement now to AI tools that generate code.
A recent survey conducted by the cloud services platform quickly suggests that the division between younger and older developers is not as clear as some could assume.
Instead of resisting automation, many senior engineers seem to be adopting in a way that highlights both their experience and their priorities.
Major encoders take the front
The survey reveals a slight majority of those with more than ten years in the field report that AIH assisted coding helps them deliver software more quickly.
At the same time, they recognize additional effort by reviewing for faults created by machine.
This pattern points less to excessive and more to a calculated use of inline automation with its broader responsibilities.
One of the most surprising findings of the study is that approximately one third of the upper developers are producing more than half of their work finished through the generation of AI code.
On the contrary, only 13% of those with less than two years of experience reported a similar level of use.
Austin Spires, senior director of developer participation in Fastly, explained that senior engineers “do not write code all day” and, on the other hand, are expected to juggle with tests, architecture and tutoring tasks.
He suggested to use AI for prototypes quickly, can recreate the “fun dopamine success” that led many developers to programming first.
This does not necessarily mean that younger encoders are left behind; Less than half of them felt that the coding of AI accelerated their work, and many preferred hand -hand solutions.
Needles described this as “encouraging”, suggesting that less experienced programmers still value traditional development crafts.
In all age groups, more than 70% of respondents said the AI systems made their work more pleasant, and more than 30% called for the “significant” effect.
However, the study also revealed differences in how generations address the environmental impact of the software.
80% of the major encoders said they considered the energy costs of their work, compared to just half of the younger developers.
Almost one in ten admitted that they had no idea how much power their code consumed.
“There are not many incentives for AI coding tools to reveal what the carbon footprint of these tools are,” added Spires.
“More senior engineers understand the second and third effects of their code on how it relates to users and how it relates to their community. And I think it is only a matter of time before Junior developers begin to understand those ramifications a little more.”
While developers may be testing prototypes in high -end work stations or even laptops for programming, the greatest consequences of generalized automation are still uncertain.
For now, research suggests that senior engineers are establishing the tone, combining efficiency with caution while navigating a evolution -coding culture.
