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AI Coding Assistants Can Help Prevent Burnout
Looking back on my two decades in software development, I can’t help but think about those long nights in corporate offices, where the fluorescent lights buzzed overhead and the coffee machine ran past 8pm.
The days where error messages poured like waterfalls and solutions seemed to exist in some parallel universe we couldn’t quite access.
Those days are long behind me now. As a CTO in the startup space, my relationship with code has evolved dramatically. But the memories (and some would say, traumas) of those corporate all-nighters still live on.
And it got me thinking. What if we had AI coding assistants back then? Would those nights have been different?
The thing is, while I no longer pull those marathon debugging sessions, I’ve found myself becoming an unexpected advocate for AI coding tools in my current role.
Not because they’re revolutionary (though some would argue otherwise), but because they’re surprisingly effective at preventing the kind of burnout I witnessed and experienced throughout my corporate career.
The Real Face of Burnout
Most people think burnout comes from coding from dawn till dusk while sitting in a 3x3 cubicle. But I personally wouldn’t call that a ‘burnout’. That’s just a rough day at the office.
Real burnout? That’s a bit more subtle and it takes time to build up.
In my twenty years of coding and leading development teams, I’ve seen burnout triggered by:
- The maintenance of legacy codebases that no one understands
- The mental drain of building complex logic under crazy deadlines
- The endless repetition of writing the same utility functions over and over
- The constant context-switching between different projects and priorities
If you do that long enough, it’s going to catch up to you.
These days, as a CTO, I’m particularly interested in tools that can help my team avoid these pitfalls. And surprisingly, AI has become one of them.
