Imagine asking a Michelin-star chef to go work the grill at McDonald’s. The food still feeds people, but the art — the craft — feels erased. All those years of blood, sweat, and tears perfecting technique suddenly look wasted when the same job can be done by someone with twenty minutes of training.
That’s how some of your most senior engineers feel when AI starts writing code. For them, coding has never been just typing — it’s been craftsmanship, mastery, and solving problems at a level only a few peers could truly appreciate.
When these engineers push back on AI, it’s not usually fear of losing a job. It’s pride.
They’ve spent decades polishing every line of code — for embedded systems, medical devices, safety-critical software, or game engines where efficiency meant survival. To them, code isn’t just instructions; it’s an art form where elegance and optimization matter. That’s why, in surveys over the past year, software developers rank among the least worried professions about AI replacing them (Stack Overflow survey). They don’t see AI as a job threat. What they resist is the erosion of craftsmanship when thousands of lines of unpolished code start flooding their world.
Signs for Leaders to Watch
- What they say: “AI can’t possibly write production-grade code.”
- Where they’ve worked: Embedded systems, safety-critical industries, real-time comms, video games.
- How they operate: Meticulously clean desk, obsessively organized repos, perfectionism in reviews.
- Their focus: They zero in on inefficiencies or sloppiness in AI output before anything else.
Questions Leaders Can Ask
- “When you see AI-generated code, what’s the first thing you notice?”
- “What do you enjoy most about writing code?”
- “If AI could write code as optimized as yours, what would you do with the extra time?”
These questions aren’t tricks. They reveal whether pride in craft is driving the resistance — and they open the door to a more constructive conversation.
The Leadership Resolution
So what should leaders do with this kind of resistance? Don’t sideline these people — enlist them.
If someone cares enough to complain about the quality of AI-generated code, that’s not a liability. It’s an asset. Give them ownership in shaping how AI is used in your org.
That might mean:
- Defining the standards AI code should meet before hitting review.
- Testing and tuning AI-assisted workflows so they align with the team’s quality bar.
- Acting as guardians of craftsmanship at scale, ensuring the art isn’t lost as productivity soars.
For example, instead of letting frustration over “junk AI code” fester, a leader might bring that same engineer into a working group to design the AI integration process. Their attention to detail can drive solutions — like using AI to pre-check quality before human review — that make the whole team stronger.
Closing Thought
If you’re leading a team, take a moment to look around.
Who are the people most focused on craftsmanship? Who worries about quality more than speed? Who gets prickly when AI-generated code shows up in a pull request?
Those aren’t blockers. They’re your future quality leaders. Start the conversation with them, give them a role in shaping how AI becomes part of your process, and you’ll keep the craft alive while moving your organization forward.
It’s not about turning chefs into line cooks — it’s about letting them design the kitchen where great meals keep coming out.