Stop Forcing AI on Developers

Mandating AI usage doesn’t make your company innovative. It makes it anxious.

I still see CEOs and leaders announce that they’re requiring AI adoption: tying usage to performance reviews, “embrace AI or move on,” even saying that people might be fired if they don’t.

I get why they do it. No one wants to be the leader who moves too slowly while a competitor sprints ahead. But forcing people to use a tool rarely creates real transformation. In engineering, it usually slows things down.

You can mandate compliance. You cannot mandate cognition.

Developers will try the tool. They’re curious. But if it gets a detail wrong, misses something subtle, or produces an answer that looks fine until you look closer, trust disappears quickly. Once that trust is gone, what follows isn’t real adoption. It’s theater.

Developers use the tool because the dashboard expects it.
Managers talk about usage because they’re supposed to.
Tool teams polish demos instead of fixing things that matter.

Much of this pressure comes from the stories leaders tell themselves about AI’s future. Often it’s a flashy demo or the tale of an engineer who “one-shotted” a feature. What gets lost is that the engineer was one of the best on the team, and it worked only because they framed the problem expertly. The AI didn’t replace their skill; it borrowed it.

LLMs are impressive, but they’re not senior engineers. They don’t understand how your architecture fits together or why certain constraints exist. They don’t see tradeoffs or push back when your reasoning is off. And when they’re wrong, it rarely looks wrong at first, which makes mistakes easy to miss.

We can build extraordinary bionics, not robots to replace developers. AI is at its best when it clears away the work engineers shouldn’t be doing in the first place: the log digging, context chasing, tool stitching, and repetitive patterns that drain energy and break flow. And you never need to force developers to use something that removes friction. They do that naturally.

So what’s the better path? Earn the adoption. Show that the tool helps, not in a rehearsed demo but in the middle of delivery. If it consistently helps teams ship, you don’t need a usage target. Developers will reach for it automatically.

Leadership can do something even more important: inspire teams. So instead of saying “use the AI tool,” present challenges like:

- Can we eliminate holiday code freeze?
- Could the codebase onboard new engineers itself?
- Could incidents detect and resolve themselves before oncall even wakes up?
- Can we modernize legacy safely without slowing the roadmap?

Challenges like these spark creativity and ambition. They invite people to combine human judgment with AI capability in ways that actually matter. And when AI helps teams accomplish something that used to feel impossible, adoption follows naturally.

The future of engineering won’t be forced. It will be earned.

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