From Execution to Cognition: Rethinking Hiring in the AI Era

A company asked candidates to go through this hiring process:

• 45 min screening

• 60 min role play

• 90 min competency interview

• 2–3 hour case study

• 60 min hiring manager interview

I’m curious, would you do it?

When I look at this, it requires someone with a lot of time and a high tolerance for friction.

As a recruiter, this tells me more about the company than it tells me about the candidate. It screams: “We have been burned before and we will do everything in our power to avoid that position again.” It also says decision confidence is lacking.

My qualm with this hiring process isn’t any single step but the stacking, because more steps don’t automatically reveal the right candidate: different interviewers optimize for different traits, so the signal breaks down.

• Candidates start performing for the process rather than the job

• Fatigue and confirmation bias weaken later-stage signals

• Teams end up picking the safe, average option instead of the standout candidate

And what you end up selecting is a candidate who performed really well for the process, not the job.

What such companies are lacking is cognitive clarity. They need to ask themselves questions like:

• What kind of thinking does this role require?

• What judgment patterns matter most?

• Where do we need depth versus breadth?

• What does “fit” actually mean here?

When those answers are articulated, hiring is simplified.

The legacy hiring model has always been lacking, and more so now as we transition into the AI era. You see, we optimized hiring for execution, but now we need to optimize for cognition.

So the disconnect between having a large pool of qualified candidates and companies actually finding the right fit is only going to grow.