[agallant]

I'm a huge fan of lifelong learning, and overall agree with this post. But, from a hiring perspective, it is missing a few important details:

1. Sometimes you have things that need to be achieved in a time-sensitive fashion, i.e. the time to ramp up may be problematic, and "taking a chance" may have real business ramifications.

2. Even if you don't have anything urgent, naturally there should be some discount factor for future utility (due to intrinsic uncertainty, etc.) - it's still positive, but remember "I'll gladly pay you Tuesday for a hamburger today."

3. Learning is not a clean linear process, and is also hard to really suss out in a few interviews - I still absolutely look for it in people I hire, but it's pretty easy to claim you take a few MOOCs and harder to know if you really engage with new ideas on a regular basis.

Again, I still very much agree with the spirit and substance of the post, but hiring is complicated, and as with most complicated things there are multiple considerations to balance.

[autokad]

also, how would you measure someone's slope? would it even be fair to evaluate them by it?

[ashtonkem]

Even if it was linear, you can’t tell the slope of a line from one measurement, and an interview is one measurement. You’d need two interviews separated by some time, which is obviously impractical.

[throwaway287391]

And even if you could, once interviewees know you're doing this, they could easily game it by intentionally bombing the first interview.

[yellowapple]

> You’d need two interviews separated by some time, which is obviously impractical.

My experience with multi-round interviews being stretched across multiple weeks strongly suggests otherwise.

Further, this is kind of the whole point of a probationary period, no?

[ashtonkem]

My feeling is that multi-round interviews and probationary periods are less about getting a more precise view of a workers growth, and more about being extremely risk adverse in hiring.

[rckrd]

Agreed. It wouldn't be so hard if things were linear.

All models are wrong, but some are useful.