The skill that interviews can most easily measure is the ability to think through small problems quickly, but the ability to solve large, complex problems well over time is what you need in an employee.

Larger companies tend to rely more on brain teasers in interviews, which can introduce noise, but they often use them as a standard part of their hiring process. Bigger companies focus more on measuring innate ability rather than specific coding skills for their codebase, while smaller companies prioritize immediate productivity in specific technologies like Ruby on Rails.

When interviewing candidates, we assess their problem-solving skills and how they think about trade-offs, rather than just their ability to write code.

Engineering interviewing is a field where many common beliefs are misleading; for instance, evaluating past work does not predict job performance as effectively as practical programming assignments.

The traditional use of brain teasers in interviews is becoming less relevant; companies should focus on practical problem-solving skills instead.

Google's difficult interview questions attract candidates who enjoy solving tough problems, which is a strategy worth emulating.

Avoiding bias from credentials during interviews can help identify skilled programmers who may lack traditional qualifications, which is advantageous for startups.

When pre-screening candidates, we evaluate programming productivity, academic computer science skills, debugging abilities, and system design capabilities.

It's better to work with someone on a quick project before hiring them, as this gives you a better sense of their capabilities than a traditional interview.