Given current AI trend, live coding sessions are transforming a lot as well. I can see more companies leaning towards virtual sessions with "prepare a blank project with your favorite IDE, share your screen and let's go". This means, that the companies acknowledge that the AI is a little trick a candidate can utilize to make a better impression.
On the other hand, this is just interviewees adapting to a relatively high standard that the industry did set. It was discussed a ton of times, how other jobs don't require a person to present the fitness in such a rigorous manner. When companies treat every other candidate as an impostor.
Not only a candidate should be a jack of many trades but also be humble once they get put into a job that may not necessarily require those algo and system design skills right away or in a year's time.
We all know that. But I'm very curious to learn how it all started, who set the "Olympic team fit" standard.
Either you enforce a minimal level of competency upfront with academic rigor, industry-standard exams, and similar measures, or you push the entire responsibility of vetting prospective applicants downstream to the employer—which is exactly where we are right now.
So how do we go about fixing it? For starters, I think we should bring back the Software Engineering PE Exam.
https://ncees.org/ncees-discontinuing-pe-software-engineerin...
EDIT: Just to respond to this: "It was discussed a ton of times, how other jobs don't require a person to present the fitness in such a rigorous manner"
Other occupations 100% DO have high standards - it's just that it's paid up-front.
Want to become a lawyer? - You've got to pass the LSAT, get into law school, and pass the bar.
Want to become a doctor? - You've got to pass the MCAT, get into medical school, and do residency.
Want to become a pilot? - You've got to get your PPL, pass your check ride, do your IFR, multi-engine, commercial rating, ATP.
etc. etc.
Microsoft did brain teasers like "How many ping pong balls fit on a bus?" questions. Then Google copied that to start. Google later realized that performance on these questions didn't predict performance on the job and developed a more data-driven approach that you see today (leetcode style) that other companies copy today.
I'm in the camp that interviewing loops all have tradeoffs, but if you're a smaller company you can't afford to copy how big tech giants interview candidates. Their funnels are much larger, and they can afford to skip on potentially quality candidates.