But yeah that's the game you have to play now if you want the top $$$ at one of the SMEGMA companies.

I wrote (for example) my 2D game engine from scratch (3rd party libs excluded)

https://github.com/ensisoft/detonator

but would not be able to pass a LC type interview that requires multiple LC hard solutions and a couple of backflips on top. But that's fine, I've accepted that.

I actually have the feeling it’s not as hardcore as it used to be on average. E.g. OpenAI doesn’t have a straight up LC interview even though they probably are the most sought after company. Google and MS and others still do it, but it feel like it has less weight in the final feedback than it did before. Most en-vogue startup have also ditched it for real world coding excercices.

Probably due to the fact that LC has been thoroughly gamed and is even less a useful signal than it was before.

Of course some still do, like Anthropic were you have to have a perfect score to 4 leetcode questions, automatically judged with no human contact, the worst kind of interview.

>Of course some still do, like Anthropic were you have to have a perfect score to 4 leetcode questions, automatically judged with no human contact, the worst kind of interview.

Should be illegal honestly.

I can't imagine this kind of entitlement. If you don't want to work for them, don't study leetcode. If you want to work for them (and get paid tons of money), study leetcode. This isn't a difficult aristotelian ethics/morals question.

That wouldn't be hard to do. Given the disparate impact standard, everything is biased against a protected class.

Thankfully not everything from SV culture gets adoption.

The faangs jump and then the rest of the industry does some dogshit imitation of their process

It was humbling having to explain to fellow adult humans that when your test question is based on an algorithm solving a real business problem that we work on every day, a random person is not going to implement a solution in one hour as well as we can.

I’ve seen how the faangs interview process accounts for those types of bias and mental blindness and are actually effective, but their solutions require time and/or money so everywhere I’ve been implements the first 80% that’s cheap and then skips on the rest that makes it work

Any way to reach out? :)

I think it boils down to companies not wanting to burn money and time on training, and trying to come up with all sorts of optimized (but ultimately contrived) interview processes. Now both parties are screwed.

>It was humbling having to explain to fellow adult humans that when your test question is based on an algorithm solving a real business problem that we work on every day, a random person is not going to implement a solution in one hour as well as we can.

Tell me about it! Who were you explaining this to?

Ten years ago it was more based on Cracking the Coding Interview.

So i'd guess what you're referring to is even older than that.

Apart from those companies where social capital counts for more ...

Based on my own experiences, that was true 25 years ago. 20 years ago, coding puzzles were now a standard part of interviewing, but it was pretty lightweight. 5 years ago (covid!) everything was leet-code to get to the interview stage.

Ah, but, the road to becoming good at Leetcode/100m sprint is:

>a slow arduous never ending jog with multiple detours and stops along the way

Hence Leetcode is a reasonably good test for the job. If it didn't actually work, it would've been discarded by companies long ago.

Barring a few core library teams, companies don't really care if you're any good at algorithms. They care if you can learn something well enough to become world-class competitive. If you can show that you can become excellent at one thing, there's a good chance you can become excellent at another thing.

That's basically also the reason that many Law and Med programs don't care what your major in undergrad was, just that you had a very high GPA in whatever you studied. A decent number of Music majors become MDs, for example.

That's literally what CS teaches you too. Which is what "leetcode" questions are: fundamental CS problems that you'd learn about in a computer science curriculum.

It's called "reducing" one problem to another. We had an entire semester's mandatory class spend a lot of time on reducing problems. Like figuring out how you can solve a new type of question/problem with an algorithm or two that you already know from before.

Like showing that "this is just bin packing". And there are algorithms for that, which "suck" in the CS kind of sense but there are real world algorithms that are "good enough" to be usable to get shit done.

Or showing that something "doesn't work, period" by showing that it can be reduced to the halting problem (assuming that nobody has solved that yet - oh and good luck btw. if you want to try ;) )

Then comes the ability/memorization to actually code it, e.g. if I knew it needs coding red-black tree I wouldn't even start.

https://www.acmicpc.net/problem/33797

Try with an LLM too :)

Architecture is not part of leetcode.

Math is like that as well though. It's about learning all the prior axioms, laws, knowing allowed simplifications, and so on.

or that writing a new book is the same.

I.e. it's not about that. Like sure it helps to have a base set of shared language, knowledge, and symbols, but math is so much more than just that.

In all seriousness, the intersection between correctness and project delivery is where engineering sits. Solutions must be good enough, correct enough, and cheap enough to fit the use case, but ideally no more than that.

Memorizing the Top 100 list from Leetcode only works for a few companies (notably and perplexingly, Meta) but doesn't for the vast majority.

Also, just solving the problem isn't enough to perform well on the interview. Getting the optimal solution is just the table stakes. There's communication, tradeoffs between alternative solutions, coding style, follow-up questions, opportunities to show your prowrss etc.

Memorizing problems is wholly not the point of Leetcode grinding at all.

In terms of memorizing "patterns", in mathematics and computer science all new discovery is just a recombination of what was already known. There's virtually no information coming from outside the system like in, say, biology or physics. The whole field is just memorized patterns being recombined in different ways to solve different problems.

I guess it's a matter of opinion but my point is, this is probably the right metric. Arguably, the kind of people who shut up and play along with these stupid games because that's where the money is make better team players in large for-profit organizations than those who take a principled stance against ever touching Leetcode because their efforts wouldn't contribute anything to the art.

But yeah, people used to ask that level of unrelated questions to programmers, and they were happy with the results. "Why is a manhole cover round" etc. LeetCode style questions do produce better results than those, so that is why they use them.

People complain, rightly so in some cases, that their "interview" is really doing some (unpaid) work for the company

This that I've singled out above is a very confident statement, considering that inertia in large companies is a byword at this point. Further, "work" could conceivably mean many things in this context, from "per se narrows our massive applicant pool" to "selects for factor X," X being clear only to certain management in certain sectors. Regardless, I agree with those who find it obvious that LC does not ensure a job fit for almost any real-world job.

I see it differently. I wouldn't say it's reasonably good, I'd say it's a terrible metric that's very tenuously correlated with on the job success, but most of the other metrics for evaluating fresh grads are even worse. In the land of the blind the one eyed man is king.

> If you can show that you can become excellent at one thing, there's a good chance you can become excellent at another thing.

Eh. As someone who did tech and then medicine, a lot great doctors would make terrible software engineers and vice versa. Some things, like work ethic and organization, are going to increase your odds of success at nearly any task, but there's plenty other skills that are not nearly as transferable. For example, being good at memorizing long lists of obscure facts is a great skill for a doctor, not so much for a software engineer. Strong spatial reasoning is helpful for a software developer specializing in algorithms, but largely useless for, say, an oncologist.

This is an appeal to tradition and a form of survivorship bias. Many successful companies have ditched LeetCode and have found other ways to effectively hire.

> If you can show that you can become excellent at one thing, there's a good chance you can become excellent at another thing.

My company uses LeetCode. All I want is sane interfaces and good documentation. It is far more likely to get something clever, broken and poorly documented than something "excellent", so something is missing for this correlation.

You're assuming that something else works better. Imagine if we were in a world where all interviewing techniques had a ton of false positives and negatives without a clear best choice. Do you expect that companies would just give up, and not hire at all, or would they pick based on other factors (e.g. minimizing the amount of effort needed on the company side to do the interviews)? Assuming you accept the premise that companies would still be trying to hire in that situation, how can you tell the difference between the world we're in now and that (maybe not-so) hypothetical one?

If it didn't work, these companies wouldn't be able to function at all.

It must be the case that it works better than running a RNG on everyone who applied.

Does it mean some genius software engineer who wrote a fundamental part of the Linux kernel but never learned about Minimum Spanning Trees got filtered out? Probably. But it's okay. That guy would've been a pain in the ass anyway.

When I look at the messy Android code, Fuchsia's commercial failure, Dart being almost killed by politics, Go's marvellous design, WinUI/UWP catastrophical failure, how C++/CX got replaced with C++/WinRT, ongoing issues with macOS Tahoe,....

I am glad that apparently I am not good enough for such projects.

The fact is that they fail is not evidence that leetcode interviews fails to select for high quality engineers.

Startups that wanted to emulate FAANGs then cargo-culted them, particularly if they were also founded by CS students or ex-FAANG (which describes a lot of them). Very, very few of these actually try any other way of hiring and compare them.

Being able to study hard and learn something well is certainly a great skill to have, but leetcode is a really poor one to choose. It's not a skill that you can acquire on the job, so it rules out anyone who doesn't have time to spend months studying something in their own time that's inherently not very useful. If they chose to test skills that are hard and take effort to learn, but are also relevant to the job, then they can also find people who are good at learning on the job, which is what they are actually looking for.

That makes the assumption that company hiring practices are evidence based.

How many companies continue to use pseudo-science Myers Briggs style tests?

In my experience, it's totally not true.

Many college students of my generation are pretty good with LC hards these days purely due to FOMO-induced obsessive practice, which doesn't translate to a practical understanding of the job, (or any other parts of CS like OS/networks/languages/automata either).

I will give you an exercise, pick an LC hard problem and it's very likely an experienced engineer who has only done "real work" will not know the "trick" required to solve the problem. (Unless it's something common like BFS or backtracking).

I say this as someone with "knight" badge on leetcode, whatever that means, lest you think it's a sour grapes fallacy.

I've always explained it as demonstrating your ping pong skills to get on the basketball team.

Microsoft, Google, Meta, Amazon, I'm guessing... but, what are the other two?

Its a learnable skill and better to pick it up now. Personally I've solved Leetcode style problems in interviews which I hadnt seen before and some of them were dynamic programming problems.

These days its a highly learnable skill since GPT can solve many of the problems, while also coming up with very good explanations of the solution. Better to pick it up than not.

And some people might say well, you should know that anyways. The problem for me is, and I'm not speaking for every company of course, you never really use a lot of this stuff in most run of the mill jobs. So of course you forget it, then have to study again pre interview.

Problem solving is the best way to think of it, but it's awkward for me(and probably others) to spend minutes thinking, feeling pressured as someone just stares at you. And that's where memorizing the hows of typical problems helps.

That said, I just stopped doing them altogether. I'd passed a few doing the 'memorizing' described above, only to start and realize it wasn't at all irrelevant to the work we were actually doing. In that way I guess it's a bit of a two way filter now.

Even if you are an exception either you are writing the library meaning you write that algorithm once for the hundreds of other users, or the algorithm was written once (long ago) and you are just spending months with a profiler trying to squeeze out a few more CPU cycles of optimization.

There are more algorithms than anyone can memorize that are not in your library, but either it is good enough to use a similar one that already is your library, or you will build it once and once again it works so you never go back to it.

Which is to say memorizing how to implement an algorithm is a negative: it means you don't know how to write/use generic reusable code. This lack is costing your company hundreds of thousands of dollars.

I actually love LC and have been doing a problem a week for years. Basically I give myself 30 minutes and see what I can do. It’s my equivalent to the Sunday crossword. After awhile the signals and patterns became obvious, to me anyway.

I also love puzzlerush at chess.com. In chess puzzles there are patterns and themes. I can easily solve a 1600 rated problem in under 3 seconds for a chess position I’ve never seen before not because I solve the position by searching some move tree in my mind, I just recognize and apply the pattern. (It also makes it easier to trick the player when rushing but even the tricks have patterns :)

That said, in our group we will definitely have one person ask the candidate a LC style question. It will probably be me asking and I usually just make it up on the spot based on the resume. I think it’s more fun when neither one of us know the answer. Algorithm development, especially on graphs, is a critical part of the job so it’s important to demonstrate competency there.

Software engineering is a hugely diverse field now. Saying you’re a programmer is kinda like saying you’re an artist. It does give some information but you still don’t really know what skill set that person uses day to day.

I'm wondering how software devs explain this to themselves. What they train for vs what they actually do at their jobs differ more and more with time. And this constant cycle of forgetting and re-learning sounds like a nightmare. Perhaps people burn out not because of their jobs but the system they ended up in.

I don't think most LC problems require you to do that. Actually most of them I've seen only require basic concepts taught in Introduction to Algorithms like shortest path, dynamic programming, binary search, etc. I think the only reason LC problems stress people out is time limit.

I've never seen a leetcode problem that requires you to know how to hand code an ever so slightly exotic algorithm / data structure like Fibonacci heap or Strassen matrix multiplication. The benefit of these "fastest algos" is too small to be measured by LC's automatic system anyway. Has that changed?

My personal issue with LC is that it has a very narrow view of what "fast" programs look like, like most competitive programming problem sets. In real world fast programs are fast usually because we distribute the workload across machines, across GPU and CPU, have cache-friendly memory alignment or sometimes just design clever UI tricks that make slow parts less noticeable.

I've been at this for 30+ years now, I've built systems that handle millions of users and have a pretty good grasp at a lot of problem domains. I spent about a decade in aerospace/elearning and had to pick up new stuff and reason with it all the time. My issue is specifically with automated leetcode pre-interview screening, as well as the gamified sites themselves.

Of course you may need to pass an interview LeetCode test, in which case you may want to hold your nose and put in the grind to get good at them, but IMO it's really not saying anything good about the kind of company that thinks this is a good candidate filter (especially for more experienced ones), since you'd have to be stupid not to use AI if actually tasked with needing to solve something like this on the job.

And when someone uses "leet" when talking about computing, I know that they aren't "elite" at all and it's generally a red flag for me.

The problem is that it is too amenable to prep

You can move your score like 2stddev with practice, which makes the test almost useless in many cases

On good tests, your score doesn't change much with practice, so the system is less vulnerable to Goodharting and people don't waste/spend a bunch of time gaming it

This framing of the problem is deeply troubling to me. A good test is one that evaluates candidates on the tasks that they will do at the workplace and preferably connects those tasks to positive business outcomes.

If a candidate's performance improves with practice, then so what? The only thing we should care about is that the interview performance reflects well on how the candidate will do within the company.

Skill is not a univariate quantity that doesn't change with time. Also it's susceptible to other confounding variables which negatively impact performance. It doesn't matter if you hire the smartest devs. If the social environment and quality of management is poor, then the work performance will be poor as well.

Systematizing this is not feasible. The next best thing (in terms of predictive power for future job success) is direct IQ tests, which are illegal in the US. Next best thing after that are IQ proxies like coding puzzle ability.

> If a candidate's performance improves with practice, then so what?

It means the test isn't measuring anything useful. The extremely broad spectrum skills that benefit a software/eng role aren't something you can "practice".

> The only thing we should care about is that the interview performance reflects well on how the candidate will do within the company.

Agreed, which any Goodhartable test will never do.

If you’re hiring software engineers by asking them questions that are best answered by AI, you’re living in the past.

You would need "photographic" memory

Most people memorize and cargo cult practices with no deeper understanding of what they are doing.

Firstly these questions you get like 30 mins to do, which is small compared to the time variance introduced by knowing or not knowing the required algorithm. If you know it you'll be done in like 10 mins with a perfect answer. Whereas if you don't know you could easily spend 30 mins figuring it out and fail. So while on average people passed by LC may be good engineers, in any one scenario it's likely you reject a good engineer because the variance is large. And then it's easy to see why people get upset, because yeah it feels dodgy to be rejected when you happen to not know some obscure algorithm off the top of your head. The process could be fairer.

Secondly, as many say, the actual job is rarely this technical stuff under such time pressure. Knowing algorithms or not means basically nothing when the job is like debugging CI errors for half your day.

The issue is that leetcode is something you end up with after discovery + scientific method + time, but there's no space in the interview process for any of that.

Your mind slides off leetcode problems because it reverses the actual on-the-job process and loses any context that'd give you a handle on the issue.

This was the demo/take-home (for https://monumental.co): https://github.com/rublev/monumental

Sorry about the job interview. That sucks.

I'm not saying that using AI for take-home assignments is bad/unethical overall, but you need to be honest about it. If he was lying to them about not using any AI assistance to write all those emojis and folder structure map in the repo, then the CTO had a good nose and rightfully caught him.

No emojis and any effort to be comprehensive? Everyone complains "what is this wall of text", or "this is industry not grad school so cut it out with the fancy stuff" or "no one spends that much time on anything and it must be AI generated". (Frequently just a way of saying that you hate to read, and naively believe that even irreducibly complex stuff is actually simple).

Stuff that's got emojis, a friendly casual tone and isn't information dense? Well that's very chatty and cute, it also has to be AI and can't be valuable.

Since you can't win with docs, the best approach is to produce high quality diagrams that are simultaneously useful for a wide audience from novice to expert. The only problem is that even producing high quality diagrams at a ratio of 1 diagram per 1k lines of code is still very time consuming to produce if you're putting lots of thought into it, double so if you're fighting the diagramming tools, or if you want something that's easy for multiple stakeholders with potentially very different job descriptions to take in. Everyone will call it inadequate, ask why it took so long, and ask for the missing docs that they will hate anyway!

On the bright side, LLMs are pretty great at generating mermaid, either from code, or natural language descriptions of data-flows. Diagrams-as-code without needing a whole application UI or one of a limited number of your orgs lucid-chart licenses is making "Don't like it? Submit a PR" a pretty small ask. Skin in the game helps to curbs endless bike-shedding criticism

> Stuff that's got emojis, a friendly casual tone and isn't information dense? Well that's very chatty and cute, it also has to be AI and can't be valuable.

As a counterpoint, I can confidently say that I've never once had anyone give any feedback to me on the presence or absence of emojis in code I've written, whether for an interview, work, or personal projects, and I've never had anyone accuse my documentation of being AI generated or gotten feedback in an interview that my code didn't have enough documentation. There's a pretty wide spectrum between "indistinguishable from what I get when I give an LLM the same assignment as my interviewee" and "lacking any sort of human-readable documentation whatsoever".

Should I also be "honest" about tab-completion? Where do you draw the line? Maybe I should be punished for having an internet connection too. Using AI for docker/readme's/simple scaffolding I would have done anyways? Oh the horror!

There was no lying because there was no discussion or mention of AI at all. Had they asked me, I'd have happily told them yes I obviously use AI to help me save time on grunt-work, I've been doing this stuff for like 15 years.

It's an unpaid take-home assignment. You'd have to be smoking crack to think that I would be rawdogging this. Imagine if I had a family or a wife or an existing job? I'd dump them after getting linked their assignment document.

Honestly at this point in the AI winter if you are a guy who has AI-inspired paranoia then I don't want to work for you because you are not "in the know".

Given what you’ve said in your other comments, it seems like you used AI in a way that I wouldn’t have a problem with but just briefly looking through I can see how it would look suspicious.

I'd probably draw it somewhere in the miles-long gap between tab completion and generating code with an LLM. It sounds like that's where the company drew it too.

It's not defensible in any case.

That being said, I think the CTO's "vide coding paranoid" after seeing this repo is 100% justified.

I'm not a math/university educated guy so this was truly "from the ground up" for me despite the math being simple. I was quite proud of that.

>Had you disclosed to then that you used LLMs for coding "basic" features outside the math and whatnot?

No it seems completely immaterial. I'll happily talk about it if asked but it's just another tool in the shed. Great for scaffolding but makes me want to rip my hair out more often than not. If it doesn't one-shot something simple for me it has no use because it's infuriating to use. I didn't get into programming because I liked writing English.

The fucking CTO thought I vibe-coded it and dismissed me. Shout-out to the hiring manager though, he was real.

The job market is brutal right now, and you have my sympathy. I hope you can find a good fit soon.

Doing it slowly over many days is only taking your time and probably wont get you the job anyway since the solution will be a hard to read mess compared to someone who solves it quickly since they are familiar with the domain.

Luckily the hiring manager called me back and levelled with me, nobody kept him in the loop and he felt terrible about it.

Some stupid contrived dumbed down version of this crane demo was used for the live test where I had to build some telemetry crap. Nerves took over, mind blanked.

Here's the take-home assignment requirements btw: https://i.imgur.com/HGL5g8t.png.

Here's the live assignment requirements: [1] https://i.imgur.com/aaiy7QR.png & [2] https://i.imgur.com/aaiy7QR.png.

At this rate I'm probably going to starve to death before I get a job. Should I write a blog post about my last 2 years of experiences? They are comically bad.

This was for monumental.co - found them in the HN who's hiring threads.

I hope you can at least leverage this demo. Maybe remove the identifications of it and shove it into your CV as a "hobby project"? It looks pretty good for that.

Best!

These are the same link

This never happened to me in a job interview before I turned 40. But once I knew I was too old to look the part, and therefore and had to knock it out of the park, mind blank came roaring in. I have so much empathy now for anyone it ever happened to when I was giving the a job interview. Performing under that kind of pressure has nothing to do with actual ability to do the job.

I spent around 40 hours of time and during my second interview, the manager didn't like my answer about how I would design the UI so he quickly wished me luck and ended the call. The first interview went really well.

For a couple of months, I kept asking the recruiter if anyone successfully solved the coding challenge and he said nobody did except me.

Out of respect, I posted the challenge and the solution on my github after waiting one year.

Part 2 is the challenging part; it's mostly a problem solving thing and less of a coding problem: https://github.com/jonnycoder1/merck_coding_challenge

That doesn't look too challenging for anyone who has experience in low-level programming, embedded systems, and reverse engineering. In fact for me it'd be far easier than part 1, as I've done plenty of work similar to the latter, but not the former.

It’s also relative because a $50/hr contract job isn’t exactly attracting low level FAANG engineering talent. But it’s a nice take home challenge for some second rate engineer like myself who will tackle any problem until I figure it out.

discussion / punchline http://conway.rutgers.edu/~ccshan/wiki/blog/posts/WordNumber...

Start of main content: http://conway.rutgers.edu/~ccshan/wiki/blog/posts/WordNumber...

You have also not attempted to hide that, which is interesting.

What is there to clarify? Leetcode-type questions are usually clear, much clearer than in real life projects. You know the exact format of the input, the output, the range for each value, and there are often examples in addition to the question. What is expected is clear: given the provided example inputs, give the provided example outputs, but generalized to cover all cases of the problem statement. The boilerplate is usually provided.

One may argue that it is one of the reasons why leetcode-style questions are unrealistic, they too well specified compared to real life problems that are often incomplete or even wrong and require you to fill-in the gaps. Also, in real life, you may not always get to ask for clarification: "here, implement this", "but what about this part?", "I don't know, and the guy who knows won't be back before the deadline, do your best"

The "coin" example is a simplification, the actual problem statement is likely more complete, but the author of the article probably felt these these details were not relevant to the article, though it would be for someone taking the test.

1. People can be hired to take the test for you - surprise surprise 2. It is akin to deciding if someone can write a novel from reading a single sentence.

> It is akin to deciding if someone can write a novel from reading a single sentence.

For most decent companies, the hiring process involves multiple rounds of these challenges along with system designs. So its like judging writing ability by having candidates actually write and come up with sample plots. Not a bad test.

https://www.reddit.com/r/leetcode/comments/1mu3qjt/breaking_...

There are funded companies set up just to help you get past this stuff.

https://www.reddit.com/r/leetcode/comments/1iz6xcy/cheating_...

Personally I feel software development has become more or less like assembly line work. If I was starting out today I would seriously consider other options.

The worst ones i've had though had extra problems though:

one i was only told about when i joined the interview and that they would be watching live.

One where they wanted me streaming my face the whole time (maybe some people people are fine with that)

And one that would count it against me if i tabbed to another page. So no documentation because they assume i'm just googling it.

Still it's mostly on me to prepare and expect this stuff now.

But I have also been to places that demand actual working code which is compiled and is tested against cases

Usually there the problem is simpler, so there's that

Huh? Of course you can. If you're practicing on leetcode, there's a discussion thread for every question where you can ask questions till the cows come home. If you're in a job interview, ask the interviewer. It's supposed to be a conversation.

> I wouldn't even mind the studying on leetcode types sites if they actually had decent explainers

If you don't find the hundreds of free explanations for each question to be good enough, you can pay for Leetcode Pro and get access to editorial answers which explain everything. Or use ChatGPT for free.

> It's not a matter of skill, it's just my ability to take in certain types of problems doesn't work well.

I don't mean to be rude, but it is 100% a matter of skill. That's good news! It means if you put in the effort, you'll learn and improve, just like I did and just like thousands and thousands of other humans have.

> Without any chance of additional info/questions it's literally a setup to fail.

Well with that attitude you're guaranteed to fail! Put in the work and don't give up, and you'll succeed.

I'm fine with hard questions in an actual interview.

Yeah this one confused me. Not asking clarifying questions is one of the sureshot ways of failing an interview. Kudos if the candidates ask something that the interviewers havent thought of, although its rare as most problems go through a vetting process (along with leak detection).

Also, the reviewer gets an AI report telling it whether you copied the solution somewhere (expressed as a % probability).

You have few minutes and you're on your own.

If you pass that abomination, maybe, you have in person ones.

It's ridiculous what software engineers impose on their peers when hiring, ffs lawyers, surgeons, civil engineers get NO practical nor theorical test, none.

That could exist for software too, but I'm not sure HN folks would like that alternative any better. Like if you thought memorizing leetcode questions for 2 weeks before an interview was bad, well I have some bad news.

Maybe in 50-100 years software will have that, but things will look very different.

Plumber is probably the closest to what you're getting at. They are state licensed typically, with varying levels of requirement. But the requirement is often just like "have worked for 2-4 years as a trainee underneath a certified plumber" or whatever. That would be closest to what I'm guessing you would be recommending?

Also relevantly: the accountant and plumber jobs that are paying $300k-$500k+ are very rare. There exist programming jobs that pay what a typical plumber makes, but don't have as many arcane interview hoops to jump through.

So .. my approach would be to just open dev tools and deactivate that event.

Show of practical skill or cheating?

But probably a general solution exists ... and there are actually extensions that will do that in general.

  > you can't ask clarifying questions

This solves one problem but it does add performance anxiety to the mix having to live code.

Until companies can focus on things like problem solving, brainstorming, working as a team, etc. the situation won't improve. If I am wrong, why is it that the vast majority of my senior dev and dev management career involved the things I just mentioned?

(I had to leave the field, sadly, due to disability)

Oh and HR needs to stop using software to filter. Maybe ask for ID or something, however, the filters are flagging everyone and the software is sinking the ship, with you all with it.