Did you mean to type 25? 5 years ago LC challenge were as, if not more, prevalent than they are today. And a single interview for a job is not something I have seen ever after 15 years in the space (and a bunch of successful OSS projects I can showcase).

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.

Not sure if that's a typo. 5 years ago was also pretty LC-heavy.

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.

I read this, and intentionally did not read the replies below. You are so wrong. You can write a library, even an entirely new language from scratch, and you will still be denied employment for that library/language.

> 5 years ago you'd have a project like that, talk to someone at a company for like 30m-1hr about it, and then get an offer.

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.

I have been getting grilled on leet code style questions since the beginning my of my career over 12 years ago.

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

LC interviews were made popular by companies that were started by CS students because they like feeling that this stuff is important. They're also useful when you have massive numbers of applicants to sift through because they can be automated and are an objective-seeming way to discard loads of applicants.

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.

But why stop there? Why not test candidates with problems they have never seen before? Or problems similar to the problems of the organization hiring? Leetcode mostly relies on memorizing patterns with a shallow understanding but shows the candidates have a gaming ability. Does that imply quality in any way? Some people argue that willing to study for leetcode shows some virtue. I very much disagree with that.

> 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.

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.

> If it didn't actually work, it would've been discarded by companies long ago.

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.

> If it didn't actually work, it would've been discarded by companies long ago

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?

Does it work though?

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 road to becoming good

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.

> 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.

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.

It's also a filter for people who are ok with working hard on something completely pointless for many months in order to get a job.

> If it didn't actually work, it would've been discarded by companies long ago

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

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

I prefer AGAMEMNON: Apple, Google, Amazon, Microsoft, Ebay, Meta, NVIDIA, OpenAI, Netflix

"Startups" and "Enterprise"? I guess that basically covers everything

Lol :)

There's even a rocket emoji in server console.logs... There are memes with ChatGPT and rocket emojis as a sign of AI use. The whole repo looks super vibe-coded, emojis, abundance of redundant comments, all in perfect English and grammar, and the readme also has that "chatty" feel to it.

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.

I used AI for the Docker setup which I've already done before. I'm not wasting time on that. Yeah you can vibe code basic backend and frontend and whatnot, but you're not going to vibe code your way to a full inverse kinematics solution.

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.

Enjoy the ultimate classic tour de force from world treasure Chung-chieh (Ken) Shan’s wikiblog "Proper Treatment"

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

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

Part 2 is the challenging part; it's mostly a problem solving thing and less of a coding problem

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.

That sucks so hard man, very disrespectful. We should team up and start out own company. I tried checking out your repo but this stuff is several stops past my station lol.

We did go into the assignment after I gently bowed out of the goofy live test. The CTO seemed uninterested & unfamiliar with it after returning from a 3 week vacation during the whole process. I waited. Was happy to run him through it all. Talked about how to extend this to a real-world scenario and all that, which I did fantastically well at.

I put absolutely every egg into that basket. The prospect of working in Europe (where I planned to return to eventually) working on cool robot stuff was enticing.

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

It isn't impressive to spend a lot of time on a hiring problem, you shouldn't do that. If you can't do it in a few hours then just move on and apply for another job, you aren't the person they are looking for.

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.

The other comments here note that, and the author even stated it directly, that it was vibe-coded.

No. Should I invoice them? I'm still livid about it. The kicker is the position pays a max of 60-120k euros, the maximum being what I made 5 years ago.

Yes. I put a ton of work into it. I had about 60 pages worth of notes. On inverse kinematics, FABRIK, cyclic algorithms used in robotics, A*/RRT for real-world scenarios etc. I was super prepared. Talked to the CEO for about two hours. Took notes on all videos I can find of team members on youtube and their company.

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.

60k-120k euros. The upper 20k probably being entirely inaccessible so in reality probably like 70-100k euros.

The only part of memorizing fastest algorithm the vast majority needs is whatever name that goes by in your library. Generic reusable code works very well in almost any language for algorithms.

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.

"Fastest algos" very rarely solve actual business problems, which is what most of us are here to do. There's some specialized fields and industries where extreme optimization is required. Most of software engineer work is not that.

I’d say it’s not even problem solving and it’s more pattern recognition.

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.

> 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.

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.

> memorizing fastest algos

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.

If a position needs low-level from-scratch code so performance-critical, and needs it so quickly that the developer must recall all of this stuff from memory, any candidate likely wouldn’t be asked to give a technical interview, let alone some gotcha test.

That was because the parent complained about not having good write ups. You can use GPT which has already been trained on publicly available solutions to generate a very good explanation. Like a coaching buddy. Keeping in mind there are paid solutions that charge 15k USD for this type of thing, being able to upskill at just 20bucks a month is an absolute steal.

I think LC is used mostly as a metric of how much tolerance you have for BS and unpaid work: If you are willing to put unpaid time to prepare for something with realistically zero relevance with the day-to-day duties of the position, then you are ripe enough to be squeezed out.

> 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.

It's bizarre because I see the opposite.

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

For Google, Facebook and Amazon, yes. At least last I interviewed there a few years ago. They're more interested in the data structure/algorithm

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

You didn't read my comment correctly and should have and clarifying questions

If they are on site why not interview them? If the purpose of these online assessments is to be the mouth of the funnel that process is starting to fail.

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.

[dead]

The major difference between software devs and lawyers, surgeons, and civil engineers is that the latter three have fairly rigorous standards to pass to become a professional (bar, boards, and PE).

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.

At least in the US, lawyers, surgeons, & civil engineers all have accredited testing to even enter the profession, in the form of the bar exam, boards, and FE & PE tests respectively. So they do have such theoretical tests, but only when they want to gain their license to practice in a given state. Software doesn't have any such centralized testing accreditation, so we end up with a mess.

"don't think about triggering a focus change event on your browser, it gets reported)."

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

Show of practical skill or cheating?