Our software engineering interviews are changing a little
blog.janestreet.com
blog.janestreet.com
What I want to know is whether someone has basic DSA understanding. Is the person familiar with any programming language. Can they translate business requirements into code? Can they disambiguate weird things PMs say into a viable plan?
You do not get a better signal about that from asking harder leetcode problems.
Never once in my career has writing a tricky algorithm under time pressure been relevant. The closest thing I can think of is debugging complex systems in an outage, but then it’s more like familiarity with bash commands and general debug skills.
As for LLMs and coding, companies need to figure out how to differentiate good and bad outputs here and what lasting engineer inputs to select for. And I don’t have any idea about this.
The argument was dsa functions like an iq test. It’s not relevant to the job (in fact it’s harder than the job, far harder) such that if you do well on it companies can be confident you can do well on the job just like how scoring high on an iq test makes people confident you’re intelligent.
There are plenty of arguments against what I said above and going after this argument is the better target because the irrelevancy of dsa to the job is widely known and obvious.
I've been engineering systems for 25 years. On a macro level, most of my time is spent considering the right tooling and stack for a job, balancing budget and time constraints and efficiency against how things may need to scale in the future. On a micro level, in the data model and in the code itself, choosing the best structures for a task is important for maintainability and overall coherence.
In my experience with LLMs, I often need to guide them toward choosing the right ways to model data on the code and database level. LLMs seem to prefer json blobs of unstructured data, naming conventions that drift over time, argument structure patterns that change from one piece of code to another. The net result is a lot of tables and code that an LLM needs to read back through, find all the linkages, and recommit to its window before any debugging can take place. It makes human debugging very difficult if, for example, an LLM decides to just store all the userdata in some json column and then decides to add some kind of stateful preferences to that, and other state to something in memory, and then parse the memory falling back to the database state. I've seen a ton of things like this where weird ways of handling state kinda work, until they don't, and it's extremely difficult to figure out what is taking precedence when or where a thread race is coming from.
All this is to say that DSA knowledge may be even more important when LLMs are writing most of the code, because an unguided LLM will write stuff that can practically only be maintained by an LLM, and make design decisions that don't cohere or scale. If that's not really a problem, and you're certain that the code you're investing in writing will never need human intervention, then I guess it doesn't matter. But with a large enough system designed that way, the boundaries and edges of poor DSA choices aren't going to be apparent until either something breaks or you need to grow.
The reason more companies don't IQ test is that it's an ineffective tool for candidate screening. We all intuitively get that as software developers: imagine hiring off an IQ test rather than just having someone write code.
Regardless, you vastly overestimate how much effort is put into hiring. The large majority of companies would never study the effectiveness of IQ tests to know if they are useful to them or not. Researching what works and what doesn't isn't on their radar and they wouldn't know how to anyway. If they had a gut feeling that an IQ test would be helpful they would try it on that basis, except they wouldn't try it because they've read online that IQ test use is illegal; meaning that it is considered to be legally indefensible.
So it's difficult to see how to square what was previously said on this thread, about IQ testing in employment being "illegal" or "legally indefensible". Those are trivially falsifiable claims. Every HR department in the world knows that.
So to the extent that we software engineers were complicit in that myth, we can’t blame management for believing that AI can replace human software engineers now that AI is the best leetcoder.
To get into college, there's the SAT test with a minimum score.
To get a high paying software job, there's the leetcode test.
These are gates meant to filter out the obviously unqualified candidates. Unqualified candidates waste the time of the candidate and the company. The real interview comes after that.
And leetcode is not something you prep for once in your life, but every time you switch jobs.
So he did the three weeks, passed the leetcode, passed the interviews, and now makes 400k.
When I was 10 or 11, I asked my dad what MIT was looking for in a student application. He (an MIT alum) told me. I picked out the things I could do (being captain of the football team was never going to work for me), applied to MIT, and got rejected. But Caltech, Dartmouth and Johns Hopkins did admit me.
You do what you gotta do.
The biggest problem, of course, is that they also filtered qualified candidates (I personally got filtered out multiple times and I'd like to believe I was qualified!) But it is an understandable compromise whenever there is an extreme asymmetry in the volume of candidates and volume of interviewers, and the fix for that is simple: you study for the test (as you pointed out.)
Note also that as grandparent comment indicates, this test is a necessary but not sufficient condition; it's just to get your foot in the door for a deeper evaluation.
It's like "to get into Marine boot camp, there's a minimum crochet requirement".
Solving leetcode problems has nothing to do with commercial coding. It's an unrelated hoop that we make folks jump through, because it's easy to measure. It's like measuring developer productivity by LoC written.
Yes, it'll measure how much time the candidate spent preparing for the interview, and how well they can jump through hoops. But it'll also deter the actual people you want in the team, the folks who know that leetcode has nothing to do with commercial coding, and see the leetcode test as a sign that your organisation has no clue and a bad management culture.
It also reminds me of the "EE"s who carry around a card in their wallet with:
V = IR
I = V/R
R = V/I
> But it'll also deter the actual people you want in the team
All the FAANG companies do leetcode testing, so you can write off the high paying jobs.
I guess that's staying as a valid measure then - if a company uses leetcode for its interviews, it's probably somewhere I don't want to work.
People don't like Leetcode because it's insulting to treat them like freshmen that know nothing but algorithms that relate poorly to the job at hand; can't judge them on coding prowesses, for most of them, indeed.
I have a friend who is a tech recruiter. There are an awful lot of frauds trying to land programming jobs. Hiring a fraud can cost a company a great deal of money. It shouldn't be any more insulting than applying for an accounting job and the employer does a routine background check to ensure that the candidate is not an embezzler, and not a drug addict.
I worked for a company that hired a coke addict. What a financial disaster that turned out to be.
Having a history of embezzlement or fraud is not in the same ballpark as struggling to whip up a DSA solution. One is a crime and one is a competence issue at best.
Too many frauds have managed to get degrees. I've worked with many of them. Degree'd engineers who cannot use a calculator, who cannot do basic geometry, etc.
If my Googling is correct, you will have chances to retake the strength test. Even if they only give you one try, you know exactly what is tested and can train to the point of near-certainty that you will pass, if your body is capable of it at all. (By contrast, leetcode doesn't care if you could learn a problem, it fails you for not figuring it out on a particular day with a particular interviewer.)
The best jobs can set an arbitrary high bar that loosely correlates with what they want, but it doesn't mean anyone who fails is unqualified to have any software job.
That's where studying it in advance comes in. Like for any test.
> but it doesn't mean anyone who fails is unqualified to have any software job.
It's pointless to argue absolutes when it comes to anything human. Filters do not have to be perfect to be effective.
For example, if I say "people like ice cream" and the pointless reply is "not everybody likes ice cream".
You got my vote right there. I also find it funny that LLMs can easily do leetcode problems, because there were so many examples and easy test cases.
> You do not get a better signal about that from asking harder leetcode problems.
I think this is a thing that needs bigger formatting for this statement or a feature to vote twice.
---
Only response I have to this:
There are many different schools of thought on how to architect systems. In many cases these different opinions don't have a lot of solid backing on why you'd do this. On top of that there is level restrictions that prevent talented individuals from being more influential. I.e. an Architect is less about technical experience and excellence and more about the abiltiy to communciate to high level stakeholds and having systems that can solve the problem [some what].
I have been looking for resources that tackle/teach/learn this translation part, but so far hasn't gotten any hits. Can anyone here point me to such a resource, if it exists?
The problem is that the compensation was so generous, and the kind of questions being asked so public, that your typical somewhat less talented, yet hard working grads would just cram for the interviews, and get past them, thus lowering the value as a filter. Leetcode and the like decided that there was an industry in helping you cram. The filtering got worse and worse, and the companies then decided to keep upping demands, hoping to still get the most talented. But there's nothing in a leetcode interview that cannot be trained. So the metric became the target, and we ended up in the current mess.
I agree with you but this is a "simpler" test with a subjective analysis (simpler in the sense that the candidate might make some progress rather than completely stuck). Big Tech works at a scale where they probably want to quickly evaluate based on objective results. Did they crack the problem or not? Imagine having a pool of 1000+ candidates for a single role.
To filter out the other 499, they can either ask a very difficult question, which based on the previous paragraph we have established is not a useful signal, or we can use a random number generator. Asking a very hard question also rewards luck in a different way, because a candidate who is lucky enough to have recently memorized that question or a similar one will be able to pass it. It does not generalize to anything actually useful for the job.
I submit that the random number generator is a faster and cheaper method.
first, a coding problem that is solved live (right now, online) -- it's not a hard one and most LLMs can easily one shot it.
BUT: if you are not a senior developer, you need to do it without LLM, and if you are a senior+ and do it via LLM, the bar is super raised and now you need to explain in details everything the LLM wrote as if you wrote it yourself.
the main component here is to know if the candidate understands coding in general, understands problem solving and how to dive into an existing (although quite small) codebase. solving the problem is not really the goal -- in fact, most candidates we hired did not solve it 100%, but were able to understand and explain everything that they put it on code. this usually takes 1h30.
(we also ask the candidate to open a PR against the repo just to see if they know the basics of git -- you would be surprise how many people cannot do it).
the second is an architecture interview, where we build a system together BUT instead of doing the whole spec, miro board, whatever, we do it in more of a free way: we start with a really simple, MVP level, spec and we ask how the candidate would build it. then, we add another feature, and we ask how they would go for it. during this whole thing, i ask random questions like "why would you use x instead of y?" or "why do you prefer this approach?".
one important thing: we allow the candidate to say "i don't know" and we tell the candidate that there's no gotcha questions (which is true, i hate these kind of questions). this lets the candidate be super comfortable (feedback we had from real people).
in general, this flow helped us a ton and i really really like running it :)
(edit: spelling)
I've heard this multiple times now and it still boggles my mind that git is something you have to test for.
not even joking: i've seen people with like 10y of experience trying to push to main :(
https://www.davefarley.net/?p=247
What's incredible is how set some people are in their ways that they can't conceive of alternatives.
I can gather that the way we're using is not the most usual ;).
This is more about opportunity cost because instead of asking about git, you could ask about other valuable skills in your limited time with the interviewee, but I guess if git is really that important, then it's justified.
Because LLMs aren't a reason to not learn your tools. A determinist CLI command vs using a statistical machine for it. It's just a waste of tokens at the very least.
add_github_remote() {
git remote add $1 git@github.com:$2/$3.git
}2. Give your shell functions a common prefix, and/or big-endian naming convention (e.g. things that help you with git start with `@git-`)
3. Tab completion is your friend.
Some 6-figure per year developer spending a quarter’s worth of tokens to do something they do once a month or so is not something I’ll ever care to optimize away…
I don't disagree that having a deterministic CLI is useful, but I'd argue that's not the question here, because the CLI is what the statistical machine will be using. The question is whether the time spent doing it manually is worthwhile compared to the tokens spent on it. I'd further argue that if you instead learn how to pick the right model for the right job so that you don't use something way more expensive than needed for the task at hand, the token overhead will be extremely minimal for stuff like git operations; knowing that you can use something cheaper than like, Astra or Opus if all you want to do is a quick git cleanup and push is going to save your employer a lot more money in the long run than if you insist on doing every messy rebase by hand.
In terms of team practices, that basically seems like a code review thing. If my team has conventions around git, and a PR doesn't fit them, that's something I would point out regardless of how the PR was generated. If a team member is repeatedly not meeting the expectations we've all agreed upon, I would deal with it in the same way I always have; reach out and offer guidance for how to do things the way they're supposed to, notify my manager if they continue having trouble with it, and eventually just not bother looking at their PRs if they absolutely refuse to do things the way everyone else on the team has agreed they should be done.
Even if an LLM can hold your hand through everything, the disruption I've had because people don't understand what the LLM tool is doing, and ultimately does damage (we've had repos corrupted, systems taken offline, systems brought their knees, numerous data security incidents... it's been a fucking nightmare) is immense.
Even worse, it gave a developer a command to run that basically crushed all history across all branches, it was a mess to clean up and lost a significant amount of work. It wasn't Claude running it on its own, but was entirely driven by a mix of a developer's lack of understanding their tools, and trusting Claude's output too much.
This was also the dev trying to "remove a key he had accidentally committed" again, just letting Claude take the wheel.
Of course, the new team _also_ really loved leaning on AI so they were all behind his plan to "clean up the repo" and not just reset the key and move on.
It was a nightmare.
One time setup commands are the sort of thing people do once when setting up the repo, but dont use day to day. its understandable that people dont have that memorized and will reach for a man page, google or an AI.
Though ideally interviewers should appreciate this - unless its a hard requirement you do it by hand day to day - the rest of us can look this up quick enough.
My OS professor in college once told us about what he considered the difference between "knowledge" and "information", with "knowledge" being the underlying facts about how something works and "information" being the terminology/labeling/bucketing/etc. of how to refer to it. The point he made was that knowledge was more important than information, and that he would try to test us on knowledge rather than information. To me, knowing how the underlying version control model works and what "shapes" you might want to make with it is useful knowledge. The exact set of commands, interactions with an IDE, or specific prompts you can use to ask an LLM to produce them is information. Arguably the entire benefit of LLMs is that you can ask them to do things even if you don't have the exact information memorized; if you can describe it in a rigorous way, and recognize whether what it gives you as an output fits that or not, you don't need to know any of the actual information of how to do it manually.
jj? what's that?
I wish better names would be chosen by the tech industry, that would make search engine discoverability easier.
Define popular. This is the first time I'm hearing about it.
>not require introduction on HN
It's not necessary to explain acronyms, but gawd damn, I wish these products had names that were easily googleable.
Tangent, but when I was younger, my main programming language was Processing, and I bet you can imagine how difficult it was to google issues with it :)
They... are?
https://www.google.com/search?aep=11&udm=50&q=should+you+swi...
You can't google for "X" like it's early stack overflow days, but adding the minimum context "X that has something to do with Y" works 99% of the time.
> The command-line tool is called jj for now because it's easy to type and easy to replace (rare in English). The project is called "Jujutsu" because it matches "jj".
There is no way to verify it just by talking.
like, i dont really need to know all the stash details when i only stash one thing at a time, very temporarily
i also dont really care to know all the origin and remote definitions stuff when i only touch it once per project or so.
i could certainly draw graphs of what different git repos look like, but what makes it salient to know the rest of the details unless im actually building git itself? if youre using every git feature regularly you're probably doing something wrong
If I were hiring, I would care about whether you can `git help stash`, skim over it (bonus points for actually using the pager competently) and figure out what you need to do.
I couldn’t care less about stashing commands.
I do care about … if someone understands origins and not by definition because developer needs to know what is his local version and what is on the server and how those two affect each other. Bonus points if they understand server is not special in Git and their colleagues copy on their laptop can be origin as well.
Drawing graphs of what different repos look like? That’s irrelevant.
Irrelevant if one understands that Git uses DAG and is content addressable store.
You see someone might know those hard words but when working daily with Git reasoning about rebase or merge, cleaning up their own work with interactive rebase, making pull/merge requests or resolving conflicts it is much easier if one knows what is local what is remote and how Git stores data.
You also learn it once. In my 15 years of using Git I basically didn’t learn much new commands but having mental model of how it works was my tool to fix any problems other people had. Knowing commands or definitions is secondary.
Now I just ask google, and I get a straightforward "do this", and it works.
That's the thing, though. Stack Overflow is not and never was intended to solve your problem, nor to solve the OP's problem. It was intended to answer questions. It was your responsibility, both as someone posting a question and as someone reading the Q&A later, to adapt knowledge to your circumstances. That's why they're called questions and answers, and are not called problems and solutions.
People who use a web site to get a solution to a problem are looking for a help desk, or a forum. Stack Overflow was specifically created to be not that, and that choice was specifically motivated by the frustration people had with trying to search those kinds of sites for information, and the frustration that experts had with trying to help people (for free) in that kind of environment.
Personally I ask the LLM to summarise what the commit does and explain it to me, make sure I understand it, then review the PR. I'm getting half the speed the High Speed Sloperators are getting but I was the only person submitting PRs the other day when the LLM service was down.
For nasty multi-way git merges and rebases, it's been a game changer. And of course that's reviewable by doing a delta on the final rebase branch vs. the original branch.
With all that said... having to use LLMs at work is making me want to use them less on my own projects.
For the more important changes, I find it easier to stay on my toes by taking a pass at the codebase before comparing notes with the LLM. Peeking at the answer key first makes it too easy to nod uncritically.
Git is an essential tool; not knowing how a key tool works is dangerous IMO
I have not run a single git command in like the entire 2026.
Should you resolve the conflicts in a bad way we're going to see the result in the MR, will we not?
I don't think git knowledge is essential anymore.
Back in the days of the crappy git GUIs this was a problem, because people would regularly misunderstand even the basics of what they were doing and managed to lose their local changes.
That shouldn't happen with LLMs.
Because someone who's familiar with those sorts of things can get the commands typed and running before someone who isn't has even figured out the prompt.
(Well, not so much if there's a need to identify the base commit for a squash, do some cherry-picking, etc. But in those cases I'd rather see direct human judgment of what to do than hoping the LLM understands a vague description.)
initializing a repo, staging files, adding them to the changeset, commiting then pushing those changes are easy to do. solving merge conflicts is a little complicated but IDEs make that much easier to do.
Fundamentally git is conceptually complex in a way that almost no other tool is. Others might have scarier syntax to newcomers but rarely expose the same level of underlying complexity.
the coding challenge itself is just a way to make sure that people can understand a request within an existing codebase. as an example, i pay attention to the questions the candidate asks -- questions asked always mean something.
my general assumption with seniors are "they can think high level", which means i "mark them" with that assumption, so for me, the architecture talk is much more important.
at the end of the day, you need to understand what your org needs and adapt.
The trick is to get a good sense of the algorithms associated with basic data structures (list, stack, queue, graph, hashmap,...). They are primitives and almost any standard problem can be solved with those.
What you need to train most is the capability to break down problems: Like I have this input (and associated metadata), I have this context (may be null), I have those constraints (values, ranges, memory space, time, both, or neither), and I need these outputs. Then it's just a puzzle.
I no longer prepare for coding problems other than a quick refresh of the syntax of the main language. And if it's a whiteboard type of things, I go with pseudocode.
we also ask the candidate to open a PR against the repo just to see if they know the basics of git
A candidate may be able to open a PR and not be able to make a commit without an IDE.
Another candidate might know plenty of git, but haven't worked with Github.
That seems very unlikely. Github is the entire reason git is so popular, vs. any of the other distributed VC systems.
Edit: I'll refine that, after a moment of thought. Git is popular because of Github. But, I guess that now maybe there are people who are using git because it's the popular/default version control choice, but they might not be using Github. They might be using another forge, something homegrown, or just manual builds.
Github was like Yahoo's directory, a way to share content in a searchable place and as a backup/bounce point. In the early days you could also upload to 'downloads' so it was a quick share host. Before that we had email, exposed ssh and cgit/gitweb but Github gave us `PR` to promote social interactions with forking. So it could be argued that Github tainted the spirit of git.
Having personally evolved from making date stamped zip files, to subversion and then to git, it earned its place quite quickly for myself and my roaming nature, didn't hurt who hacked it together either. When Linux adopted it from Bitkeeper, it became the way for many.
Personally I prefer GitLab over GitHub. The CI is better, and it doesn't go down every other week unless you self host on Azure.
I have no problem with letting an IDE or LLM handle those details in practice... but I don't think I'd want to work with someone who doesn't understand the very basics of what's going on under the hood.
The GP said "open a PR", not "make a commit and push it to a remote".
When I tell my LLM to "open a PR for those changes" (which is how I do it nowadays), my LLM understands that what I mean is "make a commit, push it to a remote and raise a PR".
Does it mean we've reached AGI when machines understand what we mean better than some humans?
This makes it seem like all of those things are part of a single operation to you. That doesn't make sense to me.
On the occasions where I've submitted a PR to a project (anywhere, not just on Github), making the commit was not part of the same operation. I'd already made the commit and satisfied myself that it captured everything I wanted, before making the PR. I don't see those things as part of a single operation. I don't think the poster you were responding to does either.
> That doesn't make sense to me.
1. Navigate your browser to GitHub.mycompany.example.com
2. Click the repo name
3. Click pull requests
4. Click the source branch[1] and destination branch
5. Click "create pull request"
???
I started out by assuming this was some kind of good-faith disagreement, but I guess you're just trying to be funny.
[1] Presumably already extant, because they never mentioned anything about committing code, nor pushing it to github (and that's not the same operation!).
The OP said:
"we also ask the candidate to open a PR"
So I think the OP meant to have the candidate, um, open a PR. Which is not the same thing as making a commit and pushing it to a remote. Maybe you always conflate those operations, but that doesn't make them the same operation. If the OP actually meant that they ask the candidate to make a commit, push it to the remote, and then open a PR, I would have expected the OP to say, um, all of those things, instead of just the last one.
I couldn't say how the OP expected the candidate to open a PR, since I don't know what their standard workflow is. There are ways of doing it from the CLI, as well as through the web interface, as well as through various IDEs.
> I started out by assuming this was some kind of good-faith disagreement, but I guess you're just trying to be funny.
Please save your patronizing for another time. And stop trying to put words in my mouth.
How does that work? Git has no concept of pull requests.
Doesn't surprise me at all that many developers can't do this, most professional software development isn't happening on Gitub.
Interestingly, an LLM involved feels like it’s made it easier to assess candidates. Senior candidates know exactly what they’re doing and strongly driving the LLM. They pre-communicating design decisions, gotchas, and requirements. They also ask a lot of clarifying questions and dial in the scope (after all not building something is better than building it).
Less experienced candidates tend to jump right in, build way too much, and stumble because they delegated all of the critical thinking to the agent. They often end up in a place where the agent doesn’t align with their vision and they can’t really reign it back in.
Worked with a "super senior", lead architect. Management was raving about the guy before he joined. Insane resume. Skipped the regular interview process because of this.
Had to show him how to open a PR and setup his git config so his commits are linked to his account. And then his PR's failed the automated ci checks for descriptions and titles, and he came to me to ask how to fix it. The failing gh action literally says what was broken.
This is all with Claude available btw, so one could literally just ask.
I guess it's a bit of a modern fizzbuzz. Where it's so simple but still manages to stump a lot of candidates.
The idea is to see how the candidates deals with it. Maybe he will just say "fuck it" and do it by hand, or patiently point out every mistake so that the LLM gets it right. Both indicate competence, what you don't want is someone who doesn't see the mistakes and hand you slop.
You have missed the point entirely.
Will you allow jj instead. I switched to jj 1.5 years ago (as many others have), and my git is now rusty.
I mean sure, I can do add, commit, basic diff, etc. But rebase/merge - oh dear, I forget which one is source/target (jj made the infinite design choice that the ordering doesn't matter - you have two parents making a child - it's symmetric).
> we also ask the candidate to open a PR against the repo just to see if they know the basics of git -- you would be surprise how many people cannot do it
This doesn't really say anything about someone's familiarity with git, considering pull requests are not a feature of git.
When I worked at a FAANG we used git but had our own internal code forge that was nothing like GitHub.
There are a lot of people telling you how they interview and why. Almost none of them have shown even the slightly indication that they are aware there there is scientific research on what works for an interview, much less that they apply it. They also are not showing any indication that they have done any testing - to see if their questions help hire better people.
If I said they could get equal results by picking resumes at random and hiring them without any other screening could they refute that? If so have they justified every part of their process or just one step that is useful and the rest they don't know?
> One day, the recruiters gave us a special round of packets to review. In these special packets, we were able to read the interviewer notes and candidate responses. All personal details were stripped out, and we were told it was a “calibration exercise.” We had to do our regular voting job with these special packets, and see how it went. I think we may have assumed they were from another site, since cross-site calibration was common.
> Our group did our job, and voted not to hire about 2/3 of the packets. This was about par for the course.
> But surprise surprise, this time, those were our own packets from when we had all interviewed at Google. The recruiters had tricked us into reviewing our own interview packets, and we had voted not to hire most of our own group.
From https://yegge.ai/essays/the-last-technical-interview/ (May 2026)
its not like they instantly reviewed their own docs; the hiring bar and comparisons changed
So that implies that they are testing this, trying to determine if it works better than the current process. Whether they are doing this in a scientifically rigorous way is unclear, however.
In my experience (both as interviewer and interviewee), interviews primarily serve to satisfy the ego of the interviewer.
The topic of the article is about adapting interviews in the age of LLMs.
Scientific research on interview techniques requires years of retrospective analysis after the hired employees have been evaluated in their roles for a long time.
That research does not exist on this topic. It's too new. I don't think this is a valid criticism of the actual article.
You might have 2 people with opposite personality traits ace the interview then get put on a team together, now all of a sudden your whole team is worse overall. That's a massive effect but your study will just see it as noise.
The reality is your best hires will just be intelligent people who belong in the group and who push the mission forward.
The idea of forcing a candidate to give a third party access to their screen, transcribing AI notes, and forcing them to do 3+ leetcode, and an architecture round, and a behavioral round while I watch over them for hours on end sounds completely idiotic and antisocial. This entire industry is high on its own supply when it comes to interviews.
ps also wrote about that interview and my 1000 days at YC company https://domelian.substack.com/p/1000-days-at-yc-company
Jane street news made it to the front page a couple times and got a lot of attention.
Now more people are recognizing the name and upvoting other Jane Street posts.
ok thanks for this slop then. Dont see why this stupid article is on frontpage.
They seem to belive in 'organic' marketing like doing a fake podcasts on dwarkesh. So maybe they have some bots upvoting their name.
Also one of my absolute favorite programming talks ever was hosted by Jane street:
https://www.janestreet.com/tech-talks/algorithm-for-precisio...
It’s like half talk, half story. Got me super interested in logic programming, and minikanren in particular.
They don't have to do marketing, though. It's not like they sell anything to Hacker News readers, they make their money trading finantial assets
The fact that you seem to adamantly disagree that there's any plausible angle here doesn't mean it's not marketing, but it might mean that it is marketing and that it's working on you.
Such strong wording, you got that from me saying "They don't have to do marketing"?
> where did you get this impression of [...] "astronomical salaries"?
From the real world fact that the base salary is US$300k/yr, and often said that the total compensation for the first year ends up being US$700k+. Even for Manhattan + SWE jobs, surely that merits "astronomical". Other devs making that much are usually working at Anthropic or OpenAI, aren't they?
> where did you get this impression of "Very High IQ"?
You didn't copy my ™ there, which was meant to be snarky.
In any case, what I was trying to say is that they don't have to do marketing in the usual sense. They don't have to get the Jane Street logo in your subconscious so you buy a Jane St. product when you go to Kroger's, and you can't sign a Jane St. subscription plan.
People in this thread seem to be implying that the company is botting/astroturfing, but for what? To maintain the image that they're a highly sought after employer?
Anything Paul Graham posts gets upvoted here instantly, because it's Paul Graham who posted it. For Jane Street there's the same halo effect, because many believe Jane Street's work is impressive. Is it really easier to believe the idea of botting to get an even longer list of candidates to interview, than it is to believe people just like to hear what this company has to say?
I don't ever see anyone saying Paul Graham is botting posts about his "essays"
The only alternative interpretation I can think of for what you said is "they waste resources on marketing they don't need to do". I didn't think that was more likely to be your intended meaning, but you're welcome to correct me on it.
> From the real world fact that the base salary is US$300k/yr, and often said that the total compensation for the first year ends up being US$700k+.
Can you clarify where these numbers are coming from? Real world facts tend to have sources that can verify them.
> In any case, what I was trying to say is that they don't have to do marketing in the usual sense. They don't have to get the Jane Street logo in your subconscious so you buy a Jane St. product when you go to Kroger's, and you can't sign a Jane St. subscription plan.
> People in this thread seem to be implying that the company is botting/astroturfing, but for what? To maintain the image that they're a highly sought after employer?
Yes, that's exactly what I'm implying. I honestly would have stated it explicitly in the first place, but I made the incorrect assumption that it was not controversial to claim that this phenomenon exists at least for some companies and that it can be described as a form of marketing.
> Anything Paul Graham posts gets upvoted here instantly, because it's Paul Graham who posted it. For Jane Street there's the same halo effect, because many believe Jane Street's work is impressive. Is it really easier to believe the idea of botting to get an even longer list of candidates to interview, than it is to believe people just like to hear what this company has to say?
> I don't ever see anyone saying Paul Graham is botting posts about his "essays"
If we were discussing this on a website originally created by Jane Street, I would find this a more compelling counterargument. That said, I also don't bother trying to discuss his writing much because I mostly find it insufferable. I find the motives of Jane Street to be more interesting precisely because my opinion on them is more malleable.
Sure. What I said is a real world fact is the base salary, which can be verified by any of their job postings, e.g. www.janestreet.com/join-jane-street/position/4274288002, where it says "Base salary is $300,000. Base salary is only one part of Jane Street total compensation, which includes an annual discretionary bonus".
The claim that has less direct sources is how much the TC ends up being. The figure I said is the one I've heard multiple times over, sometimes by JS employees themselves, so I assume it to be true
> If we were discussing this on a website originally created by Jane Street, I would find this a more compelling counterargument.
That's fair, but I used Graham just as an example of source that always gets upvotes here. Uncle Bob hasn't posted anything in a while, but if he did, it'd certainly trend here, so that might be a better example
> I find the motives of Jane Street to be more interesting precisely because my opinion on them is more malleable.
Yes, that's fair. I don't think it's impossible that JS would bot/astroturf like you're implying, I just don't think it's the case. By Occam's razor I find it's more likely that people do care for what they have to say, similar to P. Graham, Uncle Bob, or any sort of blogpost from Anthropic/OpenAI, etc. It's quite possible that they got to this stage due to intentional marketing, though, so I'll give you that
Probably just random fluctuation.
Yeah, Poisson distributions show up everywhere if you are paying attention. You can even use the theory as the basis for a fast, elegant algorithm to take parallel, weighted random samples. You can even do it in SQL!:
SELECT *
FROM Population
WHERE weight > 0
ORDER BY -LN(1.0 - RANDOM()) / weight
LIMIT 100 -- Sample size.
the book is underutilized?
Few people understand it well, even though it's effectively a binomial distribution (easy to grok) but with special constraints.
Quant firms are also notorious for being some of the most selective in the world, so that alone has become a status symbol. The idea that if you land a job at firms like Jane Street, you must be some 150+ IQ math/physics/cs Olympiad machine.
Year Submitted 100+ points
2014-2020 18-33/yr 2-7/yr
2021 14 0
2022 25 4
2023 33 7
2024 41 1
2025 61 5
2026 93 16
Looks like two things:
1. them publishing a lot more programmer-facing material
2. more news coverage (SEBI ban, Terra suit, ...)
Don't know if it's a deliberate marketing push though, tbh.
Today: https://news.ycombinator.com/item?id=50467297
Yesterday: https://news.ycombinator.com/item?id=50455394
Two days Ago: https://news.ycombinator.com/item?id=50438261
It's a bit odd (?!).
What is the deal with it though? Daily front page content in various forms starts to raise eyebrows.
There are pretty few companies out there like this. Being relatively small probably helps; everyone knows someone that worked at Mag7 and maybe has a bad story to share, but this is more rare.
I never heard of them.
If not for HN, I would never know they existed.
I don't think the remark about "nerd prestige" holds, but beyond that your points boil down to marketing.
And how an unknown company changed its hiring practices is hardly front page news.
Like I said, they are relatively small but they are definitely not “unknown”. Out of curiosity, could you name any quantitative trading firm, or trading firms in general? You specifically may happen to just not be paying much attention to this sector.
In general - I am wondering how engineering interviews change in the age of LLMs, Jane Street, tech-wise is a "thought leader", at least having opinions, sharing them is part of how they recruit "the best", i think oxide does this too.
So in some way, in this time of change it makes sense that they are noisy... It also makes sense that the noises they make may filter down...
Mind going more into this, since you named a specific person? Did he make some prominent statement?
All they've ever done for anyone but themselves is work on the OCaml ecosystem which is not exactly the biggest or most innovative.
I instinctively hear a reply to this in Jeremy Irons’s voice, “We are selling to willing buyers at the current fair market price”.
Reacting faster than others to markets is not front running. Seeing someone else's order and putting yours in front of it is front running. Traders on the NYSE Floor would hear a big order is coming in, and put their ticket in front of it- that is front running.
In a computerized world, front running has essentially ceased to exist- the last major enforcement actions I could find are from 2003, when there was still quite a bit of trading done not by pushing buttons on a computer but by making phone calls. Trading on inside information is alive and well, but this is not what JS does at all, that's the realm of hedge funds that have traders that still click on buttons.
I never worked at JS, but have worked in MM.
Whether you agree with what they do or not, they have had a sort of mystique about them (tons of money, quant vests, _and_ a niche functional programming language as a daily driver??? Sign me up!) that HN likes.
eg: https://www.sec.gov/enforcement-litigation/litigation-releas...
> The cross-market manipulation involves buying and selling stocks at a loss, allegedly for the purpose of moving the prices of corresponding options, so that Avalon could make a profit by trading those options at artificial prices.
> The Court found that the two alleged manipulative trading schemes-if proven-would violate Sections 10(b) and 9(a)(2) of the Exchange Act and Section 17(a)(1) of the Securities Act.
or https://www.google.com/search?client=firefox-b-1-d&q=banging... per https://www.steel-eye.com/news/jane-street-fine-566.3m-marke...
What I learned over time is that first, the pool of people who regularly submit to HN is surprisingly small, so if they have interest in a particular set of topics, these topics are overrepresented in the queue; and second, relatively few people patrol new submissions and the the first 3-4 upvotes in the first 15 minutes decide if something bubbles up to the front page or not. These folks often go by keywords / vibes / employer associations, so again, certain topics get an advantage that's unrelated to the merit of the story.
More generally, I think there's been a significant drop in topic diversity on HN over the past year. Almost everything on the front page is related in some way to AI or to companies on the forefront of AI. It's almost as if there's nothing else going on in tech or in the broader world. If you go to some other aggregators, you get a different view.
Reddit? General-interest subreddits such as /r/technology are mostly mainstream news, but there's plenty of specialized ones, such as /r/math, /r/programming, /r/c_programming, /r/rust, etc. Most of these have relatively little AI, some explicitly contain all AI content to weekly threads.
Many of the aggregators "killed" by HN are still alive, just not as popular. For example, boingboing.net is up and running. Also, places like Ars Technica have RSS feeds, so it's easy to construct your own, you just lose the social aspect.
Consider this: Would you find anything unusual about seeing those stories on the front page if each came from a different company or didn't mention the company name at all? I wouldn't, because each of the submissions is primarily interesting for the content, not the company associated with it.
How ‘wrong’ are we talking? Like the code is correct, but slow? Fails easy-to-spot edge cases? Uses poor taste in variables names?
This is probably genius and also hilarious!
"You are a helpful coding assistant. Make some mistakes."
It's a really interesting time to work in this field. People who are paying attention to workflows are using a range of tools, and constantly refining their own workflow. For example a whole team might use Claude, but one person collects data about their own usage on an ongoing basis and develops more advanced workflows than everyone else on the team. Their focus isn't just about working faster, but about doing better work.
I don't think the post is vague; I think we're at a time where you need flexibility in your interview process to find candidates who are doing the best work these days.
Year Submitted 100+ points
2014-2020 18-33/yr 2-7/yr
2021 14 0
2022 25 4
2023 33 7
2024 41 1
2025 61 5
2026 93 16 Looks like two things:
1. them publishing a lot more programmer-facing material
2. more news coverage (SEBI ban, Terra suit, ...)
Don't know if it's a deliberate marketing push though, tbh.
I think what I'm looking for these days is people with a technical mindset and also can think strategically. So its not Yolo prompting, but creating an engineered environment for creating software for a particular purpose.
So if you want a good AI Engineer you want to test that can address the following things (not exactly, or everything, but they should be covering a lot of these things in some form) :-
- Define goals
- Distributing/Managing work in a team
- Establish guardrails
- Build feedback loops
- Use multiple agents, spanning out AI then recombining
- Setting up Verification
- Evaluating Engineering (Security, Architecture, Code, Performance, Deployment, Monitoring )
- Set it up that the whole process improves itself
- Understanding Domains
- Mitigations for an AI outage.And
Is the salary for these experimental seats higher than before, lower than before, or about the same?
Finally
Given that salary is the same, higher, or lower, is it anticipated that the salary continues the trend in the given direction?
My optimism comes from AI's ability to solve genuinely hard mathematical problems this year. September and October could go down as two of the most remarkable months in the history of AI If, and only if, those proofs are correct and independently verified by real experts. Even if the proofs have been formally verified in Lean, expert scrutiny still matters.
Perhaps one day, interviews will require candidates to "bring your own harness/prompt/skill/mcp"
It is like an unhackable way to do it. Just hiring the person, seeing how it goes, and letting them go or not. It isn't rocket science. The guys digging a ditch outside the office know more about hiring than the career HR professionals inside I guess.
We laid off most of the company and just offshore everything anyway so I don’t care, least I can do is give these randos a chance in Brazil and hope it works out better for them
The LLM era is just dissolving this illusion, revealing the more benign truth: they are a financial company with mildly unusual tech needs. Just like Y-Combinator is just a venture capital fund, just like big techs are just a dysfunctional companies... Your work there wouldn't change the world, and if we left our future up to these institutions, we'd spend it in a couple decades of glut, leaving a deindustrialized barren husk for the next generation.
In some ways, although I detest AI, it has clarified the sort of people and organizations I want to associate with. Any latent characteristics that I abhor have been made obvious with the existence of AI and of course, I would want nothing to do with Jane Street.
ie. Not actually interviewing software engineers.
>>>>>>Our coding interviews haven’t changed, though. The questions we ask software engineers today are the same style of question we’ve been asking for years: sit down with an interviewer or two, program through a problem together, and talk as you go.
>>>>>>Broadly, they involve less code-writing, and lean more higher-level, focusing on software design, on verifying the quality, structure, and intention of code, and on using LLMs to produce code. Most rounds will continue to be traditional coding interviews, conducted without LLM assistance.
I have over 15 years of experience (more if I count my childhood QBasic experience) in programming, and I can tell you right now that if you ask me to sit down with a blank piece of paper and you asked me to write out a sorting algorithm or integer reverser or string reverser, I'm going to be dumb and write out Strings.reverse() or array().sort or tell you something about modulo and loops and look at you or even straight up ask you "This is what you want to do?"
What are you testing for? I've already done the test in my bachelor's program, I have a transcript and paper to prove that I can get sealed and delivered directly to you from my elite university. I did the test in my highschool and have the public records and awards in CS for it. It's all over the internet. I do the test everyday with the applications I have on the App Store, some of which are far more complicated than features you will ever work on in your current job interviewing me. All of those have my name and searchable all over the internet. I even have a few patents, all of which are publicly accessible and fully readable WITH MY NAME ON IT.
Then why the FUCK are you wasting my time in a bullshit interview asking me about dumb programming questions?
This is such an offensive process, I can't even stop being angry about it. I truly feel bad for all the people who have to go through this, because it just does not matter what accolades you have, we all go through this nonsense.
How about you have a simple conversation on the types of problems you encounter and how you would solve them. It's as simple as that. Don't do some puzzle nonsense. Pick real problems, if you are an interviewer (like this one who has been there for 13 year) then you should know what problems you have faced that were challenging to your team and then ask the candidate that. It takes 10-15 minutes to see how they do, and you can end it right then and there. You don't need 10 rounds. You don't need take home homework, you don't need bullshit whiteboarding, you don't need "How many sewer pipes are in a major city?", you don't need panels and weeks of this garbage. Just do, it takes at most 1 hour.