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)

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.

There is no way to verify it just by talking.

jj? what's that?

I wish better names would be chosen by the tech industry, that would make search engine discoverability easier.

> 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".

https://github.com/jj-vcs/jj

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 :)

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.

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.

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.

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.

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.

    add_github_remote() {
        git remote add $1 git@github.com:$2/$3.git
    }

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…

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.

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.

  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.

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".

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.

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.

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.

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.

How does that work? Git has no concept of pull requests.

I've heard this multiple times now and it still boggles my mind that git is something you have to test for.

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.

I can gather that the way we're using is not the most usual ;).

You have missed the point entirely.

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.

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.

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.

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?

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.

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 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.

> 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)

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.

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.

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.

https://hn.algolia.com/?q=jane+street

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

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 (?!).

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.

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.

I instinctively hear a reply to this in Jeremy Irons’s voice, “We are selling to willing buyers at the current fair market price”.

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.

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.

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.

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.

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.

Perhaps one day, interviews will require candidates to "bring your own harness/prompt/skill/mcp"

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.

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.

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.

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.

ie. Not actually interviewing software engineers.