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It’s been a month since I offered coaching for EA software developers.

The main goal of this update is to create transparency and invite outside feedback that will make a better project long-term. There are also some topics that I won’t be transparent about, but I can at least be transparent about my reasons for this (for example, the mentee’s privacy).

Since I’m writing an update, I’ll also write some requests for help, feel free to jump to that section.

Numbers

I have about 5 meetings per week, including about 20 future meetings already booked.

I estimate I talked to about 20 people and have 13 chats open, out of which 8 were active in the last week. [Excuse me for off-by-one errors, I just skimmed my calendar and chats]

If you tried to schedule with me and found my schedule is full: I only noticed the problem while writing this update, but now I opened up more slots.

TL;DR: There is definitely demand for this.

How is it going?

I’ll talk about my experience so far

  1. I don’t feel overwhelmed, I’m enjoying this. My brain is constantly in “how can I do this better” mode, which I like very much.
  2. Async text/voice messages: I wasn’t sure if I’d discover why nobody is doing this except for me. So far, it’s great, and I wonder if most coaches don’t do it because they have to worry about monetization.

How is this different from coaching in Israel (what I did before) ?

  1. I was really worried about culture gaps, about not managing to fit into the social norms of small talk and so on. I approached this problem by being extremely informal, including posting a picture of one of my cat shirts. This seems to be working pretty well: My brain has more or less stopped trying to “fit in”.
  2. Rushing: I try really hard to give significant value to mentees in our first meeting, which is limited in time. What I did before didn't involved time boxed calendly meetings, but rather.. social events. I’m fun at parties.
  3. How useful am I? I don’t think I’m on-par with how effective my previous conversations were, but I think I had only maybe 1-2 conversations where I wasn’t useful. Perhaps I’ll write more about this.

What did I change my mind about?

  1. Exploration vs exploitation: At first, I’d spend ~20 minutes trying to explore “what is the most impactful thing we could talk about”. Many mentees said this was too long. Now I only ask for an overview of potential topics, and reply to each (about one minute per topic). This seems to get a “oh, wow, this was useful” response. I also go over the conversation structure in advance.

Transparency

I’m splitting this into

  1. Technical advice: such as how I recommend maximizing one’s salary.
  2. Soft coaching skills: such as how I help people resolve internal conflicts.
  3. Results

Transparency on technical advice

I’m considering writing posts (like a blog) with common questions I get and answers I often give.

Some topics I started writing about:

  • How to conduct a job search
    • Option 1: If there are dozens (or more) potential companies I could work for
    • Option 2: If I’m aiming for just a few specific companies (such as Google+Microsoft, or Anthropic+OpenAI)
  • How to negotiate for salary?
  • How to discover what I want in a job?
  • How to improve a CV?
  • Is being a software developer a good career path?
  • Am I good enough to get accepted to $COMPANY?
  • So many things to learn, where to start?
  • How to improve in skill long term?

Obvious advantages

  • Scale. I’m “automating” the most common parts of my “work”.
  • People can comment and improve it.

Why not just write all of these?

The main downside in posting these will be that I will get far less feedback and thus won’t improve. If I could magically get every reader to tell me what was and wasn’t useful (including changes in actions), that would resolve the problem for me.

I don’t like generic advice

I believe in customized advice so much more, but that’s a topic for an entire post.

How I plan to approach this problem

Send drafts to mentees

If a mentee asks me something where I have a ready answer, I’ll try sending that answer, and based on the feedback I’ll improve the article until it’s in the level where it actually makes a difference for people.

I tried this once so far, and the conversation went amazingly from there.

Get senior people to review

I hope to find ~5 people to review this kind of thing. If that might be you, please comment or message me.

Try publishing one article

I’ll probably post the “how to conduct a job search” article and see how it goes.

Transparency for the coaching process

A lot of my conversations are saved: Text/audio messages, and lately I started asking mentees if I can record video calls too, so I have some of those.

Someone could review this (after getting permission from everyone of course).

I don’t want to publish this semi-publicly, both for privacy reasons, but also because I will be way too self aware if I expect lots of people to watch me later. I do think I’ll pick 1-2 reviewers though so if you think you’d be a good fit, let me know.

Impact analysis

If someone will ever analyze how impactful this project is, I think that having raw recordings could be really useful.

Transparency for results

I think that talking publicly about results and statistics would be good, and almost nobody does this. 

I will at least organize the information for myself before revisiting this topic. I ask for feedback a lot, and the answers are saved. Still, there are higher standards of measurement that I might try to achieve, for example following up with people.

Calls to action

Are you a data scientist? (Including Machine Learning!)

I am not. Could you help me with these questions:

  • How to decide whether data science or software engineering would be a better fit for someone?
  • How can someone study at home and find their first job in data science?
  • Would you like to mentor data scientists sometimes? I’d be very open to special requests, like “only people in stage X of their career”, and you can also decide to stop any time.

Are you an EA org hiring software developers?

FYI:

  • A LOT of people are asking themselves if they should work for you or earn to give. I send those people to just ask you (“hey, would prefer that I work for you or that I donate X$ ?”), but perhaps you have something better to say.
  • If there are specific ways people can prepare for an interview with you, it would be useful to publicly say so. For example “we ask leet code questions” or “we ask trivia questions about django”. I think that a common pattern for people (who don’t talk to me) might be “I’ll work in some other company for 2 more years to be sure that I’m qualified for the EA org”. I think this is a bad outcome for everyone.
  • Consider keeping in touch, I will probably have more questions come up

Do you know the software ecosystem in the U.S / Europe / (somewhere that isn’t Israel)?

  • How do people find good jobs there? Do you have recruiters? Are there reasons not to use them?
  • In Israel, the official requirements for a job are higher than the real requirements. Are there strange things like that in your country too? (They might not seem strange from the inside, I can try helping with more specific questions)

Are you a first time tech leader or founder?

  • I’d be happy to talk to you, especially if you feel somewhat overwhelmed about the technical aspects (which is the default situation! everyone is just pretending otherwise). So far, only a few people of this profile have scheduled with me and I hope to get more. See some comments in the original post.

Do you work in Algorithmic Trading?

I mean writing software that automatically trades in the stock market.

  • How can an EA get accepted to such a company? (What to study? Where to apply?)

Are you a senior developer or coach who might want to review my work early on?

  • Please comment or message me

Do you like meta questions?

  • I’d be happy for feedback about this post, what was useful, what else would you like to hear about and why?

 

Until next time,

Yonatan
 

Update: Jeffrey is doing something similar, check him out too :)

Comments16
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Thanks for doing this coaching and sharing the update! Some answers from myself; I'm not sure how much my coworkers at CEA agree with me, so these are intended as a personal opinion rather than an official stance:

A LOT of people are asking themselves if they should work for you or earn to give.

I spent a few minutes trying to think of engineers that I personally know for whom it's so obvious they should earn to give that they shouldn't even apply to EA organizations. I was only able to think of a handful, and they are all on the founding teams of $100M+ companies.

I advise myself (CTO/cofounder of a reasonably successful company) and engineers at top quant trading firms to strongly consider direct work. I can think of only one person who had an engineering offer from an EA organization I respected but I thought they should do earning to give instead.

A more common scenario is "earning to learn" – EA org's don't always have junior positions or provide mentorship, and many (probably most) junior EA engineers should be skilling up at for-profit organizations. Again here though, I think these people should at least try to apply for positions at EA organizations, and if they get rejected ask the hiring manager where they should skill up, then try to gain those skills elsewhere.

(I acknowledge that applying to a bunch of EA organizations and getting rejected from all of them really sucks; the above advice is what I think an impact-maximizing robot would do, but there might be psychological reasons why the people you are advising should not do it. To the extent that you can coach people to feel okay with rejection though, that seems helpful.)

If there are specific ways people can prepare for an interview with you, it would be useful to publicly say so

For CEA:

  1. The initial stage of the interview is leetcode-style algorithms questions. Typescript/JavaScript preferred, Python second choice. I haven't given this a lot of thought, but the next time we hire for an engineer I might just outsource to Triplebyte. 1.1. I'm having difficulty calibrating exactly how hard our questions are. I think they are harder than "hard" leetcode questions. I can try to think of a better calibration point, if this would be useful to you.
  2. The last stage is the person actually working with us for a day or two. We have an open source code base, so you can see verbatim what this looks like; e.g. this is what the most recent engineer we hired did during her interview.
  3. Regarding whether people should work somewhere for some amount of time before applying to CEA: the email I send to people with limited experience is basically "to be respectful of your time, I'll tell you that I think you probably won't be a fit here, but it's really hard to judge someone from their resume so if you want to try our trial task you should go for it." Most people bail after that email without trying the task, and no one I've sent that email to has successfully completed it, but I'm sure there are people with zero work experience who would be capable of doing it.

I'm having difficulty calibrating exactly how hard our questions are. 

I think they are harder than "hard" leetcode questions.

Can...can you share one that you think is that hard?

+1 to this question.

Do you mean "hard" in a specific website?

Or perhaps you could make up an example question that is has a similar difficulty to whatever you ask?

Another example: I really like how Anthropic said "If you think you could write a substantial pull request for a major machine learning library, then major AI safety labs want to interview you today"

Leetcode has a "hard" tag on questions, I assume Ben meant these https://leetcode.com/problemset/all/?difficulty=HARD 
I agree there is a huge variance, I have solved 19 last year and remember some being much much harder than others

Yes, I'm fairly sure this is what Ben meant. I've looked over some of the earlier versions of questions Ben was interested in, and I can confirm that the questions are harder than the average "Hard" questions on leetcode, which in turn is harder than typical interview questions at large tech companies. However, for people intimidated by this, I think there are ~3 things that claw back the difficulty somewhat:

  1. The typical expected time to complete a BigTech interview question is about 30 minutes in a 45 minute interview (with ~15 minutes extra time to explain your solutions, ask questions of the interviewer, etc), iirc CEA gives you ~2-3h to solve their questions.
  2. Most BigTech interviews are closed book on a whiteboard, iiuc CEA's interviews are open book and you can use your preferred IDE.
  3. (Only relevant for people familiar with leetcode questions). Leetcode questions have, for want of a better word, "idioms," ie, common patterns that crop up fairly frequently across leetcode problems, including Leetcode Hard problems (e.g., sliding window, square root decomposition) but almost never real programming jobs. This makes Leetcode Hard problems easier for people who've already solved other LC problems, in ways that don't generalize as well to solving algorithm puzzles that don't come from the same generator. 
     

One reason I asked about the difficulty of Ben's problems, is that I want to calibrate myself to the EA tech talent pool when giving comments. 

It would be good to know if many people here, with little practice, can solve unseen leetcode hard problems in a BigTech interview format (where you have to simultaneously create a verbal narrative throughout the interview).

If this is true, I will stop giving "advice" on any tech related post as this is out of my reference class.

Charles,
TL;DR: I would not stop giving tech advice just because you can't solve hard leetcode puzzels

Longer:

If this [solveing unseen leetcode hard problems in a BigTech interview format] is true, I will stop giving "advice" on any tech related post as this is out of my reference class.

If it influences your opinion:

  1. I think I'm very good at leetcode puzzels
  2. I give tech advice
  3. I think those "skills" are almost totally unrelated.
    1. It is very rare for me to actually teach someone how to solve leetcode
    2. It is more common for me to just point out "cracking the coding interview" as a legit way to prepare for big-tech interviews, but knowing this is unrelated to my ability to solving the questions myself. (I know it because a Google recruiter recommended that book for me. I can elaborate)

Thank you for the thoughtful reply Yonatan!

I guess my intuition is that the correlation between being good at giving career advice for techies and being able to solve algorithms puzzles is only moderate, and very little of that is causal.

It would be good to know if many people here, with little practice, can solve unseen leetcode hard problems in a BigTech interview format (where you have to simultaneously create a verbal narrative throughout the interview).

Fwiw I suspect this is pretty uncommon among EAs, including EAs in tech. I was unusually good at leetcode-style problems (both in general and especially relative to my ability to actually do useful work in programming), and I suspect my hit rate for novel LC Hard problems in 30 minutes was less than 50%*.

*I've regressed a lot in my algorithms puzzles ability, I'm not even confident I can consistently do LC Easys now. 

As Linch says, we don't use the interview format you describe. It's all done asynchronously, and with less time pressure. I'm not well calibrated on how well the average EA does under the whiteboard format, but I would say that in our format:

  • ~50% of applicants pass our 30 minute screen
  • 5-10% pass our 2.5 hour in-depth task
  • ~5% get an offer

Note that the people who apply for our jobs are probably not representative of who you would speak to on the Forum, so I'm not sure how helpful these statistics actually are.

Lorenzo was correct, I was referring to the classification of "hard" on leetcode.

A rough equivalent to our trial task is: implement a piece table in 2.5 hours from a scaffold with some basic tests, using Wikipedia/the Internet but you aren't allowed to verbatim copy code. It's done as a take-home, so you don't have to think out loud or write on a whiteboard or whatever.

I spent a few minutes trying to think of an analog to the Anthropic statement; I think if you are able to write a substantial pull request to a popular npm package (or similar web-based framework) I'm probably interested in talking. (Though I want to reemphasize that people should value my time at ~0, and therefore apply even if they think they are unlikely to get an offer.)

In response to your questions, speaking with some (limited, worked as an not-100%-software engineer in the SF bay area with lots of SW eng friends) experience:

How do people find good jobs there? Do you have recruiters? Are there reasons not to use them?

  • Large or VC-rich companies have recruiters, they're fine to use. Lots of good but smaller companies don't have recruiters. You can apply through their website but get a referral if possible.
  • A referral? Yes, most companies have an internal referral system, and if you can get any kind of referral whatsoever, this helps you.
  • If you hate networking, Triplebyte (https://triplebyte.com/) is pretty great. Take a programming test, get matched with top companies.

Something potentially non-obvious: there is an indirect and socially-acceptable way to ask for an internal referral. It goes something like this:

  1. If you know someone who currently works at a company: you don't have to ask indirectly. You can just say, "hey, will you refer me for [job] at [your company]?" You can offer to give more context on why you're interested or what relevant background you have, but you may not need to.

  2. If you have a tenuous connection[1] to someone who works at a company: it's acceptable to contact them (over email if you have it, otherwise over LinkedIn) saying something like, "hey, I've been looking at [job] at [your company] and would love to learn more about what's it like to work there. Any chance you'd have have time for a coffee chat / video call to talk about it in the next week?"

    1. If they agree, aim to have a pleasant conversation about your mutual (tech / business) interest. Be a friendly, curious person who enthusiastically wants to hear about their job and company culture. This is not an interview in either direction!
    2. Towards the end of your conversation, assuming you're still interested in the job, say something like, "alright, thanks so much, this was so helpful. I think I will apply!" (pause here to see if they offer to refer you) "No pressure, but I figured it doesn't hurt to ask: does [your company] have an internal referral system? Any chance you'd be willing to refer me for [job]?"
  3. If you have a no connections at a company: it's acceptable to look through your social networks (e.g. LinkedIn, Facebook) to see if anyone at the company in one degree of separation from you, and ask for an intro through your connection. For example, you might be in touch with a former co-worker who was in the same grad school lab as someone now working at the company. It's okay to ask that former coworker something like, "hey, I'm not sure how in touch you are with [person], but I'm thinking of applying to [their company] and would like to learn more, any chance you'd be able to intro me to them?". Make it clear that they can say no! If they say yes, you will probably get an intro email to the person, and then this turns into (2).

In Israel, the official requirements for a job are higher than the real requirements. Are there strange things like that in your country too? (They might not seem strange from the inside, I can try helping with more specific questions)

  • It is the case in the USA that a good candidate usually meets more than half of the listed job requirements, but a candidate who meets all of them is probably overqualified.
  • One thing I've found annoying / weird is that you don't necessarily hear back from recruiters or others if you don't get a job, even after an interview. This varies among companies, but for many of them you just... eventually assume that you didn't get the job.
  • You may have seen this already, but Haseeb Qureshi's writing on US tech careers for earn-to-give is top-notch stuff: https://haseebq.com/tech-careers/. I've forwarded his advice on negotiating job offers to SO many people.

  1. on the level of, like, "took a class with them 5 years ago" or "volunteered with them at an event once". These are not people you're really in touch with. ↩︎

Thank you very much, this is very useful for me, specifically that you also added the culture/social norms which there's no way I'd guess myself

I have a mild amount of insight into getting algo trading software engineering jobs: I had an internship at one of these companies this last summer and got a full time offer from from several. (However, I'm planning on working on alignment).

Maybe this is all totally obvious, but regardless, my short summary for one path into this industry is something like:

  • Go to university in the US, ideally somewhere with prestige. Top public universities (e.g. university of Michigan) can be decent, but MIT or similar is better.
  • Try to build up an internship ladder to one of these places. Maybe go small company -> small hedge fund or other finance -> algo trading.
  • Once you get an internship, you should be basically good to go (assuming the company thought you did a good job). I think most people get return offers and once you have an internship at one of these places, it's easy to get past the resume screen at other algo trading companies.

This means that internships after freshman/sophomore year can be really important. Of course, ideally, you would just intern at an algo trading place from the start, but these internships can be hard to get without the right prior internships.

Obvious advice is under rated, thank you for sharing this

Thoughts on data science questions from myself (worked 2 junior data science positions after ~1 year of self-study) and my circles (mostly DS/ML at tech orgs):

How to decide whether data science or software engineering would be a better fit for someone?

  • Data science work involves more uncertainty and longer iteration times (i.e. debugging workflow is more of an art and takes half a day as opposed to a minute). Does this sound like a pro or con?
  • DS/ML hiring managers care more about pedigree. Your resume may be auto-filtered by HR/scanning software if you don't have a graduate degree in ML/math/stats/computational science. Do you have one/would this be of interest to you? 
  • What areas of DS/ML are you most interested in? Depending on what that is, SWE and DS work may not be mutually exclusive: Look into positions in analytics engineering, ML engineering, data engineering, software engineering for telemetry/observability (common in organizations with more mature analytics departments). 

How can someone study at home and find their first job in data science?

Would you like to mentor data scientists sometimes? I’d be very open to special requests, like “only people in stage X of their career”, and you can also decide to stop any time.

  • I'd be willing to mentor data scientists, though would probably only be useful to people more junior (i.e. finding their first job in data science).
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