careers¶

Don't Bask in Reflected Glory

Identity

I am here to tell you how to keep your identity small. I'll share what I think is the bare minimum context you need to have:

Why should I keep my Identity small?

Paul Graham explains how keeping your identity small can be a competitive advantage:

The most intriguing thing about this theory, if it's right, is that it explains not merely which kinds of discussions to avoid, but how to have better ideas. If people can't think clearly about anything that has become part of their identity, then all other things being equal, the best plan is to let as few things into your identity as possible.

1. If you know what is part of someone’s identity, you can avoid inflammatory discussions. This can be as simple as avoiding discussions about which shoe brand is the best?

2. The bigger advantage is this: Better ideas. The ability to think with lucidity, without biases is an unfair advantage. If you act on rational decisions without attacking someone's identity, it's an even bigger advantage which few can compete with.

What do you mean by Identity?

Identity, in the crudest sense are the words (and ideas) that you use to describe yourself - in your head. For instance, while you might be someone who build rocket ships, your identity might be "I am a family man". Or “I am a craftsman engineer making ships for space travel”

Here is a short mental exercise. Fill this blank with at least 3 small phrases:

Done?

Awesome. Let's carry on:

Here is what I came up with a few years ago:

The labels in {} are (in the very crude sense) - my identity. Notice that these labels do not always have to be professional, personal or even Truth in the strictest sense.

They don't have to align with reality in any meaningful way. They simply describe how you perceive yourself.

Want another example? Here is what a friend filled:

If you have not filled in your three, please pause - take a quick second and type it down somewhere. I'll wait.

---

Cool, I hope you have your three written or typed somewhere accessible. Let's carry on. We'll come back to it, I promise.

Don't Bask in Reflected Glory

That's it. That is the only thing I want you to do and you will be on your way to learning how do I avoid these labels?

Reflected Glory is the invisible demon which will lead you to the butcher, chop you up into pieces, then slow barbecue you in open air. All this while you and the Demon, both laugh and make merry.

Reflected glory is how Satan wins over honest, smart and hard working people. It is insidious. Sinister. Subtle.

In Professional Circles

Even in certain careers, labeling yourself can be a career limiting move:

And why are otherwise honest people, so deeply tempted to label themselves professionally?

The best people in most professions are incredibly talented and (often enough) make good money. The professional label is aspirational.

The worse off are your professional skills, the more you need to riff on the shared professional identity of amazing folk in your profession.

Here is an important nuance which I constantly remind myself of:

Stop calling yourself a programmer

Don't bask in Reflected Glory

Keep your identity small

In Politics

The politician is tricking you into filling in the gaps he left. What do you will fill this with? What makes best sense for you, from your own identity.

He is hacking your identity to make most profit for him. Don't waste your energy. When making rich people richer, get something in return.

But why does this trope work in the first place?

Well, because somewhere in your identity - you allowed words like Indian, American, Patriot or Nationalist to creep in.

Why did you allow them in the first place? Because there are actually positive connotations of being a part of the world's largest and most powerful democracy respectively.

Stop

You walked into my trap.

You basked in the reflected glory of your ancestors.

Both America and India are countries born of blood, sweat and tears. Not enough of which is yours. You haven't done anything meaningfully large to contribute to democracy.

You are basking in the reflected glory of your dead ancestors

Be grateful. Use them as your ideals.

For the sake of good that is oft interred with bones, don't bask in glory of your dead ancestors

Do the work that when you meet your ideals, they can be proud

Do the work such that you can be proud

Don't bask in reflected glory

Keep your identity small

In Casual Conversation

Brag about achievements of someone you know. Or worked with. Or went to school with.

Everyone around you looks at you for a brief moment of envy, or pride if they love you.

They could have been proud of something you did. And instead they're proud that you know people who do things. You are basking in the reflected glory of others.

The first time I internalized this perspective, I was deeply embarrassed.

Given that you've read this piece so far, I hope something for you.

I hope that when you go to sleep tonight - you will sleep with the resolution to not bask in reflected glory of your friends and family.

No matter how much you love them. You will be proud of them. And you will not bask in their glory. Don't bask in their reflected glory.

It's their spotlight and you will not even a light a candle to steal that

Your Three

Remember the three blanks we filled? Those are the your borrowed labels. No matter how innocent, they cloud your judgment.

Those are the ideas - and people whose reflected glory you are stealing unknowingly

Even the Get things done is basking under the reflected glory of people who actually get things done. It clutters your thinking by making you swing for the extremes. By not letting you slow down.

It might be quite some time before my friend sees that it's about the getting the right things done.

That we are human beings, not human doings.

The moon waxes and wanes because it basks in reflected glory - but even the darkest clouds cannot hide the glory of sun

Why we need to do a reference check on startup teams we work with?

Great Startups always ask someone who is joining for a reference check. They speak to your previous managers and colleagues. There is no reason why candidates should not do the same. Many startup employees have more opportunity costs than the founders themselves.

I'm surprised by the lack of due diligence which candidates do when interviewing with us. I assume that at least a part of this is that they don't know that they can do this. And second: how to check which startups are worth working with?

Well, first off:

I, Nirant, with the power vested in me by decent human beings who care about their lives, hereby grant you the license to do reference checks at places where you will work.

That out of our way, I'll invest the rest of this post how to evaluate startup teams. I write this with an engineer's context, with early career folk in mind. The mindset should transfer to other functions, but the specific examples will not.

How do you pick a team you want to work with?

Given that you're reading this, I am assuming you're are a proactive person.

• Pick teams which grow on your strengths
• Pick teams which mentor proactive people
• Pick teams which take pride in promoting people who are young or from similar backgrounds as you

Go where you're a profit center, not a cost center:

For instance, if your strengths are in Natural Language Processing, you might not want to go work for a neobank. Why? Because their moats and growth come from consumer trust and regulation. Your innovation is a cog in the wheel.

When you are Interviewing

When you are interviewing with a team, ask your interviewer

On Mentoring

Have they mentored someone recently? Are they mentoring someone for the last few months?

• What are the key accomplishments of their mentees?
• What incentives (direct or indirect) do they have for mentoring others?
• Is the mentee growing enough to inspire/challenge the mentor?

Org Scaling

Do they scale by hiring more people or up-skilling employees? What is the balance between these extremes?

• Do they promote internally? If not, ask/learn why?
• Would they back you if you want to learn something adjacaent to your skill?
• What is the state of tooling which acts as safeguards e.g. central platform, data teams, and accelerators in the ecosystem e.g. standardized API configs and deployment across all devs?

(Optional) How many engineers have quit in the last 6 months as a percentage of team size?

On Decision Making

How do they design systems? E.g. who makes the final decision? You might not want to work for hero driven or extremely consensus driven engineering teams.

• What does their release cycle look like?
• How do they handle technical debt?
• What are the safeguards (e.g. central platform, data teams) and accelerators in the ecosystem (standardized API configs and deployment across all devs)?

Asking questions along these lines will give you a pretty fair sense of how they think about investing and growing people, as well as how they make decisions. Those are probably the Top 3 on what determines what your experience will be like with that team.

Things to Avoid

Teams which have communication failures e.g. when you talk to interviewers the company messaging is inconsistent. One person might pitch college pedigree of existing employees. While another person is pitching how meritocratic they are.

Communication failures are easiest to spot. It’s symptomatic of larger problems within the company. When you have a high temperature, you know you are unwell, but you can’t guess why. That’s fine.

If the team does not value hiring, that means the people you work with will neither be effective, nor motivated.

Some of the most common reasons behind inconsistent communication are these:

• leaders are poor communicators of their vision/roadmap
• mid-level managers are poor at executing the vision/roadmap
• they don’t have a sense of what “quality” or skills are needed to accomplish desired goals

There is a motley mix of reasons why communication can be broken. Either way, you don’t want to work with such a team.

And ohh, on startups with condescending recruiters: If someone who is supposed to invite you within the team is not 5-start hospital courteous on call - the odds that they'll be polite & professional when you join are low.

Who to Talk To

Previous Employees

Common Myth: Need to talk to someone from exactly the same role as you.

Better: Anyone who has worked with that team, or close to that team. For instance, do not hesitate to talk about a backend engineering team's skill level from a Data Scientist or Product Manager.

Small teams enable everyone to work closely with each other and have a lot more signal about each other's competence. That means, cross-skill/cross-function bar and ability of competence is quite well understood.

Exception: Someone whose first job was the company you're doing a reference check. Most people seem to have extreme opinions about their first job, atleast till their 3^rd or 4^th job.

---

Chai Sutta Story

True Story: I was about to accept an offer from a company but on a whim, I decided to visit their office. Because I was waiting for my hiring manager to come to work, I hung around at the nearby chai sutta place.

I learnt that the CTO had quit, the Engineering Managers were on notice period and other small array of red flags which I didn't see earlier. Worse, they had no one who could mentor me on data science and my hiring manager's strengths were different from ML. I met the hiring manager, and said No. That was a close save.

The best place to learn about a company's culture is the chai-sutta place. The geekier and more engaged they're about work itself, and not bitching about work -- the better off that team is. Nothing sparks joy than joy of creation in a good team.

If not any of these, I guess it'd be a good idea to do a little bit of Linkedin, Github and Twitter stalking. If none of the devs have never done anything impressive on any of these places, the team might just not be that high caliber. I'd wager that these websites capture something like atleast ⅔rd of the top 2% talent.

---

Present Employees

Present employees in India typically avoid giving anti-referrals. I get why this happens: we like to gossip. That said, there are ways to get enough signal by asking a lot of specific questions. These work best when you've worked for some time (sorry to folks graduating this year):

• What is your typical release cycle? What are the steps? What does your developer tooling look like?
• How do you measure/assess the quality of your software? What metrics define these? What led you to pick these metrics?
• Of the people promoted in last 12 months, why do you think they were promoted?
• I saw on Linkedin that X recently quit to join company Y - do you have a guess on why that happened?

These are all very direct versions, they work for me because I am a little more direct than usual. My friends and juniors, both have used more indirect versions to great effect. The key idea is to get that information, it's less important whether you were tactful in getting it.

How to reach out to people?

Well, there are no right answers to this. For some people, specially those from certain developer communities or good engineering colleges have a wide enough network. They've friends/seniors/juniors in almost every good company worth working with.

If you don't, fret not. Internet is your friend. Tweet to people, find their email id from Github commit messages. For instance, I've had great luck following advice from CTO of Shaadi.com, whom I met over Twitter. And maybe it's finally time to give that 1 free month of Linkedin Premium a try for their inMail.

I've personally had a decent modicum of success with emailing people, simply because developers don't get cold emails from other developers often enough. It's so rare that as long as I don't bungle it up, people do get back to me. Even if it's just to say "I'm busy, but let's talk next week/month".

-- That's it. I hope this quick intro helped you get started on how to evaluate and pick teams worth working with. If you have questions, please feel free to reach out to me on Twitter (or email).

Till we meet again,

Natkhat Nirant

Revised: September 2020. Original 2017 Edition lives here

Get this directly in your inbox by leaving your email id here:

How to prepare for a Data Science job from college?

A Getting Started Guide

Let us get our facts straight, shall we?

I am writing from my non-existent but probably relevant experience. I worked in a Machine Learning role at Samsung Research, Bengaluru. It is only 1 of the 4 research enterprises which hire Machine Learning researchers from Indian colleges — the other being Microsoft, Xerox, and IBM Watson.

I am now in a even more Computer Vision focused role for a small enterprise tech company. Here are some pointers:

Forget the courses

I am from BITS Pilani, Pilani Campus. College courses and even a lot of popular MOOCs are mostly useless in getting a Machine Learning or Data Science role. They don’t have enough of a learning curve at most colleges. Neither in theory nor in programming skills.

Build a project worth noting

Have you done any decent Machine Learning projects? What is the largest data size that you have handled? What is the most complex data set that you handled? How important was the problem that you applied Machine Learning to the society? Participate in Kaggle competitions and Hackathons, if you don’t have good answers to these questions.

Intern in your summers

Summers and semester internship programs in a Machine Learning or Data Science role. I did my semester internship at a startup and skipped Amazon against lot of prevailing (and probably correct) wisdom at the time. I was grilled on my intern project in my campus interview.

Share your results

Share like a madman: In a Medium blog, put your code on Github and get a paper published. It is easier (and more tedious) than most people think. My friend’s first paper was in a reputed Springer Lecture Notes in Computer Science. He did not get any guidance from any Professor.

Demo or Die

Projects on the web, projects which can be demo'd using a video or something similar. Essentially, a portfolio that you can showcase to potential recruiters. I walked into an interview with a video of my previous project on phone.

Linkedin India hires as Software Engineers but allows you to grow into a Data Science role. Microsoft Research has among the best research organisations in Computer Science in India. I’d love to work there.

Organisations like IBM Research, Xerox tend to prefer Masters and PhD students over plain undergraduates. You might want to bring that on the table. A Masters in CS can also give you the time to polish your Machine Learning portfolio too.

The simplified formula to get to a Data Science role is this: Build, build more, share and sell

A 2016 version of this is available on Medium