Hiring, Rock Stars, and How Camaraderie Fails Us

The mythos of the “rock star” is a compelling and seductive one.

by Alyssa Kwan on April 4th, 2014

Hunting for jobs is hard. Or at least, it’s supposed to be.

I was a week into my search. Already I had 10 companies reach out to me.

Eight phone screens later, I had four onsite interviews scheduled. I was made an offer less than 10 minutes after I left my first onsite, which I happily accepted – it was one of my top two picks. Eight days after first posting my resume on a single website, I had a new job.

I am a senior software engineer in San Francisco.

Rock Stars

This is by no means typical, but it is far from atypical. Despite the high rate of unemployment, good engineers are hard to find, and the market is extremely competitive. But there is a warped version of reality here – one where a hiring manager recently compared “top-tier” engineering talent to professional athletes. Technology companies in the Bay Area all want “rock stars” – magical beings that, fueled by catered lunch and Red Bull, will strike at market opportunities quickly enough to warrant astronomical valuations by venture capitalists and Wall Street.

A white man in an iron maiden shirt plays air guitar.

Creative Commons photo CC-BY via mijustin

The mythos of the “rock star” is a compelling and seductive one. Unfortunately, it is false. And the way in which decision makers in Silicon Valley, particularly venture capitalists and entrepreneurs, decide who is and is not a rock star, is part of the seedy underbelly of the industry, one that reinforces and magnifies structural oppression.

I Know It When I See It

Let’s accept, as a given, that “rock star” engineers exist and that Silicon Valley startups need them. (We will touch upon this later.) How does someone recognize a “rock star”?

Startups are small by definition. Everything is new. Basic operations which are core to a larger, more established organization have not yet been established at a startup. This is particularly true for recruiting. Human resources as a function is vital, but does not directly generate revenue. Therefore, it is not a priority for a startup trying to find its legs. Do recruiters do background checks? How wide is the net cast for a particular role or position? In the absence of formal practices, how do hiring managers – typically the founders themselves – decide who to hire?

The unfortunate truth is that, without structure, hiring is done “by the gut.” You glance at a resume. Does this look like the resume of a “winner”? Based on that glance, do you speak with this person? Does a person “sound smart” during a 30 minute telephone conversation? Do you bring them on-site based on that?

The hiring process is a series of opportunities to say no. Left unchecked, our biases creep in, and we end up hiring people that are just like us.

Isn’t that the case for all organizations? Don’t we all instinctively look for reasons to say no? Yes, this is true. However, the problem is increasingly pronounced the smaller and newer an organization is. Human resources exists as a check to these biases by providing a structured way to assess the capabilities and fit of a particular person for an organization. It also exists to cast the net as widely as possible – seeking potential talent from a wide variety of sources, many of which are non-traditional and make room for a diversity of backgrounds and lived experiences.

Furthermore, lack of diversity is its own echo chamber. In an organization where the founders hire their version of “rock star” – one that is often self-assured about their abilities and outgoing about it – all decision makers are deciding based on the same biases. I have been through many technical interview gauntlets, where a broad swath of the team weighs in on my fitness as a candidate. But if the environment is homogeneous, is there any value to those additional voices? Or do they merely confirm the existing biases of the hiring manager by uttering the same pronouncements that the founders themselves do?

Hiring “By The Gut” Magnifies Our Underlying Biases

If we only want computer science graduates from top schools, we exclude those from backgrounds who may be capable, but, for a variety of reasons, may not have been able to pursue post-secondary education. If we only want people with a certain career trajectory or velocity, we exclude those who have had lives where career was not a focus – whether by circumstance or choice. Is someone a parent, and if so, are they the primary caregiver? Parental responsibilities are rarely divided evenly, and women are single parents far more often than men, for a variety of reasons. Does someone come from a class or cultural background that leads to caring for ailing relatives? Each marker of success that we look for has exceptions a mile wide, regardless of how innocuous they may seem.

And that’s being charitable and ignoring the very real discrimination that exists. How does someone “look smart” or “sound smart”? Does someone who is poor, or who is a woman, or who is an ethnic minority (particularly African Americans and Latin@s, who tend to grow up with a different set of cultural expectations for self expression) come across the same way that a white male from a privileged class background does?

What is this mythical “smart”? The answer lies in the famed technical interviews of giants like Microsoft and Google: the ability to solve algorithmic brainteasers. For example, one common question is how to detect an infinite loop in a singly-linked list. The particulars are unimportant, but the key insight to answering this computer science brainteaser is the analogy that on a circular track, a faster runner will eventually “lap” a slower runner. If you have this flash of insight (and know the characteristics of a singly-linked list), you will know the solution right away. And that immediate response, the fact that this problem is something you either get right away or never do, is part of why this version of “smart” is so seductive. If someone “gets” weird problems right away, and you have them on your team, then chances are they will have flashes of insight that advance the business or avoid critical mistakes. Or at least, that’s the reasoning.

The ability to have these kinds of insights lead to a key set of personality traits that Silicon Valley employers have been conditioned to look for. Someone who “gets” things right away will often be loud about it, rushing to point out their insight to others. They may have a history of having academic and other intellectual achievements come easy to them. This leads to a confidence that can border on smug. In a technical interview, these individuals will often lead the line of questioning. They know the subject matter and are eager to prove it.

Setting aside the question of whether this brand of “smart” is broadly helpful to an organization (more on that later), the lived experience of class, race, gender, gender identity and expression, sexuality, and ability factors greatly into whether or not someone fits that mold. Someone enculturated to be deferential is not going to readily point out their insights even if they have them. This includes those raised with the ideal that being smarter or more quick-witted than your peers is undesirable and unattractive – like most raised female in our society. It includes those whose interactions with authority figures from an early age are predominantly negative – like most people of color, particularly African Americans and Latin@s, whom our police and school systems treat with fear. It includes those who grow up poor, who must blend in to survive, as not having the right clothes or parents with the right jobs are not things to call attention to. It includes those with a non-normative gender identity and expression, where any attention is negative attention. And it ultimately excludes people from any culture where this eagerness to be quick-witted is seen more as obnoxious and immature than as clever.

A person in a button down shirt draws a box diagram on a whiteboard.

Creative Commons image via jonnygoldstein

This definition of “smart” is particularly pronounced in the reality distortion field of Silicon Valley. There is an odd “slacker savant” culture, one where students will brag about how little time they spent at the library. The culture is not one of quiet competence; it is one where people talk a big game about their capabilities and achievements. And ultimately, whether or not someone perceives you to be “smart” in a 30 minute conversation has much more to do with those cues than any other factor.

Camaraderie and How It Fails Us

We are human, and we seek connection. “Smart” people are no exception. There is an odd kind of bonding that takes place over the shared experience of being “smart”. This is not limited to having shared insights that others do not have. It’s also bonding over how the world reacts to it. A man and a woman who are equally gifted with the ability to have these insights will not experience the same reaction from the world at large. Men are largely encouraged – even if there is marginal social cost in popularity from peers, authority figures such as teachers, coaches, and parents will often reward this behavior, while women are often rejected for it. The same distinction applies to race, class, and gender identity and expression. Ultimately, only straight white men of a certain class background will be able to bond over these shared experiences.

A group of five men play foosball in an office environment. In the background a whiteboard wall has speech bubbles drawn on them, one of which reads 'This is way more fun than actual work!' and appears to line up with the head of one of the foosball players.

Creative Commons image via alabut

When the founders of companies are largely “smart” straight white men of a certain class background, they will experience the greatest camaraderie with people from the same mold. And when hiring is done “by the gut”, this psychological comfort leads to mistaken confidence about a candidate’s abilities. Seeking camaraderie and comfort is the opposite of diversity, which often leads to discomfort. And it is toxic to organizations.

The Confidence Game

I am an East Asian American trans woman. I am fortunate that, growing up, academics were a priority in my household. Though my upbringing was not always stable, education was never to be sacrificed. And I’m fortunate enough that it came easy to me from an early age. I didn’t have to struggle for it. Consequently, I had my intelligence, especially in math and science, affirmed to me by a wide range of people every day.

But on top of simply having confidence, I grew up being expected to move through the world as male. And in this society, that means having swagger. And I became good at it. It was necessary for my physical and emotional safety. And being trans, like bearing the cross of anything that one is compelled to be in the closet about, means that I became very good at acting. Everyone who is in the closet has to work day in and day out to convey an image to the world that is something that they are not. In my case, that was as a cis- and heteronormative male.

That’s not to say that being in the closet doesn’t destroy self esteem. In my case, by the age of 30, I was a psychological wreck. But it does make a person good at acting. I had become very adept at convincing people of my intelligence in 30 minute conversations. In other words, I became a model “rock star” engineer.

Couple that with my career trajectory – I never had to deal with children, and only had to deal with other familial responsibilities in less intrusive ways – and I come across “smart” on paper and in person. I don’t have a standard path to a highly esteemed post-secondary education, but as someone who graduated high school into the labor market of 1998 (when there was a critical shortage of technical talent), I happened to dodge that bullet. I was able to start my career earlier than my peers in the context of employers who couldn’t afford to discount entry-level staff.

Ego and Funding

The great irony of all this is that very few companies, including Silicon Valley startups, actually need “rock stars”.

As many larger organizations have discovered, raw math and science aptitude is not a good indicator of whether someone will be a good engineer. Soft skills are what makes a good engineer: Can a person understand the problem being solved from the point of view of the person needing it solved? Can a person communicate effectively to gain that perspective? Is someone conscientious about design, so that when they or a team member has to revisit a piece of code, it can be easily understood and extended? Does someone have the capability to direct their own work and manage the expectations of others appropriately? All of these go out the window when the focus is on “raw intelligence” as defined in the culture of the Valley.

And yet, faith in this brand of “smart” persists. There is a warped sense of ego and self-importance here. Putting millions of dollars of capital behind a team requires a mind-boggling degree of confidence. To be worth that much, a startup must be “changing the world”, even if all that’s at stake is optimizing some virtual advertising. Every entrepreneur fancies themselves to be the next Steve Jobs. The irrational drive for innovation and risk-taking almost certainly demands it.

Great Engineers vs. Great Engineering Teams

This is not an argument to stop hiring people who fit this mold of “smart”. Rare insights have value. But if everyone on a team is focused on insights, who is focused on execution? If everyone on a team is used to impressing the people around them with their quick wit, will they listen to the insights of others? If everyone has a smug confidence, bludgeoning those around them with their intelligence, will they effectively communicate?

The truth is that building an organization is a team effort. It is teams that must function well, not merely the individuals on those teams. And teams require diversity that can only come from having a wide array of skills and life experiences. Software engineering, particularly product software engineering, requires a little of everything. Someone has to be the one with an obsessive attention to detail, and that is unlikely to be the person to whom things have come easy, who is used to putting the book down early. Someone has to be the one to mediate disputes between people and ideas, because ultimately a unified direction must be chosen and executed on for an organization to move forward. Someone has to be the one to do the unglamorous work of finding and fixing bugs, often in other peoples’ code; those used to cutting their own code bases from whole cloth often make terrible maintenance programmers, choosing to remake entire modules in their own image rather than fixing with the least intrusive means possible.

Teams are ecosystems, and ecosystems must be diverse to survive internal and external shock. If everyone is the same, the ecosystem, the team, will not survive. Building diverse teams requires careful curation that extends beyond the quest for single star players.

Imagine a Silicon Valley funding culture that focused on building great engineering teams rather than recruiting individual great engineers. Would we see the same churn that leads to high value equity exits where the entire company’s talent base leaves shortly afterwards? Would we see the same obsessive focus on being “first to market” rather than being “best to market”? Would we see a focus on building great organizations with longevity rather than merely planning to cash in and jump ship when the first opportunity presents itself? I strongly believe that this brand of “smart” is intimately tied with the short-sightedness that plagues the Valley.

No Rock Stars Needed

After a week of (admittedly flattering) recruiting whirlwind, I had a shiny new job. I started my new job the following week. The company solves interesting problems at scale, and almost certainly requires someone who is both conscientious and has a firm grounding in the theoretical underpinnings of computer science. But “rock star”? No, rock stars do not build products and organizations that stand the test of time. Rock stars do not encourage teams where ego takes a backseat to solving problems in a sustainable way. I do not want to be a “rock star”. I want to be a good engineer on a great engineering team.

As a major generative force for the world economy and society at large, we owe it to ourselves to have a healthy startup culture, one where the objective is to build great organizations with longevity. Only with long-term goals in mind do the interests of stakeholders beyond venture capitalists and other shareholders begin to factor into the equation. If Main St. is to have any hope of surviving against Wall St., we must change.