Happy April 1st! This post is part of April Cools Club: an effort to publish genuine posts on topics our usual audience would find unexpected. The tech content will be back soon!

Over the many years I spent heavily involved in intern and full-time recruiting at $PREVIOUS_JOB, multiple people have commented something to the effect of: "How come Predrag always gets the best people?"

This post is a series of vignettes showing three of the less-obvious ideas that gave us an edge, despite being a startup of ~100ish people that was far from a household name.

Moneyball: a baseball made from a currency collage, with a large dollar sign inked on the side facing the camera. Over twenty years ago, the Moneyball concept changed sports forever. Surprisingly, 20 years later, tech hiring is still reluctant to adopt many of the same principles, so early adopters of Moneyball-inspired hiring practices get to reap the rewards. Here's some of what I learned over the years. Source: DALLΒ·E 2

But why should you pay attention to me about any of this?

While building compilers and distributed query infrastructure, Don't take my word for it: a representative portion of this work is public via blog posts and on GitHub. The GitHub contributor data can substantiate the below claims. my team had:

Moneyball hiring

Just like in pro sports, Moneyball strategies can work in tech hiring too: know the market and your competitors, find which traits they under- and over-value in candidates, and hire the top people they missed.

For example, many companies have rules that explicitly exclude freshmen Or sometimes even a more extreme version, a juniors-only interns policy that only selects people who can convert to a full-time role after the end of the following year. for their internship programs.

This caused a funny situation when I was a freshman in college: a top tech company refused to even interview me for their internship program since "they didn't hire freshmen," and then two weeks later offered me an interview for a full-time position on the basis of my results in a programming competition they had sponsored πŸ˜† My profile on the competition site didn't list my age or the fact I was a freshman at the time!

These factors leave freshmen and sophomores systematically undervalued as interns, while overvaluing juniors (for non-American readers, third-year students in a four-year program).

One year, a surprisingly large fraction of our "campus recruiting competitors" imposed new no-freshmen and/or juniors-only policies for their internship programs. In response, at all college career fairs I attended, I purposefully sought out and connected with the most awesome freshmen and sophomores I could find! They were being turned away by most other companies, so that was one of our best-ever recruiting years!

We hired many exceptional interns that year, including multiple medallists from worldwide math and programming competitions. They were already amazing engineers despite being only freshmen or sophomores. They only got better from there!

This move also paid dividends for years to come:

"Years of experience" vs "experience in those years"

Most companies and hiring managers put a lot of weight on candidates' years of work experience. It's especially a large factor when considering levelling and compensation.

But years of experience is a weird metric: I'll explain via a personal anecdote.

I've always loved playing hockey in all its forms. In 2011, I joined an ice hockey team and I've been playing regularly ever since. I now have 12 years of experience in ice hockey.

And yet, somehow I haven't managed to make it onto my city's NHL club yet! What gives?! With 12 years of experience, by now surely I should have become a Senior Hockey Player on their team, if not even Staff+?

Almost as if the number of years by itself is the wrong metric...

Instead of "number of years" or "success per se," measure the "density of success." Some candidates have experience beyond their years, and many candidates have remarkably little experience despite their years.

A related idea is "slope, not y-intercept".

Mediocrity can be a sign of excellence

A huge barrier for diversity in tech hiring is using an incorrect frame of reference when evaluating accomplishments.

Let me explain by way of example: I'll describe the backgrounds of two people, and you tell me which person seems more promising. Assume both people are the same age β€” say, college freshmen β€” so we don't have to worry about normalizing for density of success purposes.

Person A's extracurriculars include math and programming competitions, where they posted some of the best results in their country's history. Not only did they win medals on the worldwide stage, but in doing so they broke a 6-year medal dry spell for their country. They also won their country's first-ever gold medals in a few events, despite their country not having a well-developed system of training camps and mentors to prepare students for such competitions. In fact, Person A needed less than 6 months of training to go from zero to eclipsing the Elo ratings of their mentors!

Person B also did math and programming competitions. They worked hard and showed flashes of promise, but their outcomes were mediocre: predominantly ~50-70%th percentile in their worldwide age group. Due to a quirk of these competitions, this percentile range is usually awarded a bronze medal. In fact, those percentiles are almost certainly an overestimate: all countries send a fixed number of students to the competition, so qualifying for a large country's team requires much more skill than qualifying in a smaller country. Person B comes from a tiny country, and their demonstrated skill level would without a doubt have been insufficient to qualify for the same competitions if they hailed from a larger country instead. Thousands of their worldwide peers are more accomplished than Person B.

Is there even a shred of doubt that Person A is more promising than Person B?

Except ... they are both the same person! They're both me!

What happened here? The answer is in the framing.

Person A is presented in context and relative to their comparable peers. Person B is presented sans context, and is graded on the same fixed scale with everyone else regardless of initial conditions. One might have also used the word "privilege" here. I intentionally did not use that word, so as not to give the false impression that I feel unprivileged. Even though I'm an immigrant in a foreign country, as a cis white male in tech with a degree from a top university, I have way more privilege than most.

Person A is impressive in a relative sense: they over-achieved compared to the expectations arising from their situation. Person B is "meh" because in an absolute sense, their achievements aren't notable at all β€” and would actually be considered a big failure for most countries with well-developed training systems. Person B's mediocrity is quite impressive in the frame of Person A. For another example, I recommend watching "More Than Robots", a documentary that follows multiple teams competing in the FIRST Robotics competition. One of the teams has to build their robot in a school hallway with nothing more advanced than drills and screwdrivers. Another team's workshop has a few million dollars' worth of advanced tools and machinery, plus an contingent of professional engineers to mentor them. The appropriate definitions of "success" for these two teams are radically different.

Many organizations fall for this fallacy. "Why would you ever hire a worse candidate," they might say, Slope, not y-intercept, as just one of many possible and perfectly logical reasons. completely failing to understand the candidates' broader context. In fact, many organizations are actively geared against understanding. They often won't even interview such candidates, let alone hire them. The book "Hidden Figures" and the movie based on it both show visceral depictions of real-world situations like this. Highly, highly recommended.

In Moneyball terms, people that succeed in spite of their circumstances are massively, shockingly undervalued. They've already outpaced their comparable peers β€” just imagine what they could do if for once they got a proper support system that sets them up for success! A related idea is "equality vs equity".

You don't have to look far to find people succeeding in spite of their circumstances. The worse the overall industry does on this axis, the more likely you are to find underrated people in the groups that industry is biased against. You've heard of gender or racial discrimination, but how about: college dropouts, people with disabilities, folks with criminal records? Even people that speak English with a foreign accent get measurably worse outcomes in tech company interviews.

I'm only able to write this today because MIT's admissions system might work similarly to what I've described here. They could have admitted a dozen people who had won better prizes at all the same competitions I did. Instead, they admitted me: a fairly mediocre nobody from a tiny country β€” the big fish from a pond so small that most people can't even find it on the world map.

Going to MIT was like drinking from a firehose: it will knock you over no matter how prepared you thought you were. I was used to being knocked over. So I came back up, again and again. New to me was the number of opportunities available everywhere β€” so, much like Hamilton, I didn't hesitate nor exhibit restraint and instead tried to seize every opportunity like it was my last.

It appears to have worked.


Tech hiring is broken.

Many companies just adopt industry-standard hiring processes and call it a day. But those industry-standard processes lead to the usual industry-standard problems.

Raise your hand if you've heard "we can't find good people" or "we need more people with experience" or "nobody wants to work anymore." Yeah, me too. We have to do better.

If you're a hiring manager, hopefully this post has given you some ideas on how to turn better hiring into a competitive advantage. If you'd like more personalized help with your company's hiring processes, please reach out.

If you're a job-seeker, you've probably already experienced how random and nonsensical the hiring system can be. You are not alone! Just like there's a broad spectrum of candidates, there's also a broad spectrum of companies! The best ones are a lot better than the worst ones, and knowing which is which is key. Ask your friends, your former coworkers, folks you meet at meetups and conferences.

Then, pay it forward.

Thanks to Hayden Stainsby, Saul Pwanson, and Hillel Wayne for feedback on drafts of this post. All mistakes are mine alone.