A million years ago I happened across a blog post called A Love Song About Web Standards. It featured a song called "Hands to Boag", a perfectly reproduced cover of the 80s song "Hands to Heaven", but rewritten to be about web standards and web development and the blog Boag, which is about those things. Even if you have never heard of Boag it's a pretty great cover and should make most web developers smile.
It's pretty good, but even better when you learn that Marcus Lillington, a host of the podcast in question, used to be a member of the band Breathe, who originally sang Hands to Heaven.
Every so often this idea that an 80s superstar is a web developer and people remade his song to be about web development returns to my brain and I go back and find the song and laugh again. But the last time, I discovered bit-rot had set in and the MP3 was no longer playable on their site. This is a tragedy! So I have rescued it and put it here, so you can still enjoy it:
Then, in the spring of 1977, Quasar rolled in the door. Its arrival marked the beginning of the first debate over free speech in cyberspace. The controversy centered on an unusual device made by Quasar Industries and blew up into an argument over using the taxpayer- fundedARPANETto speak, in openly critical terms, about a private company.
The brainchild of Quasar Industries, the device stood five feet four inches and weighed two hundred forty pounds. It was called the Domestic Android robot, a programmable helper that could perform a dozen basic household tasks such as mopping the floor, mowing the lawn, washing dishes, and serving cocktails. It came equipped with a personality and speech, so that it could “interact in any human situation.” It could “teach the kids French” and “continue teaching them, while they sleep.” At the advertised price of $4,000, the thing seemed a steal.
Phil Karlton of Carnegie-Mellon was the first to alert the Msg-Group, on May 26, 1977. His site on theARPANETwas heavily involved in exploring artificial intelligence, speech recognition, and related research problems, so he knew a thing or two about robots. The android and its inventor had attracted a fair amount of national press attention, most of it favorable. Quasar’s sales pitch had also caught the attention ofConsumer Reports,which ran a skeptical item on it in the June issue, just out.
At first Quasar seemed nothing but an amusing diversion from the MsgGroup’s main business. Everyone in the group knew the thing was a hoax, and for a while that seemed enough. But then a sense of civic duty arose. Dave Farber told of being in Boca Raton, Florida, and hearing on the radio that the Dade County police department was considering purchasing a Quasar guard robot for their county jail, for $7,000. In March theBoston Globeran a story quoting MIT’s Marvin Minsky and other skeptical AI experts. But the article took the overall attitude, said a MsgGroup member, that it “just goes to show you, those academicians can’t do anything practical, and all you need is some guy working in the back of a garage to put them to shame.” The saga left a trail of disbelief in the artificial intelligence research community.
Brian Reid and a colleague, Mark Fox, from the Carnegie-Mellon Artificial Intelligence Lab, posted an offbeat report to everyone in the MsgGroup, giving them a personal account of their inspection of the domestic robot, “Sam Strugglegear,” at a large department store in downtown Pittsburgh. People in the research community, knowing of CMU’s pioneering AI work, had been calling the Lab to ask how it was possible for Quasar’s robot to be so much better at speech recognition than anything CMU had produced. Rising to the challenge, a four-member team from CMU had done the fieldwork.
“They found a frightening sight,” reported Reid and Fox. In the men’s department, among the three-piece suits, was a five-feet-two-inch “aerosol can on wheels, talking animatedly” to a crowd. Electric motors and a system of gears moved the device’s arms. The robot seemed conversant on any subject, recognized the physical features of customers, and moved freely in any direction. The crowd was charmed.
But the scientists were skeptical. They looked around for some evidence of a remote controller. “Lo and behold, about ten feet from the robot, standing in the crowd, we found a man in a blue suit with his hand held contemplatively to his mouth like Aristotle contemplating the bust of Homer in the famous Rembrandt painting.” Reid and the others watched for awhile and noticed that whenever the robot was talking, so was the man in the blue suit—muttering into his hand. The man had a wire dangling suspiciously from his waist.
The discussion about the Quasar robot continued on and off for a couple of years until in early 1979, Einar Stefferud, the MsgGroup’s moderator, and Dave Farber, who had been lurking on the sidelines of the commentary, sent a note of caution to the MsgGroup. “We are asking for potential problems,” they warned, “when we criticize the Quasar robot.” Using U.S. Government facilities to cast aspersions on a corporation, they said, could backfire on the ARPA research community. They urged their peers to impose careful self-censorship, to report only facts of technical interest to the community. Not everyone agreed, and with that the MsgGroup got embroiled in a soul-searching exchange.
The country where I was born and grew up still has some terrible, outdated laws against homosexuality. The laws are seldom enforced, but hang over the heads of gay people in T&T, forcing them to be quiet, subjugated, and fearful. They live their lives as second class citizens before the law. It is the reason I can't live in the country I was born in. These laws create misery for tens of thousands of people.
I have been waiting a long time for somebody to step up to the challenge of taking on these cruel and repressive laws, and finally, that's happening:
The brave @trinijayjay is taking the government of Trinidad and Tobago to court to overturn their outdated and cruel laws against gays. Read his story here https://t.co/ZlWQcxEFGR and please do donate to his crowfund to fight the case here https://t.co/e5nH9rQawn— Stephen Fry (@stephenfry) December 12, 2017
Jason Jones, a Trini based in London and an activist for 28 years, filed a legal challenge to these laws in February 2017, and the case will be heard in January of 2018.
The government is defending the law. Jason has received dozens of death threats and has had to hire bodyguards to protect him. But he's sticking to his guns, and his bravery for a cause that is so close to my heart is inspiring.
Jason isn't getting anything out of this case. There's no payout for him if he wins, just the freedom for him and the thousands of other gay Trinidadians to be openly themselves in the country they were born in. His legal team is working for free. Nevertheless, there are legal fees, travel and security expenses to cover. He's raising funds, and I want you to donate to his campaign right now. Over on Twitter, I'm going to be encouraging people to donate by matching funds.
Everyone's favorite sarcastic talking pushpin asked an honest question about the state of the web:
From the outside, front end development in 2017 looks pathologically overcomplicated. Is this a fair perception? If so, why is it happening?— Pinboard (@Pinboard) May 21, 2017
I replied with a tweetstorm. Here it is as a slightly more readable blog post on my ancient, creaky blog.
The replies to Maciej's tweet are interesting to read. They fall roughly into two camps:
As is often the case, both camps are correct! The web is a shitshow of wheel reinvention and bad APIs. It's also a blizzard of innovation.
Expectations for what a web site should be able to do have evolved enormously. Users expect snappy, desktop-like responsiveness and rich presentation in web apps. They also expect those same web apps to work equally well on mobile devices. And they expect these apps to load basically instantly. As Tom Dale says, that's actually a harder problem than desktop or mobile apps face. Users expect to download and install those types of apps before they will run.
Devs must meet these high expectations, but they have no more time and no more co-workers than they did before, and they still have to ship just as fast. To meet this requirement, they are throwing ever larger combinations of frameworks, boilerplate code, tools and build chains at the problem. The result is a lot of complexity and it's frequently frustrating.
Devs aren't adopting all this new tech just because it's new and fun (though it's a bad idea to dismiss fun as a valuable quality in a development tool). They are doing it because they have to in order to survive.
Modern web dev has the complexity of, say, the native mobile ecosystem, but no single vendor or consensus build chain or tools. iOS and Android have compilers and long build steps and dozens of competing frameworks, but nobody complains that these things are unnecessary. But they do for the web, because the web didn't need them before. (And if you're okay with throwing together a simple, 2000s-era web page, they're still not. But few users are happy with those any more.)
Over the next 5 years I expect there will be a lot of consolidation in technologies and in tools. A lot of the stuff web devs are currently constructing using frameworks will be adopted as first-class citizens, built into browsers. Because the web has a lot of inertia, people will keep using these tool chains longer than they need to, much as web devs still use jQuery even though mosts of its API is part of browsers natively now.
jQuery is an instructive example: jQuery was a reaction to a terrible API and a lack of raw functionality in the web at the time. It changed the web for the better, forever, by showing browser makers what devs needed, and how it should work. It was a huge success, and its ultimate success is that it made itself unnecessary.
Webpack, babel, react, and the cambrian explosion going on in that ecosystem will do the same thing again. All of these frameworks and tools are devs experimenting, seeing where they want the web to go.
jQuery was a performance problem at scale, and sometimes over- or mis-applied, or used superfluously by newbies who didn't know there was a simpler way. Big deal.
Modern front-end devs are repeating the same mistakes: these new frameworks often create shocking performance hits. Sometimes we over-use them. Sometime we mis-use them. But the web is evolving, and evolution is by nature slow and messy. And the results are already amazing.
Is modern web development fearsomely, intimidatingly complicated? Yes, and that's a problem. Will we make it simpler? Definitely, but probably not as soon as you'd like. Is all this new complexity worthwhile? Absolutely.
The web's amazing capacity to reinvent itself, to evolve and adapt to new needs is its strength as a platform. Things that don't adapt die or are replaced. Nobody is talking about the death of the web. Nobody is demanding it be replaced. If anything they're pleading for it to slow down a bit, and let them catch up. That's a sign of a healthy platform, an innovative platform. The web was like that in 1996 and it's still like that, and that's amazing.
Nobody but nobody loves the web more than I do. It's my baby. And like a child, it's frustrating to watch it struggle and make mistakes. But it's amazing to watch it grow up.
It's a question on the minds of all right-thinking Americans, and on mine. I don't claim to be a political genius, or that this is the right solution or the only solution. But here's what I've got so far; tell me what you think.
First, to defeat Donald Trump you must make him unpopular. His popularity is what elected him, but more importantly it is what drives him. An unpopular Donald Trump will melt down and quit, humiliated. That's what we want. We need "being the next Donald Trump" to be an ignominious fate. We want Donald to never run again, and we want any Donald-shaped monster in future to be terrified of the possibility.
To work out how to make him unpopular, we must understand what made him popular in the first place. To do this, we must look beyond our liberal peers, with whom he is already maximally unpopular, as widespread demonstrations have indicated.
Here's what Donald Trump supporters believe about him (however incorrectly) that they like:
Anything about economic insecurity and not listening to the concerns of rural voters or the working class is bullshit. Poor people did not vote for Trump (his voters earn above the median wage, unlike Hillary). There are also plenty of rural voters who went for Hillary, and plenty of city dwellers who voted for Trump.
So to defeat Trump, we must make him look highly corrupt, part of the establishment, unwilling or unable to privilege white people over other people, and weak. The first two are easy, the second two more challenging.
It's easy to make Trump look like part of the establishment because he is part of the establishment. He is the damn president. Everything bad that the government does, whether or not he had anything to do with it, can and should be tied to him. Every slip in the economy, every problem with healthcare, every sparrow that falls from a tree should be loudly attributed to Donald's mismanagement. Republicans got really good at this and so should we. We can also point to his appointments of CEOs of Exxon, Goldman Sachs and other very-much-establishment companies to important posts.
Making him look more corrupt than most politicians is trivial because he is shockingly corrupt. His casino deals, his mafia ties, his many bankruptcies, Trump University, and repeatedly welching on debts to contractors establish him easily as a cheat, a liar and a crook. His base seemed to overlook or ignore these things as "tough negotiation" or something but we can keep dredging up more tales of his thievery basically forever.
Making him look like he's not secretly racist is very tricky because he is openly racist. He has repeatedly said he believes his superior genes guarantee his success, and that's before you get to his many obviously racist acts, from refusing to rent houses to black people, to failing to condemn the KKK, to demonizing Mexicans and Muslims (neither of which is a race, but racists aren't very bright).
To make Trump look un-racist will not work. What we can do is make him look powerless to act on that. Here we've already seen the most action: protests on the Muslim ban and swift legal action have halted it and may overturn it entirely. Protests against his border wall will likewise do so, and legal or legislative action should come there too. Making him look powerless to enact racist policy, however, is just part of the bigger play: make him look weak.
Because by far what people responded to in Trump is his strong man persona. He claimed he could do anything, fix anything, build anything, and it would all be great, the best, yuge, people would love it. His supporters bought these empty boasts as promises, so we have to puncture the idea that he can get anything done.
We have to be careful though. If the obstruction appears to come from outside -- from filibusters and other legislative hacks, from well-meaning heroics by democratic appointees, from "the establishment" -- then we bolster his support rather than erode it. Instead it needs to come from within, and here we are aided by Trump's stupidity and incompetence. His failure to negotiate trade deals, his inability to fund the wall, his botched attempt to ban Muslims, his failure to deport illegal immigrants: these are or will soon be his failures, and we can amplify them. This house of cards will collapse on its own, but we need to make sure it falls our way.
The other way to make him not just look weak but really become weaker is to peel off his inner circle one by one. The loathsome, openly racist and anti-semitic Bannon has already overstepped several times, to Trump's displeasure. By amplifying Trump's sense that he is being manipulated and overshadowed, we can use Trump's own ego to get Bannon ejected or diminished.
The repugnant Kellyanne Conway, with her "alternative facts" and imaginary terrorist attacks, is also faring badly in the spotlight. In any other administration her repeated, obvious lies would have already had her fired. In the Trump administration what will get her fired is if news organizations refuse to interview her anymore because her every word is openly mocked. If she doesn't get to speak on television, her power and her value to the administration will fail and she will be discarded after one lie too many. Sean Spicer will suffer a similar fate, perhaps even sooner.
What can we do? We can amplify. Every failure must be trumpeted, every policy overturned, every decision nullified by protest or local action. His inner circle must be hounded until they become political liabilities, leaving Trump isolated and impotent. But be selective: don't amplify things that make liberals angry (you'll exhaust yourself, everything he does makes liberals angry). Amplify things that make him look stupid, make him look inept, make him look corrupt and compromised by establishment ties. And above all, make him look weak. If we can persuade his base to abandon him, he will not last as president.
He mentions, briefly:
But it seems to me this conflates two very different use-cases that we should consider separately:
The generational disconnect I mentioned earlier seems to be coming from the fact that web developers are in two groups, with different "default" ways of thinking about web development. The first group, who turned up in the past 5 or maybe even 10 years, think of it as application development with the web as a medium. The second group, which includes myself, who started 20 years ago think of it as building a set of discrete pages. Obviously, both groups can and do build both types.
As I argue every time I give my Stuff Everybody Knows talk, web development is not a competition between single page web apps and multi-page web sites. Neither is going to "win". There will always be both kinds of web experiences, and what counts as "graceful degradation" is very different depending which one you're building.
Nobody's arguing that graceful degradation is a bad policy, merely what it looks like, and I think these widely diverged use-cases is the source of the disagreement. In fact, as I mentioned on Twitter early this month, web app development and web site development are so different now that they probably shouldn't be called the same thing anymore. Both types of developers are web developers, but you should probably specify which flavor you're talking about. Web app development and web site development (pick your own terminology if you don't like mine, just make it unambiguous) are so different now that rules from one flavor almost never apply to the other.
The tragedy of all online community spaces is that the goals of "inclusive" and "safe" are, at the extreme, mutually exclusive goals.— Laurie Voss (@seldo) July 13, 2015
If you keep including people you will eventually end up with people in the same space who cannot stand each other and will not get along.— Laurie Voss (@seldo) July 13, 2015
At some point you have to exclude someone. You get to pick if it's the people feeling unsafe, or the people making them feel unsafe.— Laurie Voss (@seldo) July 13, 2015
And *that's not always an obvious choice*. Somebody's "reasonable topic of discussion" is *always*, eventually, somebody's threat trigger.— Laurie Voss (@seldo) July 13, 2015
I've run online communities for 20 years and I have learned that there is not even an approximation of a consensus of "reasonable".— Laurie Voss (@seldo) July 13, 2015
This is why online communities fragment. Let them do it. It's the only viable solution to the existence of mutually incompatible people.— Laurie Voss (@seldo) July 13, 2015
Define your space clearly. Let in anyone who shares your reality. Be honest that people who don't share it will be excluded. Say why.— Laurie Voss (@seldo) July 13, 2015
Don't wring your hands about free speech. You are under no obligation to let people say things you hate. They can go elsewhere, and will.— Laurie Voss (@seldo) July 13, 2015
[Disclaimer: I am writing this from my perspective as npm's CTO, but purely in a personal capacity. It has not been reviewed or approved by anyone at the company, and any questions or complaints about it should be directed at me.]
At npm, we care a lot about workplace diversity.
This statement by itself distinguishes us in no way from the majority of companies, who will all say, if asked, that they value diversity. Of course they do! "Diversity" sounds like one of those nice, cheap, HR sorts of words, like "empowerment" and "transparency", that you can put into your mission statement and be so meaningless as to require no effort whatsoever on your part to live up to. Just another buzzword. The actual level of commitment to diversity, and even the level of understanding what it means to have and support a diverse workplace, vary enormously from company to company.
We started npm, Inc. back in January 2014, and over the last 14 months I feel like I have come a long way as a manager of people and learned a great deal about what it means to really, truly value and support diversity. When I learn things I like to write about them, so that's part of my motivation for this. Another, bigger part of my motivation is intense, unbearable impostor syndrome about my own, and by extension npm's, actual level of success at doing so.
This started when I wrote a blog post comparing diversity at major tech companies, then seriously escalated when I wrote a half-joking rhetorical tweet about a Bechdel test for tech (which, you're right, Ryan, should totally have been called the Techdel test:
Does your project pass the Bechdel test? To pass, a function written by a woman dev must call a function written by another woman dev.— Laurie Voss (@seldo) February 27, 2015
This then got picked up by the excellent people at 18F, who used it to kick off a much more serious and useful conversation about gender diversity at their organization, and from there to diversity in general. The original tweet has been remarkably long-lived and 18F's post has been picked up by dozens of other sources. It has been extremely gratifying to see an offhand remark of mine, mostly via 18F's amplification, spur so many interesting and useful conversations, but it has also made me feel like a huge fraud.
Here's why: npm has, at present, exactly 11 employees (though we are hiring a bunch more right now). The three founders are all white men (though we managed some diversity in sexuality, having one straight, one gay and one bisexual founder). Of the 8 non-founders, all of whom are engineers of various kinds, we have four women and four men, all but one of whom identify as white, with some additional variation in the LGBT spectrum. This is... fine. It's not great. It's better than a lot of places. It could be much better. It's also far, far too small to be statistically meaningful, so as we grow we could either get much better or significantly worse. The best I can say is that we're doing okay so far, and will continue to try to improve. Hiring diversely is hard, and a great deal has been written about it, and I'm not going to write about it now.
But hiring diversely is merely the first step. You can't just hire a diverse group and then employ standard Silicon Valley workplace culture and expect things to go well. Once you get people in the door you have to make sure the culture values them and helps them perform at their best. And this is another reason why I have been so uncomfortable receiving attention for our own diversity, because in this area we have been even less successful.
Of our eight employees, over 14 months, people have had big enough problems with the workplace environment and their job quality to raise those concerns to their manager (me, in nearly every case) a total of about 20 times (we keep records of the individual meetings, but I haven't collected them for exact stats). From my experience of previous companies, that's actually not bad -- people often run into things that make them unhappy at work, especially at startups where the situation changes rapidly. But what is bad is that of those reports, more than three-quarters were raised by the women.
These problems varied in scope. Some were minor -- we had problems with over-talking, especially during ad-hoc meetings. We were unnecessarily negative in our discussions of third parties and other technologies. A couple of times, I gave credit for a piece of work to a man who worked on a project instead of the woman who actually did the work until I was corrected. More seriously, I gave ineffective feedback in a way that was distinctly gendered. Various members of the team fell victim to gendered expectations on a number of occasions. On two occasions I really majorly fucked up, totally misunderstanding a team member's needs and expectations, making them miserable entirely by accident. Not all of these problems were gender-related, but obviously since women experienced the majority of them, gender bias was at work.
The best, in fact the only, thing that I can say in our defense is: we give a shit. We really do. When these things were brought to our attention, we took them seriously. We made immediate changes. Sometimes they worked and the problem was resolved or at least improved. On some we had to try a couple of times before we found something that worked. On some of them we still haven't found a solution. But we give a shit. We are trying.
Really early on, we talked about what npm's values are, and one of the clearest summaries of them turned up in a tiny paragraph of text that Isaac churned out for our jobs page. It's so good that it has been almost unchanged in 14 months:
npm is not a typical product, and we are not a typical early-stage “work hard/play hard” startup. We are responsible adults with diverse backgrounds and interests, who take our careers and our lives seriously. We believe that the best way to iterate towards success is by taking care of ourselves, our families, our users, and one another. We aim for a sustainable approach to work and life, because that is the best way to maximize long-term speed, while retaining clarity of vision. Compassion is our strategy.
The way you can tell what a company's values are -- as opposed to what they say they are, which are universally the meaningless platitudes I mentioned at the beginning -- is by their actions. In particular, you can tell what a company believes is really important by what it will give up, or pay, to get that thing. At npm we have made real, meaningful sacrifices in terms of speed of development and cash outlay, to ensure that our team works sensible hours, and isn't woken up in the middle of the night for operational issues. We have also made real, tangible sacrifices in speed of hiring to ensure that our applicant pool is diverse, and our interviews as fair as we can possibly make them. We didn't decide things in favor of happiness and diversity vs. cash every single time, but we did it often enough to hurt, and to be sure that yes, we really do value these things enough to bear that hurt. Because we give a shit.
And that's really all you can do. Detecting and compensating for bias is mind-breakingly difficult. You can be totally conscious of your bias and yet still make biased decisions even though you're actively trying to avoid doing so. You can put processes in place to promote fairness but the design of the processes themselves can and will be biased. You can track statistics and set goals but that doesn't make them happen. You can try to cast a wide net for hiring but job postings are more likely to spread via social connections, which means your friends, i.e. people who are already very similar to you. That's not to say you shouldn't try to correct for your bias, and make goals, and put processes in place, and hire widely. of course you should. But it will never be enough. It is a morass. Once you notice bias you suddenly see it everywhere. I spend an inordinate amount of time on my morning commute considering the gender politics of who gets out of my way.
Oh, and what about the Techdel test? Well, until very recently, npm didn't even pass that. Our four women devs are all on different teams (www, registry, cli, and dev relations). While they all lay down a great deal of high-quality code, their functions rarely call each other directly. On our website, Raquel's code now calls a caching library written by CJ, so we squeak by. I'm not beating myself up over this, though. The Techdel test was a rhetorical joke intended to inspire a conversation, not be a genuine measure of quality of participation, and while npm's gender diversity isn't perfect, we are well above the minimum bar that it was the original Bechdel test's aim to set.
Ultimately, npm is a tiny part of the overall picture. Me giving a shit about hiring diversely and working diversely is not going to change Silicon Valley, especially since I get it wrong half the time even though I'm trying really, really hard. But I care, and I really honestly try to do better every day. It's not good enough, but it's not bad, and that's better than most.
You are bad at giving technical interviews. Yes, you. You're looking for the wrong skills, hiring the wrong people, and actively screwing yourself and your company. Without changing anything about your applicant pool, you can hire different people and your company will do better and you will enjoy your job more.
I realize these are bold claims. In the ten years since I became senior enough to be asked to interview people, I have conducted a great number of technical interviews, been part of a lot of teams at companies big and small, and watched the effect that different types of hires have had on those companies. I'm not claiming to be perfect at hiring -- at various points, I have done nearly all of the things wrong that I'm about to tell you not to do. But here's what I've learned so far.
The primary mistake that people make when interviewing is over-valuing present skills and under-valuing future growth. Don't hire people for what they already know; the pool of people who do exactly the thing you need them to do is much, much smaller than the pool of people who are smart enough to be good at that job.
But even worse is the way we try to determine whether people have these skills. People ask questions in interviews about obscure syntactical features of programming languages, or details of popular APIs. The famous fizzbuzz test simply asks "are you aware of the modulo operator?" If the answer is "no" then they are probably a pretty weak candidate, but it provides exactly 1 bit of data. Yet people will spend twenty minutes on it in an interview, a huge waste of limited time.
I used to ask people to write code in interviews. This is terrible. Writing code on a whiteboard is an experience so far removed from the real practice of writing code as to be no predictor. Even writing code on a computer, as part of a pair for instance, tests for the wrong ability -- you are asking them to write code under time pressure, with somebody watching. Some of the best engineers I know would melt under those conditions. And if your belief is that writing code under intense time pressure is part of your job, then you should examine whether that's a problem your company has.
Whiteboard and coding interviews also routinely ask people to re-implement some common solution or low-level data structure. This is the opposite of good engineering. A good engineer will try to maximize productivity by using libraries to solve all but the most novel problems. It's also a poor test: how do you know if somebody is solving the problem or merely remembering somebody else's solution? There is no value to memorizing the details of algorithms you can google in 15 seconds.
Some people are impressed by academic credentials. Having gone to a good college, or having gone to college at all, are not in my experience good predictors of ability as an engineer. Having a PhD in a relevant field is interesting but also an unreliable predictor: engineers write code and ship software; academics prove theories and write proofs of concept. Somebody smart might be able to do both but it's by no means a given, or even very strongly correlated.
People also over-value brand names on resumes. Don't hire somebody because they worked at a hot company, or a famous one, especially not if that company is big. Variation across teams in big companies is enormous. Just because a company was successful doesn't mean your candidate had anything to do with that. If you are familiar enough with another company's hiring process that you can vouch for it as a good selector of qualified people, you might use that to bump them to the front of an applicant queue, but beyond that, go with what's in front of you.
And finally, never hire your family and if you can avoid it, don't hire your friends either. Existing relationships create bias and implicit power structures, webs of obligation and loyalty that are at odds with what is best for your company. You will either compromise your friendship or your company, and rather than being forced to pick one or the other, just avoid the conflict entirely.
Your first stage of interviewing should be attempting to answer two questions:
Syntax and API questions are aimed at finding relevant experience but they are bad ways of doing so. Instead, talk about the technology they're going to be working with. Find out how much they know about it. You're not looking to hire or pass on the basis of any individual fact. If they are weak on the skills they need for the job, then find a topic they know a lot about instead, and get them to talk about it, if necessary explaining it to you. You are looking for grasp of complex topics and the ability to clearly communicate about them, which are the two jobs of the working engineer.
Much more important than what they know is how they learn it, and how quickly. You are looking for somebody with a track record of learning new skills and applying them successfully. Talk about their career path, and look for evidence of increasing responsibility (which is related to, but not the same as, seniority). Remember that anybody you hire will expect raises every year: somebody who isn't getting better all the time is going to become worse and worse value unless their skills increase in value, too.
Joel Spolsky's classic essay The Guerilla Guide to Interviewing (and the book that followed it, Smart and Gets Things Done) are some of the smartest things that have ever been written about technical hiring. Smartness is hard to judge, and some of the techniques I'm talking about here should help. But "gets things done" is equally important. Have they shipped real software?
Joel and I don't agree on everything, though. I don't think live coding exercises are particularly valuable. Joel is (or was) also pretty big on understanding pointer math, which is an interesting "can grasp a complex topic" question but likewise outside the experience of many excellent engineers, so while it can be a useful thing to try talking about, it shouldn't be an acid test.
As I mentioned, the two jobs of an engineer are to understand complex concepts, and then communicate them clearly. Somebody who can do just one or the other may have a brilliant career in some other field, but is going to be an inferior engineer. The best programmer in the world can develop incredibly efficient algorithms in record time, but the job of an engineer is to work with a team to achieve something larger, and if you are unwilling or unable to spend time communicating with your colleagues you're only doing half of your job.
When interviewing I always attempt to find some area of expertise where I definitely know more than my subject. This is not to prove I'm smarter -- see below -- but because it's important to see how somebody reacts when they find themselves out of their technical depth.
The weakest candidates will try to waffle or make wild guesses. This is a terrible sign, firstly because it never works, and secondly because they thought that it would. In Dunning Kruger terms they are in the bottom quartile, unable to accurately judge their own lack of knowledge. It also means they will try to do this in other situations.
Strong candidates say "I don't know" as soon as they hit their limit, and may start asking questions. The very strongest candidates say "but if I had to guess" and then attempt to extrapolate. Those are great because it shows intellectual honesty and a strong desire to figure things out.
As I said before, it's a good idea to find an area where you know more than your interview subject. But this is not to prove to them that you're smarter or better: it's to explore the extents of their expertise, to get a sense of the breadth and depth of their knowledge. You will bump into the edges or touch bottom, and that's the point. When you do so it doesn't mean they've failed.
It's important that they're aware of this contract, too. You want your interviewee to be relaxed and comfortable, because that is the state they'll be in when they're doing their job (if not, your company is awful, please quit). Answers you get from candidates who are stressed or panicky are basically useless. This is true even if they're good answers, because they're not representative answers. Stress and panic are not sustainable states, so you risk hiring someone who only performs when pressured to do so.
If your candidate has no relevant prior experience, your only option is a more traditional technical interview. This is true of both very junior candidates, and also more experienced people switching from other careers.
Somebody who has just completed a training course, no matter how intensive or well-regarded, does not know how to be an engineer. They may know how to code, but that's only half the job. Somebody fresh out of college may not even really know how to code beyond academic puzzle-solutions. In my experience, if someone has been coding professionally for less than a year, there's not really been enough time to know if they're good at it.
Fresh-out-of-college and other junior types are also not going to know anything about how to interact professionally. Not only does this make interviewing them trickier, it's also a terrifying responsibility: if you hire them, the culture and working practices of your company will be what they think of as "normal" forever.
The other exception to my rules is if you work at a company large enough that engineers can become deeply specialized. When that happens, you may in fact need the genius programmer who isn't very good at explaining what they're doing. If you're big enough, you can hire a manager whose full-time job is to communicate with that person and then translate back and forth between them and the rest of the company. This works really well but is expensive, so it's not something startups can really afford to do. Past your first 50 engineers, you might consider it.
When you're sure your candidate is good enough to do the job, you have another question to answer: do I want to work with this person? There are no specific questions to ask to get this answer; it's more about how they answer the other questions. This makes it a personality test, and that makes it very, very dangerous territory. Personality is subjective, and that means you are inviting bias into the equation. Personal bias, implicit bias, unconscious bias.
The terrifying possibility of turning away a great candidate because you are biased towards them in some way you don't even know about is why people think giving pure, right-or-wrong technical questions are better. They're not, they're just easier. And they do nothing to protect against bias: when there are 50 syntax questions you ask, it is easy to give hints and passes to the candidates you implicitly prefer and pretend that they were just better. I've caught myself doing this. There is no simple way around this: you have to be aware of your biases, constantly conscious of them, and correct for them, or you will screw your company by hiring inferior people.
The most common way I see startups get the "do I want to work with them?" question wrong is by confusing that question with "do I want to be friends with this person?"
Get that assumption out of your head. Those two are not the same. You can have brilliant, productive professional interactions with someone with whom you have absolutely nothing in common with on a personal level, and that's fine. Your company does not need to "feel like a family". It's sure as hell not your frat house. You are not picking a drinking buddy (and as an aside, if your company regards drinking as a big part of its culture you probably have deeper problems).
From day one at npm Inc we implemented our No Assholes policy, and I was pleased to read recently that Polyvore (who seem to do brilliantly at maintaining a diverse engineering team) have pretty much the same policy. Avoid the "genius assholes", avoid the bitter and cynical, the bullies, the snobs. Don't work with somebody who is going to be mean, unpleasant, or demeaning to their co-workers. There is no level of brilliance and productivity that can compensate for poisoning the morale of your team, and once a team culture is broken it is very hard to fix. Hiring these people, even to get you through a crunch, is not worth what it costs. And if you hire one by mistake, fire them fast, and without hesitation.
The easiest way to spot that you are hiring a jerk is the phrase "hire, but not for this team". That means "this person has skills, but I don't want to work with them directly". If you don't, nobody else will, so don't inflict crappy people on other teams.
But in general jerks are easy to spot. If somebody has a personality flaw so strong and baked-in they can't keep it in check for a couple of hours while being interviewed, it is going to be a huge problem in the regular work environment. Arrogance, rudeness, inattention to detail -- these things turn up quickly, and if you spot them, trust your instinct to avoid them.
I have never heard a definition of "team fit" that didn't end up sounding like "let our bias run free". Phrases like "looks like they belong here" are terrifying. More insidious are complaints like "doesn't like the same social activities we do". Grow up. Your office is not your frat house, and socializing with your co-workers outside of work is not some crucial test. There is no requirement that you like someone socially as long as you want to work with them.
And while I'm at it, as an introvert and lifelong non-drinker, may I make a personal plea that you stop incorporating social events into your hiring process? Professional interactions and social ones are not the same. Some people suck at small talk, and are not comfortable at bars. Remember the part about making sure your subject is relaxed and comfortable? It's about them being comfortable, not you.
How do you reconcile the "don't hire for team fit" rule with the "no jerks" policy and the "somebody you want to work with" requirement? The distinction is subtle, but important: somebody who is good for your team is not necessarily somebody you want to be friends with. It's tempting to look for both, but it's the wrong metric for the success of your company and is ultimately unsustainable.
I'm not going to make an argument that "diversity is intrinsically good" for some social purpose. That's a stupid way of looking at it. Lack of diversity is obviously, mathematically, bad for your company. Instead of hiring for "best for the job" you have accidentally hired for "looks like me". There is no chance that all the best programmers in the world look the same, so a lack of diversity means only bad things. It means "this team sucks at hiring", it means "management and HR are not strong or competent enough to spot and correct this", and worst of all it means "this team is not the best people available".
Here I must hand-wave. npm is incredibly lucky on the talent front: people love node and npm, and we get dozens of qualified candidates just by posting a vacancy. My previous startup, awe.sm, was not nearly so popular, but we managed to find good people anyway. It's a matter of taking a long time, and trying every channel: we got great candidates via posts to the Who's Hiring post on Hacker News, via our blog, and once from some coverage on TechCrunch.
The important thing to remember is that hiring a bad person is more expensive and wastes more time than waiting for a good person. It's tempting to say "at this point, anybody would do" but that's never, ever true. The wrong person will not merely fail to do their job, they will make everybody slower at theirs, and unhappy to boot. Don't hire if you're not sure about somebody, and if you hire somebody who's no good, give them as much support and direction as you can afford to get them to turn around, but if you don't see any improvement be ruthless in letting them go.
This is why you've been giving bad technical interviews all this time: bad interviews are easier to give. They require less thought and creativity and effort on your part. These techniques are tricky to define and tough to follow. But that's what hiring is like. It's really hard, and it always takes much longer than you hope it will. The rules are fuzzy, and there are no acid tests that can be applied. But the payoff to trying harder is a stronger company, better people, a better product, and a happier working life for everyone on the team. Making those things happen is, as a hiring manager, your only job.
Update 2014-07-23: added Twitter and Salesforce to the spreadsheet after they published their numbers.
This is unusual first because this is data they previously kept secret, and also because of the striking uniformity of the reports -- they all chose to report in the same categories and even gave those categories exactly the same names. I'm not sure how that happened -- maybe they conferred, maybe there's a third party driving all three of them to do it -- but whatever happened, it means it's possible to do an apples-to-apples comparison of these three, which collectively employ around 60,000 people (Google is by far the largest company).
First up, gender breakdown across US employees:
Unsurprisingly given what we hear about tech, men are over-represented. The only other interesting thing is that Yahoo is the only company to acknowledge a non-binary gender option (though they include "undisclosed" in that group, so it's not clear how many employees are taking advantage of that). But interestingly, all three companies chose to further break down their stats by "technical" and "non-technical" positions. None disclosed how they made that classification, but the results are strikingly similar. Here's non-technical staff:
Not bad at all. But here's technical staff:
Boom. The problem with gender diversity isn't in "Silicon Valley companies" it's in engineering. In case you needed the point rammed home any harder, this is 100% tech's problem. The companies are doing generally okay, but the engineering organizations are ridiculous, averaging only 16% women.
The racial data has fewer surprises. Here's all US employees again:
Again, I had to make no adjustments at all to this data. All three used exactly the same names for categories. Is there some national standard for reporting this data I'm not aware of, or is there some coordinated campaign? Anyway, these companies are hella white, and basically everybody who isn't white is asian. The breakdown amongst non-technical staff is pretty much identical across all three companies:
With the one surprise being in the data on technical staff:
Yahoo's engineering staff is majority asian, by a huge margin. I triple-checked my data to make sure I wasn't getting this wrong, and that this is only about US employees (Yahoo India is a substantial organization). But no. For some reason Yahoo employs way more asians compared to the other companies, and all the "extra" asians are engineers. As an ex-Yahoo myself I can't say I ever noted this myself, but there it is.
What does this say about our industry? Nothing we didn't know before: tech companies are
very mostly white and very male, and engineering organizations embarrassingly so. Engineering orgs are also disproportionately asian (the Bay Area is 23% asian, and non-technical staff match that figure). But here's some nice, solid, clean data, all released in the same six-week period, to back that up.
If you want the actual numbers, you can save some typing by cloning this spreadsheet, which also has the charts from this post.
 Thanks to Tom Coates for suggesting I clarify this.