The High Cost of Fitting In

They say authenticity is the key to success, and once you can fake that, you’ve got it made. My experience says it’s not quite so simple.

Originally published on NewCo Shift

When I was 23, I was hired as a system administrator for the first time. I joined BlueStar Communications, which was a young but well-funded company stupid enough to take on the incumbent telecom carriers. Their CEO was a maverick, especially in staid telecom in Nashville, Tennessee. He was bringing always-on internet to small businesses in the southeast (yes, there was a time when this innovative), and blended in about as well as a hockey player in a three piece suit. I was excited to work with someone who I could identify with, and learn from.

He was fired the week I started.

Like the founder of BlueStar, I’d had my own struggles with long tenures. I was fired from a cabinet company after only a week. I lasted a full three month contract at Adidas before having it ended the day I left to visit family. I also lasted only three months in QA and Mac administration jobs.

For all of these firings — except maybe the cabinet shop, which bored me to tears — I wasn’t bad at the work, I just didn’t fit in. You could say I wasn’t really housebroken, that I didn’t know the rules of how people acted in American corporate environments.

All of my prior work experience was remodeling houses with my family, after growing up on a commune. I had no idea what made people normal, I just knew I was missing it.

These failures inspired me to work harder at being worth keeping around, but in parallel I started learning to look like I knew what the rules were and was at least trying to follow them. For someone who only a few years earlier walked around campus with knee-high boots, a spiked leather jacket and a mohawk, this was no mean feat.

This experience with firings was a huge influence when I started Puppet in 2005, six years after I met the CEO of BlueStar. I bootstrapped the company for more than four years, partially because I failed to find an investor I trusted to keep me in the CEO role. The first term sheet I ever received was on the condition that I accept a friend of the investor’s as CEO. (I declined.)

As I grew the team, things got more difficult. One of the first people I hired immediately declared his greater fitness for the CEO role, with zero relevant experience, and tried to convince others to oust me from the company I’d built and they’d just joined.

Yes, I was paranoid, but they really were out to get me.

From my first hire through raising $87m in funding and growing to nearly 500 employees, I could never get comfortable. Everyone I worked with reminded me — unintentionally — that I didn’t fit in, that I didn’t behave as they expected. As I grew into my role, I excelled in areas, but continued stepping in holes that everyone else could see.

The suspicion that I wasn’t faking things well enough was confirmed as I was raising a later round of funding.

Before a pitch meeting, an investor said to me “Now try to be more like a Valley guy, not so much a Portland guy.”

Infuriatingly, I knew what he meant, but also that I’d never be able to pinpoint what I was doing wrong. I worked every day on my “Valley guy” pantomime, from the clothes to the books to the words. This pointed statement told me in stark terms that my efforts were obvious failures to even the casual observer.

Knowing the world saw me as an imposter caused me to hold back. I don’t mean I had imposter syndrome; I suffered from it like most high performers do, but that’s not what this was. The world around me constantly pushed back against what made me “me”, making me worse at just about everything.

I had put myself in a box. I wasn’t even willing to consider ideas that I didn’t think the people around me would accept. I was brave, within that window. I was daring, but not too much. I could do anything I wanted, as long I still kind of looked the part. This box excluded many great options, and notably, excluded a lot of what I most wanted. My weirdness isn’t skin-deep, and a lot of what I wanted just didn’t fit, so I tried to do something that did. Thankfully a lot of it worked out, but I think it could have better, and I know it would have been more pleasant, if I had been more brave, more willing to own my lack of belonging.

It’s worth noting, this was all as someone who did theoretically look the part. I’m a medium-sized white male with a degree from a great school.

I can’t imagine how much worse it would have gone for someone who literally looked different — wrong skin color, wrong gender, wrong accent, disabled, too short, etc. Maybe that was my real problem — people let me in the door thinking I was like everyone else, and only once they started talking to me did they realize how weird I was.

Finally, after almost ten years of running Puppet, I found a way to escape this box I had put myself in. I would quit.

It’s not fair to say this was the only driver for my decision, or even that I was thinking of it this way at the time. What can’t be denied, though, is how much it changed me. I lost my fear of being fired for not fitting in, because I was working to leave anyway.

I couldn’t see the box when I was in it, but when freed, unavailable actions suddenly became doable. I could trust myself for the first time since that first hire, so my cost of decision-making plummeted. I didn’t need to look to society as some sort of arbiter of what’s reasonable.

I had been preventing myself from using my now-highly trained instincts, which reduced me to tackling easy problems or making slow, bad decisions. Or sitting there and doing nothing, which is generally an even worse decision.

Outside the box, my inductive reasoning center could operate without all the second-guessing. I was able to hire a product leader based on instinctive conviction that we were aligned on how to work. I made an incredibly tough call on hiring for Business Development, by following my thread of fear that maybe I was being pulled toward too easy of an answer elsewhere. Most importantly to me, though, I was able to develop and begin rolling out what I think is a truly great product strategy.

I did some of the best work of my life.

This experience has an interestingly conflicting lesson.

On the one hand, the cost of trying to fit in is often too high. No matter how much you want it, you might have to choose between failing at what you want and succeeding at what you can authentically do. If you’re building a team, the choice may come down to those who are great at the job and those you can work with.

On the other hand, I somehow fooled people into thinking I was normal (well, normal enough) for long enough to become a successful CEO in a field where I seemed like an alien to everyone involved. That pantomime was critical in developing the instincts I was able to apply so well as my tenure wound down, and now I have opportunities I never could have dreamed of.

I think the duality of this lesson is important in the conversation around diversity. Puppet couldn’t have existed without some tolerance for my weirdness, but it was also much harder because of it.

I’ll never know if getting out of that box earlier would have caused me to do even better as CEO, gotten me fired ignominiously years earlier, or even maybe caused the company to fail early on. What I do know is that I was deeply hurt by not facing and acknowledging my fear of being fired.

Fear is healthy and reasonable. But you have to pursue it, nail it. Understand it. Not run from it.

I am privileged to have no idea what is in store for me, and no fear at the prospect. I feel no need to fit in anymore, both because I have nothing to prove and because the cost of not fitting in is now one I can afford to pay. If anything, I’m now considered more valuable because I don’t fit the mold.

The lack of pressure to conform brings incredible freedom. Freedom that everyone deserves.

How Can I Help?

I am not a technologist. This surprises many, including a CEO I was on the phone with recently. I explained that I had no pet software projects I was working on at home, and thus couldn’t demo her software. She paused for a second, like, “Uh, why are we on the phone, then?”

It’s true that I have worked on tech since graduating from college, and that I wrote Puppet essentially alone while I bootstrapped the company for years by myself. I enjoyed the work, but those were all a means to an end, not the goal. This became more and more clear to me as I hired large teams who really were technologists. I was able to do the work, but they loved it. I naturally fell into different, complementary areas.

So no, I can’t really help your company in sorting out its software stack. Or rather, I could, but you really shouldn’t want my help there. There are better people. Far better. People have found my advice really helpful in the past, but not in this area.

Strategy is where I’ve had the biggest effect as an advisor. You are already deeply committed to your goals — you don’t need my help figuring out what to do. You are just as committed to how you’re going to achieve them, but probably haven’t spent as much energy thinking about it and expressing it. This ‘how’ is your strategy, and key aspects are decided early on, whether you mean to or not.

Do you want a big field sales force, or a self-service model? Either way, why? How does that choice affect your product price point and service attach rate? There isn’t necessarily a right or wrong answer, but a choice will be made, and it has massive consequences on the life of your company. My great ability is pestering you with questions until you’re forced to put your opinions on the table and really examine them. As a leader, your job isn’t just to be opinionated — it’s to be able to usefully express that opinion to your team.

Product is the second major area I will push you. Again, this isn’t about the tech, or the code. I don’t care how it’s built. The first step is being clear about what problem you want users to hire you for. I bet you have a decent grasp of this, but you have to go down a layer into which users you’re going to start with, how you’re going to parlay them into a larger group, and how all of that relates to adoption within a single organization and across a market. The path of a product’s adoption is as critical to plan out as the features you build.

All of that ties into how you price. How does it drive user behavior? What do you want to incentivize through low or free pricing, and what must you charge for to make your business work? How does charging per seat vs consumption vs features change their behavior and affect your business?

All of this must come together into a coherent system that pushes you, your team, your customers, and the market to focus on the right problems at the right time. You should seek my help in seeing the whole system, and especially the gaps in it. I hate software, but oh boy, do I love systems. My brain is so optimized for managing, storing, and assessing systems that I lose nouns constantly. It’s worth it, for me and for you.

I can also help you.

You’re not a coincidence. You have to understand, it’s not an accident that you’re here. Even if the only thing that makes you special is that you were the first one to raise your hand… it’s been a few years now. Because of that one little action, you’re different than everyone else. It’s up to you to demonstrate whether that difference is good, or useful, but it’s definitely there.

I don’t mean to say that you’re better, or that only certain people can be entrepreneurs. History shows the exact opposite, and I’m a huge believer in empowering ever more. What I mean is, the mere act of taking the step permanently changed you. One of the hardest acts for most founders, especially those from underrepresented groups, is believing that they belong, that they deserve to be out front. I can help you see how just sitting in the seat has led you to be a different person than you were before, led you to special insight and special opportunity.

It’s up to you, now, to make the most of the opportunity, to believe in it and to deliver on it. You have to learn how to extract that difference, to bottle it, to share it. And when to dump it down the sink.

Founders are so full of dreams that they have a hard time letting go. “It’s true we can’t do this today, but I’m going to keep talking about it in hopes we can do it tomorrow.” Your business is on death’s door and the wrong success gets you all fired, but sure, go ahead and distract your team with something you know you can’t and shouldn’t build, and that your customers would never buy.

Everyone knows founders have to make hard decisions, but most don’t seem to realize the hardest ones are about their own dreams. To build something great, you have to give up on other dreams. You can’t build it all at once. You can still hold it, treasure it. But you don’t get to talk about it. You can’t distract people with it.

You haven’t earned it yet. When your company is a massive success, and throwing off more cash than you know what to do with, that’s when you pull out your other great ideas and turn your success into a platform for experimentation. Until then, you have to focus. Let go.

Beyond all that, I enjoy working through demos and user experiences, helping people see your work through new but educated eyes, asking a thousand questions that you might not have answers to. This teaches us both a lot about you, your product, and your company. The differences between the easy and hard answers teach you a lot, too.

What I don’t like to do is tell people what to do. At most, I will share frameworks I’ve used for decision-making in the past and recommend some of them for you, but preferably, I will focus on pulling from you what you really believe, and then make you really confront it. It’s not about me. I can’t live your life. I don’t know your customers. I can’t run your company.

But maybe, with the right prompting, I can help you look at it in a new light, help you make the right decisions faster, and help you avoid some of the worst parts of this insane decision you’ve made.

It Shouldn’t Get Easier

Anderson’s knife can cut anything, taking a chunk from everything in the land.

Master Terrence’s strokes remove less with each cut.

Greg LeMond once said, “It never gets easier, you just go faster.” This quote has been a rosary for me, a source of contemplation and meditation over the years. I think of it every time a new problem reveals itself as an echo of something I thought I already solved.

When I started Puppet, everyone I worked with stressed the need for me to recognize my position as founder and CEO, to bring people with me. The summer before I stepped down, more than a decade into practicing this skill, it still showed up in every coaching session. Not because I haven’t improved — but because it is a life skill that I can improve at every year and still die with more work in front of me than behind.

I found it incredibly hard to hire those first few people. I second-guessed myself, was slow, looked like a fool, felt an even bigger one, and finally made bets based on too little information. When I rebuilt the executive team in my last year, I second guessed myself, went too slowly, made what looked like basic mistakes, and felt incompetent the whole time.

This isn’t a coincidence. It’s not a sign of my incompetence. It’s the exact opposite: It shows that I never let things get easier, instead I kept my intensity up and always focused on going faster.

LeMond knew how to win. You train, you work, you focus, and all that effort delivers leverage. What you did yesterday when giving 100%, you can do today giving only 97%. What do you do with that 3%?

If you want to win, you reinvest it. In what? Counter-intuitively, exactly what got you that leverage in the first place.

For each and every one of us, there are two kinds of skills: Those it’s worth devoting our lives to, and those it’s not. A given pursuit can be less important because it doesn’t matter to you, because you’ll never be good enough at it, or because you just don’t like it. Those that matter, though, are a perfect intersection of your love, your abilities, and your values. They will reward any amount of investment by making you better at what you care most about, and are best at.

You have to love it because you really can’t devote the time and energy needed to dominate unless you like the work. You need at least some ability. You don’t need to start with a natural talent, but you are most likely to be rewarded for investing in areas that come easier than when you’re starting at the bottom. And your investments have to match your values. Some people care most about skills that earn them money, others about having an impact on people’s lives, and yet others want to build. You have to believe that what you’re investing in will help you spiritually, not just materially. It’s the only way you can convince yourself to work as hard as you need to.

Yes, there absolutely are things you will never be good at that you have to invest in. When I started Puppet, I was an outright liability in some areas, such as business operations. I had to get better at those. But I was never confused into thinking I would be great at them. That’s what team building is for.

Given two skills, one where you’re 8/10 and the other where you’re 3/10, where do you invest? Some might recommend the skill you suck at.

Not me. If that skill mattered, you would never have gotten hired in the first place. The reason you have a job is because of your 8/10 skill. Get 10% better at your weakness, and wow, you’re at 3.3/10. Big whoop. Get 10% better at your strength? You’re at 8.8/10. That’s a huge difference.

But getting 10% better in your area of expertise is fantastically difficult. It’s your life’s work.

I am suspicious of people who say the hard things are easy. What I hear is not that it’s easy, but that they’re not trying very hard. Or they’re too embarrassed to be honest.

Greg LeMond was the fastest cyclist in the world, but never stopped trying to ride faster.

Miyamoto Musashi won more than 200 individual duels with a sword, but never stopped trying to cut faster.

Excellence requires perpetual intensity. You should be confident enough in your strengths to admit that it’s hard. It should be hard. It’s the only way to get better.

Learning to Write

Reese’s keyboard produces truth of complexity and beauty, admired from a distance by all.

With a violent strike of Master Aaliyah’s pen, Jorge is enlightened.

I set out in January to study the realms of finance, software, and my own desire, but found myself adrift with no laboratory for experimentation. Programming was my testing ground for the hypotheses that led to Puppet, but my new questions cannot be answered in silicon. Clumsy studies provided two conclusions: Writing itself can and should be how I express and test my beliefs, but only if I get much better at it.

I started Puppet with core hypotheses, considered stupid by the experts around me. There was no point in talking about them; anyone can talk, and listeners similarly get to pick their conclusions. Only those I could prove had merit.

Proof is complicated. Few of us live in the world of math, where there’s enough overlap between objective reality and our language for discussing it that we can be truly sure. Computer science is itself lacking the unsentimental judge that the natural world provides to actual science. In truth, I should not discuss proofs, but rather disproofs. My real challenge with Puppet was to get rid of my false beliefs and let the remainders shine through, and there, programming was the perfect foil.

The best product idea in the world is worthless if it can’t be expressed in software in a sufficient timeframe. Merely building Puppet forced me to discard many convictions, and early rejects often became critical axioms undergirding the whole system. Of course, in the world of software, the compiler is only the first test. The real arbiter is your user, your customer. Once you’ve expressed your belief in a form someone can use, do they? I remember arguing for hours with a customer against a feature he requested, but the cold hard reality of his problem had me spending that night in my hotel room fixing it.

I am often asked if I miss programming. I do not.

What I miss is the laboratory it provided me, and the complete world that enveloped me, pressing in on me with its constraints, requirements, and complexities. I miss the hours I spent focused on one problem, and the complex systems needed to turn my ideas into a form usable by others.

I am thrilled and relieved to see that writing can be a new and even better laboratory for me. When I was programming full time, problems would haunt me, refusing to leave. I wore holes in my shoes walking back and forth between my keyboard and the local coffee shop, trying to line things up so they made sense. I’d scrunch up my face while drinking the coffee, drawing enqueries as to my wellbeing.

Writing is harder than that. The problems are bigger, and yet deeper inside, and harder to extract. I was never afraid of programming, but every idea I fail to write frightens me at least a little. On the far side, successfully expressing something is cathartic, a release, and it washes everything out with it.

It’s a better laboratory, because I have far more opinions about the real world than about the software world. Like those hypotheses that led to Puppet, I don’t know if they’re good. But I do know they’re different. I’ve bounced off reality enough times, asking for help from the crowd of onlookers and then getting back up, that I have a good sense of which of my beliefs are widely shared, and which are rare. For better or worse, little of what I believe, of what I think is important, is widely shared.

I’m excited by disagreement. Alignment is critical to execution, but diversity is needed for learning.

More than anything, I look forward to sharing my ideas, and as I did with Puppet, either finding them useful to other people, or having them cut to shreds to reveal new constraints, insights, opportunities. To do that successfully, though, writing is not enough: People must be able to read it.

Writing is no easier than coding, and in both, it’s ten times harder to write for others as for oneself.

One of my earliest optimizations in building Puppet was to prioritize my own productivity wherever possible. I explicitly chose to program in Ruby because I was faster there, even if it was slow and unpopular (Puppet was started before Rails was released). It took years for my programming style to reveal itself as an implicit personal optimization, highly effective for me but inscrutable to others.

My writing turns out to have a similarly mixed legacy.

All of the great shifts I initiated at Puppet began life as an essay, some extruded in a single sitting but more often sculpted over months and years. Once a hypothesis could defend itself, I then spent months and (more often) years translating it, turning it into something people could execute.

I’m proud of that work — how can I not be, when it helped build Puppet into what it is today?

But it’s fair to define good writing as something that doesn’t need a translator into its own tongue. By that measure, I’d failed.

Like a young programmer, I used to see people’s confusion as a sign of my genius and the value of my work. Now I look back with my designer’s eye and see it as a missed opportunity. We could have been there years faster if my beliefs had come with a better user experience. Kanies’s Razor is as applicable in prose as it is in code: Never attribute to genius that which can be adequately explained by incompetence.

I sit at the keyboard today as thrilled and scared as I was at the shiny benches of my science classes in college. Today I smell tea instead of banana oil and denatured ethanol, and I have no lab tech to stonewall me when I ask for easy answers, but the feeling of hope, of optimism, of a world to be discovered, understood, and fought through lifts me up just the same. I believe I can enjoy writing as much as I ever enjoyed programming, I can develop and test a wider range of hypotheses with a greater impact on those around me, and I can even learn get those ideas across to other people.

This, to me, is joy.

The Job of the Filesystem

It should do more so you can do less

Originally published at Hacker Noon

Apple just released iOS 10.3, which for the first time puts one of their production platforms on their new filesystem, APFS. I’m pretty happy that they are finally replacing such an aging, obsolete piece of core technology, but I’m nowhere near as excited about it as John Siracusa is. All APFS seems to do is finally meet the basic needs of a modern operating system, and not even all of those. It doesn’t come anywhere near doing what I care about most in the filesystem, which is owning metadata so applications don’t.

As anyone following the discussion of federal surveillance knows, metadata has become at least as important to our lives as our data. It’s not just the phone calls, it’s who you called, when, and for how long. It’s not just the phone, it’s which ones are your favorites and how they relate to each other. This metadata is as important to us personally as it is to the NSA, because it’s what brings simplicity, usefulness, and most importantly accessibility to the reams of information we create and rely on.

The reason I’m disappointed in APFS is that it missed the opportunity to promote metadata into something as important as the data, and as a result I’ve largely lost hope that computers will ever be as useful and open as they can be.

I’ve been trying for months to convert from Apple’s Photos to Adobe’s Lightroom for photo management, and the biggest barriers to doing so are metadata. It’s easy to get all of the photos — just drag the Masters folder into Lightroom. Oh, you organized your photos into albums? Yeah, that’s all gone. You had thousands of photos categorized as favorites so you could easily find the best? Oops, we ignore that.

Google Photos has the exact same problem. I can’t imagine how anyone who cares even a snit about photos could migrate to it, because there’s literally no way to do so that preserves any metadata at all. You get to keep the photos, but not how you organized them, and your only option is to rely on what they think matters to you.

Can you imagine switching email providers but losing all of the information about who the email is from or when it was sent? That’s as idiotic as what’s happening here.

If my filesystem owned this metadata, on the other hand, no conversion would be necessary. Any application could be written to read and write it directly, or I could trivially use any scripting language I wanted to do so. In fact, I could easily switch back and forth between different apps for different purposes, because they would not be able to lock me into their proprietary databases.

This shift is hard to understand, as we’re so used to thinking of applications and their metadata as somehow intertwined. For those in the programming world, there’s a clean analogy that helps to explain the horror of the modern filesystem:

For most of the history of software, applications have been written to directly access databases. They needed to understand the structure of tables and rows, and they had to write and manage their own queries for interacting with that data. Because of the complexity of duplicating this ability, applications tended to own their data entirely, and no other apps could get access.

We’ve recently instead seen a trend towards building very simple data services on top of databases, so that no app directly accesses them. This data service provides an API that understands how all of the data works, and also provides all of the key operations that can be performed on the data. This way, any application can access the data — for both reading and writing — without worrying that its use of the data is somehow incompatible with another consumer. You get the added benefit that any optimizations in the data service help every consumer, not just the one or two apps you remember to change.

Those data services are exactly what have enabled modern applications to scale to the level they do. The application developer can focus on their goals for the data, relying on the data service to provide consistency, portable operations, and everything else.

In the land of the operating system, though, we have no such luck. Everyone who talks to the filesystem gets about the thinnest interface imaginable: Get me a blob of data. Yes, there’s basic metadata (who owns it, when it was created, etc.), but none of it is or can be custom to the application, which makes it useless. Can you imagine how unpleasant it would be if we had to shoehorn both the subject of an email and the subject of a photo into the same keyword?

As a result, everyone turns that blob that the filesystem is trusted with into a database, and that’s where they put all of the metadata. Some even put the data there, even if it means huge database files and entirely non-portable systems. Really great app developers then go to the effort of building a full read and write API on top of this database that allows you to manage and port everything in the database. That’s enough work that most people skip it, though.

I would never have seen this missed opportunity in the filesystem if I hadn’t used BeOS. I went to Reed College, where Steve Jobs famously attended briefly (I made the unfortunate mistake of graduating, unlike him). This meant I was a Mac user all through school, which were the bad days of Quadras and MacOS 8 and 9. shudder I switched to BeOS because, well, I could, and it’s what really turned me into an OS junkie. There were many awesome things about it (many of which are now in OS X), but my favorite became how much responsibility the OS took for metadata. Applications became smaller, simpler, and in many cases, you realized your whole concept of an application was a way of organizing metadata, which meant you could rely on the OS entirely, and needed to write no code.

The greatest irony is that the author of Be’s awesome filesystem, Dominic Giampaolo, is now a lead engineer on APFS. Through the work of him and the rest of the team at Be, I came away with a clear idea of the value of my metadata, and especially the benefit of the operating system putting it on center stage.

So while I’m happy that my phone is no longer running the oldest, crappiest filesystem around, and I’m looking forward to the days when my computers aren’t either, I’m not excited. Until it was released, I could always dream that Apple saw the same future I did.

Now that the new filesystem is here, that hope is lost.

The Wrong Successes Kill Companies

Just because it’s working doesn’t make it right

Startups are in a constant life and death struggle, where a short succession of failures can destroy them completely, or a sudden string of successes can lead to growth and stardom. Exactly because of this constant risk of death, startups grasp at every flash of success, and their eventual failure can often be traced back to those successes they bet on, rather the roadblocks they hit.

This means what you decide to double down on is as important as the fires you decide to fight. This is true in any company — a specific form of this is covered in depth by Clayton Christensen in “Innovator’s Dilemma”, where successful companies over-solve their customers’ problems rather than finding additional customers. It’s especially true for startups, though, which are so risky that every potential customer, employee, investor, or partner can be the difference between making payroll and going bankrupt.

Steve Blank and Eric Reis have done a great job of teaching the world about the importance of quick learning and iterating until you get wins, but reality is more complicated. Say you’re in the middle of rapid product iteration and you get a rash of customers who sign up but are completely different from those you have been trying to attract. Is this awesome or horrifying?

How could new customers be such bad news, you ask? Easy: They could be the wrong customers. “Wrong” could mean many things. They could be from a very small market, such that success with them isn’t enough to build a scalable business; they could be unprofitable, in that they’ll be very high-cost to acquire and support, so every added customer loses you money over time rather than making it; and most commonly, they’re just not the customer your company strategy set out to find.

Eric Reis might say finding this kind of customer is the sign you need to pivot. That might be true. But it’s not automatically so. You were right enough to get this far, why give up so quickly on your definition of the perfect customer?

Because once you change your direction from focusing on the customer you want to customer you have — that is, once you start focusing on whatever seems to be working rather than your goals — you will quickly find yourself running a different company than you had planned.

This is one of the hardest problems for entrepreneurs: How do you decide when good news is leading to a better place, or a fatal compromise to your dream?

This came up constantly for me while running Puppet, in almost every part of my job. For instance, we did all of our high-growth hiring from Portland. Because of the small market and especially small tech sector, you have to be pragmatic about who you hire. You look up in 2 years, and you’ve got complete teams built off that first compromise hire. That first developer hire was a success, but changed your team’s direction. Now that that person has hired a team, or at least provided the template for the team, are you where you wanted to be, or completely off track?

You can argue that this isn’t a problem we would have had in the Bay Area, but not compromising when hiring is as pernicious a myth as true love. Even if you think someone is perfect, they’re still a real person, with opinions, behaviors, and habits that affect the destiny of your company, in good and bad ways. Again, the point here isn’t that you failed when you hired this person — the point is that the success you experienced changes your destiny in ways you can’t undo or predict.

That first customer started making feature requests and filing bugs, and two years later you’ve built something that can attract a lot more customers like them. Yay, or boo? There’s no right answer. I know one company that was almost destroyed by its biggest customer, and easily lost two years of roadmap progress focusing on them, but I know another company who built an amazing business by initially focusing on a couple of heavyweight customers.

When no decisions have been made, all life in front of you is opportunity. Choosing one opportunity inherently closes off others, and great decision makers know and accept this. If anything, sometimes a decision is great because of the opportunities it rejects, rather than those it selects. Running a startup is an accumulation of these bets, these selections and rejections. It’s hard to predict the consequences of even one of these big decisions, and it’s impossible to know what their legacy will be in a few years. You might end up exactly where you want… but you might be sowing the seeds of your downfall. That’s what makes the job hard.

The only tool I ever developed for managing this over the long term was to hold clearly to a specific set of goals, and to a specific strategy. When successes came along that didn’t fit our goals or strategy, we could decide to change them. But if we chose not to, then we essentially ignored it. It was a false positive. On the other hand, if you look up and a series of false positives starts to look like a trend you want to refocus on, then you must first rethink your goals and strategy, and only then switch your execution.

Or at least, that’s what I did. In truth, though, I don’t think I held the line enough. I think I was too willing to listen to people who were tactically great but didn’t buy into our strategy, and I was too willing to believe someone else’s expertise should take priority over my opinions. That doesn’t mean these were all mistakes, but it does make my time at Puppet easy to see through the lens of compromise and regret rather than the great success it really is.

In the end, when I look at how Puppet evolved, my sharpest pains come from compromises in strategy, and my brightest joys shine from a flawed execution in service of a pure vision.

The Binary Future of Software Companies

We’re seeing a rapid separation into SaaS companies and suppliers to SaaS companies

Software as a service is the most important technology business model innovation my lifetime, and before too long all important technology will be either provided as a service, or be an expert tool purchased in order to provide a service.

Software as a Service (SaaS) will not just restructure the entire economy of technology but dramatically improve it, because the rate of learning in a SaaS company is orders of magnitude better than for on-premise software (and oh my god better than for hardware). A really good on-premise software product is released and upgraded quarterly, meaning its fastest learning cycle is a 3 month cycle. A good hosted product is released tens of times a day. Twenty releases a day, times 5 days in a week and 12 weeks in a quarter mean that a SaaS company gets 1200 releases out in the time an on-premise company gets a single release.

Every release is a learning opportunity, which means a SaaS company can learn, and thus improve its user experience, more than 1000x more quickly than even a high-performing traditional software company. With this kind of difference in the rate of improvement, before too long anyone who isn’t a SaaS company is irrelevant. Literally — you can just ignore them.

Except of course that’s not true. If you’re a SaaS company, you can’t rely only on other SaaS companies; there are problems that can’t be solved off-premise, complexities that can’t be abstracted into a service, and technologies needed to provide your service that can’t be procured as a service. The most obvious example is that it all has to hit silicon at some point, and someone somewhere does actually have to buy CPUs, hard drives, and memory, with enough duct tape and baling twine to hold it all together and enough fans to cool it all down. While this is one obvious exception, there are plenty of others.

Thus, even with the learning rate of SaaS companies, and the resulting obsolescence of most other kinds of tech providers, there is still room for those who sell to the SaaS companies. This is somewhat akin to the ’49 gold rush, when there were gold miners and those who sold to gold miners. Both were valid pursuits, and tightly entwined, but they were very different businesses.

In the early days of the software world, and especially the early days of the enterprise IT department, every company evolved to be mediocre at any kind of technology, and they all looked pretty similar. They could do just about anything, and they sold to pretty much everybody, but they couldn’t do anything particularly well. This impending world of SaaS companies hires only experts; they are absolutely fantastic at everything they care about, and they have an equally fantastic service partner to whom they can outsource anything they don’t care about.

In some ways, this world is even more dangerous to the status quo of the technology industry. Our entire industry has evolved to sell to generalists: We build pretty decent stuff, and sell it to people who are ok at managing it. Our stuff can’t be too great, because great stuff requires expert users, and we can’t demand too much of our users because they have to be competent at nearly everything within a very large field (“networking”, “hardware”, “applications”), so they can’t invest in being particularly excellent at any one thing. Also, great stuff would be really expensive, and companies don’t buy expensive stuff, because no particular investment is all that important to them.

In this new world, there exist only experts, whose entire mandate is to specialize in the specific tools and technologies that will allow a SaaS company to excel, to win. For the investments that can make a real difference, no cost is too high, and no expertise is too narrow. For investments that can’t make a real difference, of course, we just find a service partner who cares so much about it we don’t have to think about it. Thus, as a SaaS company, I only invest in technology when I can afford to invest in experts, and I immediately reject any technology built for generalists because I can’t achieve outsize results with tools built for generalists.

Here we reach a future where there exist only SaaS companies, and companies who build expert tools for narrow use cases that exist within SaaS companies. Anyone else is fiercely riding a bicycle while watching a train recede into the future. The pundits of today are correct that the cloud is the most important trend of the modern era, but they’re wrong in thinking that AWS or Cloud Foundry hold a candle to the restructuring that SaaS will wreak.

Start With the Dangerous Questions

Throughout my 12 years as CEO of Puppet, I made critical decisions that affected nearly everyone involved in the company: What investors should we work with? Who should we hire? What products should we build? Should we take that deal with a customer?

These decisions are scary. Getting them right can be a huge lift for a company, but getting them wrong can destroy one. I worked at a company that lost more than a year of growth and roadmap development because they signed their largest customer ever. One of my advisors told me a payment of more than one hundred million dollars from a partner destroyed his company. I’ve also taken big risks on key employees, and had some of them work out fantastically, and others flame out spectacularly.

We’ve all been there. You’re in an interview, the first of many discussions with a candidate. You’re focused on building rapport, getting an overview of their career, but some niggling fears are pushing down on your sense of comfort. What do you do?

I know what I used to do, and it didn’t work. I’d focus initially on an overview and getting to know them, then I’d dive deep into their experience and skills. At that point I would find I still had fundamental questions I need answered, but it’s a bit awkward to ask these basic questions in the 3rd interview, isn’t it? Awkward indeed. You either take the risk and hire without those answers, or you take the loss and reset, looking like an amateur. I’ve done both of these more times than I can count. Just talking about it brings up again the anguish I’ve had in those late meetings, realizing there were critical questions I didn’t have answers to, and I just didn’t know how to get out of there.

So I flipped it. Now I chase the fear. I pin it to the wall, and I scrutinize it until it withers away or takes over the room.

With customers, one of my scariest questions has always been, “Why are you buying our product?”, as if merely asking them would cause them to reconsider. The only thing worse than losing a prospect, though, is having the wrong customer sign up. I’ve had customers who I spent hundreds of thousands of dollars supporting who never succeeded with the product and then didn’t renew a year later. Some have signed up then complained incessantly that we don’t have the features they need. I’ve said yes to a painfully low-priced deal to land a big customer, only to have them change all the terms at literally the last minute because they know they have us over a barrel. These are all signs that someone should not have signed up with you, that you have a mismatch you’re dodging.

I have hired people with time at important companies during critical growth years, and then found out later for all their knowledge of the events, they weren’t remotely involved. That was early in my experience of hiring — I’ve since learned to ask, “Yes, but what exactly did you accomplish while working at that great company near those great people?” I don’t care if a previous employer did great things, I care if you helped them do great things. Otherwise, it’s irrelevant.

This change in practice was initially frightening, and felt almost like I was breaking the social contract. I’m already hard enough to get along with, and not a person people usually enjoy interviewing with. I also have great loss aversion, especially when trying to convince a talented executive to move to Portland. The truth is, though, if you aren’t going to move, I should learn that in our first conversation, not after I’ve put 30 hours into interviewing you only to have to reject the offer because you can’t pull your kids out of school. I understand, but shouldn’t we have learned that together earlier?

Once I forced the conversation through these risky channels, though, the rest of the work is done without much fear. We quashed all the really scary stuff in the beginning. Even better, because we’ve walked the deep dark forest together and come out the other side (assuming we have), we understand each other better, trust each other more, and all of our conversations are tinged with that greater knowledge. When I recently went to hire a CFO, I rejected multiple highly qualified people very quickly because they were looking for the badge of leading an IPO rather than wanting to help build a great company. That’s not necessarily bad, but it’s not what we were looking for.

The best thing about this technique is that it’s good science. I have a chemistry degree, and I really kicked myself when I realized how inconsistent, how unscientific I was when making decisions. In some areas I experience no real loss aversion, so I can dig right into the scary stuff, but in hiring, signing large customers, and a few other areas, I found that the fear had been too strong and I kept tying myself in knots. Once I backed away and considered any candidate, any decision as a hypothesis, and then looked at my questions as experiments trying to disprove that hypothesis, the answer was dispassionately clear: You must run the most dangerous tests first.

Sure, you can do a bunch of simple experiments that are highly unlikely to prove you wrong. But if the 9th test was always the most dangerous one and your hypothesis fails there, then you just wasted a lot of time and paid a high opportunity cost.

The objectivity that came from looking at this problem through a scientific lens helped me recognize that my loss aversion was making my decision making much worse. I didn’t so much learn to operate without fear as learned that the fear was rational and was a useful signal. It gave me the strength to pursue that fear, rather than hide from it, even in the scariest areas.

Maybe you aren’t hiring people, or seeking investors. But I know you make key decisions, decisions that affect you and those around you. If you don’t get out of your comfort zone and ask the important questions, not just the easy ones, then you’re basically filibustering your work: “Well, we’ve run out of time, guess we’ll just have to skip those questions.”

If instead you can find a way to focus first on the scariest parts of those decisions, the parts that can least stand the light, then I think you’ll find you make higher quality decisions, you will enjoy the process more, and you’ll have better outcomes for everyone involved.

Your Whiteboard and Post-Its Aren’t Kanban

Kanban is an incredibly useful productivity tool, initially developed in Japan on automobile manufacturing lines. It has since become a widely adopted practice, including in software development and project management. Or has it?

That cute, simple tool you have that uses post-its, or skeuomorphic representations of them, to keep track of the state of some task or project? It’s not Kanban. To paraphrase Bill Hicks: No no no, I know you think it is. But it’s not.

What you have is a useful means of task and project management. It might be awesome. It might be saving you effort, time, and stress, and actively making your life better. I’m sure it’s a good tool, Brent. But it likely has nothing to do with Kanban.

To be clear, that’s fine. There’s no rule that says Kanban is useful to solving your problem, or that you ever need to use it. It’s just, you know, words have meanings. And the meaning of Kanban is all about inventory management. It’s true that you totally could be using post-its on a whiteboard to track inventory. But you’re probably not.

In both your task tracker and in Kanban, the card represents something. That is, the card itself is not relevant, but it represents a thing that you care about. In your tool, it’s representing some task that someone needs to do and the state that the task is in. This helps you to understand and communicate key information across all of your tasks, projects, and teams. I can see why you find this useful. Heck, I find it useful. I’m using it to track the state of this article, for instance.

In Kanban, the card represents something completely different: The need to refill inventory. At its simplest, you use cards to denote the minimum allowable inventory in a system, such as car doors sitting at an installation station. You do so by literally placing a card on the door at the minimum level. You pair these cards with separate rules about the maximum allowable inventory. Now each of your inventory pools (doors, engines, seats, etc.) have maximum and minimum levels — if the inventory gets low enough, the installer encounters the card and orders a refill, which itself is never above the maximum allowed. As you operate the system you tune it over time to make sure your min and max levels are right.

For most of your work, you can ignore the card and focus on what’s in front of you, but as soon as you encounter it, you must take action. This gives you two features that are otherwise lacking: You get to ignore the card and focus on your work for the majority of the time, which is incredibly important for productivity, and you also get to explicitly separate the process of optimizing the inventory pools from how you consume them. You can always be in the moment when you do the work.

On first blush, you might think to yourself that this doesn’t sound very useful. I mean, how much of your life is really affected by inventory problems? Pffft. Literally all of it. You deal with this constantly in your car, for example; its maker decides on your maximum fuel level (the tank is fixed in size), and you never want to run out of gas, but instead of a card you have a light on your dash when it gets too low. Obviously every grocery store and restaurant has to think about this, but so do banks (envelopes, paper, checks), mechanics (parts, tools), and coffee shops (coffee, chairs — yes, chairs).

You have personal inventory problems, too. We keep hearing about these magical fridges that will order milk for us automatically (but are more likely to be used in a DDoS); Amazon has released one-touch buttons that enable us to trivially order new inventory; and most of us have experienced the ignominy of running out of a key supply at just the wrong time, such as when using the toilet. To see these problems for what they really are, you need to step into a different mental model, a new world.

You need to step into the world of inventory. Rather than seeing everything around you in terms of work to be done, see it in terms of pools of inventory to be shifted, consumed, and refilled. It’s not necessarily “better”, but it is often enlightening. Kanban got created as a tool specifically for increasing the efficiency of such a world, and only makes sense when you’re in it. In fact, the cards themselves aren’t important at all — there are plenty of different triggers available.

It might shock you to realize just how much of your life would be improved by viewing the world this way. Suddenly all of those latent tasks that are sudden emergencies when you run out of something become simple efficiency problems that are easy to model and solve. In my last few years of experimenting with this in my personal life, I’ve built many triggers into many of our inventory pools. None of them are cards, but they are all closer to Kanban than your Trello board.

For example, we go through a lot of granola in my house. Our means of ensuring we never run out is to have two containers, about the same size. We always pour breakfast from one and refill from the other, and the emptying of our refill container is the trigger that causes us to buy more granola.

We keep one in-use and one unused toilet paper roll in each bathroom, plus a cache in a closet. Emptying the in-use triggers using the extra roll, which triggers pulling another roll from the cache. If that is the last roll there, pulling it triggers buying more.

In each of these cases, we’ve set up inventory pools that match how long it takes to refresh them. For example, our granola containers are sized that so that we don’t go through a whole container faster than it takes us to buy more. We never run out of toilet paper, but we don’t have to dedicate a room to storing it.

This perspective also allows us to recognize when we are missing a trigger to refill inventory, allowing us to shift the conversation from personal blame to process improvements. For example, in a bid to teach our kids to self-regulate their sugar intake, we’ve started making our own fruit yogurt and letting them add sugar, rather than buying pre-made fruit+sugar yogurt. We kept running out, though, because it took a day to thaw frozen fruit. We didn’t have an appropriate trigger to start this task at the right time. Having recognized this problem, we created one (I get frozen fruit out to thaw when we have about one meal left of pre-mixed yogurt), and on first blush, it seems to be working. We haven’t yet integrated it with one that buys more yogurt on the right cycle, though, so it’s not yet a complete system.

These are examples of using non-card triggers for Kanban-style inventory management. It’s the triggers that matter, not using cards to represent them. If we tended to have larger collections of unit inventory, cards might be appropriate. E.g., I usually buy razor blades in bulk, and it might be appropriate to label one of those blades with a card to trigger repurchase when I reach it in my stack. Here I’d have to find the right optimization between managing a large inventory, finding the right trigger, and getting the lowest cost per blade (which requires buying in bulk). Combine that with the fact that I usually use an electric razor (which means I rarely assess the state of my blade inventory) and the likelihood of making an inventory mistake goes up, thus increasing the value of a trigger-based system.

For all that I love tools like Trello, and systems like Kanban, I’m not sure they can ever actually be used together. That is, I think we have a whole industry of tools built to model a specific kind of problem, which are instead useful for many things but specifically not the problem they’re meant to exemplify.

The beauty of Kanban is that it’s out in the world, where your work is. (Don’t be confused into thinking that that board or those cards are your work; they just represent it.) I’ve been trying for years to build a Trello board, or some equivalent, that enables an inventory-oriented view on what I’m trying to do, but I’ve not yet succeeded. For instance, [WIP limits] mean something completely different when they represent tasks instead of inventory. That doesn’t mean they’re useless, just not useful for the same reasons.

My recommendation is that you enjoy your task management system, and continue to get what you can out of it. Maybe just stop calling it Kanban. At the same time, though, ask yourself: Where are the inventory pools in my life? What do I run out of, and how can I build triggers at the right point to prevent that? How does my world change when viewed this way?

Most of all, get out into the world. That’s where the work is.

I’m Often Asked

Since these are questions I’m often asked, I thought you might be interested in their answers.

How did you get from a hippie commune to starting a software company?

I was born on a hippie commune in Wisconsin, then moved to a related one in Tennessee when I was 4 (this was “The Farm”, best known for having produced Spiritual Midwifery, a book that was a major contributor to reviving midwifing in the US). When I was 8, I cut a foot of hair off my head and began attending public school in Nashville, Tennessee as a vegetarian who’d never heard of capital-G God.

Suffice it to say, it did not go well.

Much later, as I worked my way through college, I realized that my coping mechanism for dealing with the stark conflict between those two cultures was to literally forget everything I knew. It was then I realized I only retained a few memories of my childhood on the Farm. Given contradictory but unverifiable information — and Nashville and the Farm were definitely both — the only reasonable response is to discard it all. That explains why I didn’t trust the kids in 4th grade who told me I was going to burn in hell for 10,000 years because I wasn’t baptized, and it also explains why I do not resemble someone raised on a hippie commune.

I graduated from high school a year early, mostly to escape my incredibly violent 3,000 person high school run by jocks. I didn’t exactly have role models to show the real possibilities of what going to school can do — nearly every adult I knew went to college, but I knew I didn’t want to use my degree to build shoddy houses and dig outhouse holes in the woods. When it came to picking colleges, I eliminated all schools that had fraternities, sororities, or organized sports (because I wanted my school run by the geeks, the nerds, the brainiacs), and then I picked the best school I could find the furthest from my home town.

I looked at schools in Alaska, but the one I found that fit the criteria was too small at 400 people. It never occurred to me to consider overseas schools. Then my home room teacher pointed out Reed College, in Portland, Oregon. I’m sure their whole book was useful, but the only bit I remember was how their Guerrilla Theater of the Absurd ingested red, white, and blue mashed potatoes in preparation for a visit by then-vice president Dan Quayle, and then threw them up at his speech. I was in. That was a whole different kind of patriotism than they practiced in Nashville.

I was too poor to visit any schools, so I showed up at Reed having never been on the west coast, or within a thousand miles of Portland. The black and white photos in the school book didn’t quite capture the place. Seeing the campus for the first time is unquestionably the first time I remember honestly crying for joy.

One of the first things I did there was buy a computer, and one of the last was decide not to be a scientist.

How did you get from a chemistry degree to starting a software company?

I had seven jobs in two and a half years at the end of college, so I tried a lot of things. I got fired a lot. Until my last year, I was planning to be an academic scientist, but Reed did a great job of training me on exactly what that job entailed, and the result was that I didn’t want it. For all that science is all about trial and error, they don’t actually allow much failure in your career — you better pick the right boss, the right school, the right project. Anything else means you can’t get the grants, because there’s just too much competition for too little money.

Once science was out, there weren’t a lot of other great options. I am not one of those who grew up with a computer; I didn’t get one until my sophomore year in college, and taking a loan out for it is one of the first things I did in school. I had spent a lot of time playing with my computer, and I found I was particularly adept at breaking it. When are you most likely to break it? When you’re procrastinating. And when are you most likely to procrastinate? When you really, really need your computer to work because there’s something big due the next day.

This meant that I also got pretty good at fixing it quickly. Or maybe, setting it up in such a way that it was always easily fixable.

When it came time to look for work, this is pretty much what I had to go with: A science degree, and facility at breaking computers. That led to a QA job, a couple of mac admin jobs, and finally a support job, which soon turned into a Unix administration job. Most of those jobs I was fired from (who gets fired from the Plaid Pantry?), but the last one was a great fit for me, and I only left because I was moving to Nashville.

Once I got there, I continued my investment in scripting and automation, which two jobs later resulted in my being a consultant, having worked myself out of a job. I quickly concluded I could make good money at consulting but hated the job. I thought about an MBA, because the badge is useful, but I didn’t think the schooling would be. I almost went to law school, but then I realized it’s so expensive you have to become a lawyer afterward, which I didn’t want. So, I did the only thing left: I started a software company. I figured I’d learn more failing to start a software company than I would succeeding at getting an MBA.

Puppet wasn’t my only idea — I’m still pretty enamored of a software product I wanted to build for scientists — but in the end I concluded it was the one I was most likely to succeed at, based on my own knowledge and on the market. In the end, I started Puppet to get out of system administration, not because I loved it.

Did you ever think Puppet would get this big?

I always knew it was a possibility, but I never let myself get hung up on whether it would happen or not. Any given situation has many possible futures, and it’s generally unwise to be too attached to any one of them. With Puppet, I was always committed to some of the constraints, but generally not so much to the specific outcome, and certainly, I didn’t spend much energy trying to predict it. With the right constraints, I hoped we would end up in a good place, which was the most I could hope for.

In terms of those constraints, they were things like maintaining a high quality business, where deals were good deals and customers generated real revenue, where we focused on the user and not the buyer, and where we maintained our authentic voice even in marketing.

That being said, I did think that Puppet could succeed, and in a big way. I knew the market was measured in the billions of dollars a year, and I knew it was composed primarily of bad software sold by dying companies. Someone was going to come in and take business away from those companies, take users away from them, and I saw no reason why it wouldn’t be me.

“Someone has to do something, and it’s just incredibly pathetic that it has to be us.” — Jerry Garcia

Did I hope for something like this outcome? Heck, I hoped for more, faster. This is one of the better possible futures Puppet had when I started, but there were far better futures available, and it’s tough not to see those and ask, “What if?”

In the end, though, I am incredibly proud, pleased, and surprised by what we were able to accomplish. I know how lucky I am, how rare this outcome is, but I also know that it wasn’t entirely accidental, that I started at the right time with a good idea, a good market, and a pretty decent plan, and I worked intensely while passing up many opportunities to make mortal mistakes.