Value Chain: Intentional Generosity Starts with Gratitude

This note is the first in a series of four that detail Loup Ventures’ core values. These values drive how we operate, who we hire, and ultimately, what we look for in founders. We believe that vibrant culture driven by shared values separates the best companies from the rest. We meet with hundreds of startups a year and one of the common gaps that we see is a lack of focus on culture building. In an effort to bring our values to life, we’re sharing them in our Value Chain series.

We believe in the power of generosity – both as a means of fostering a positive environment for team members to do their best work, and as a powerful business tool that generates a virtuous cycle for stakeholders.

The Golden Rule. Treat others the way you want to be treated. By giving more than you receive, you place your faith in the fact that others will return the favor. Generosity, however, is not quid pro quo – rather, each generous action pays into a culture that you hope will benefit you indirectly. So, if you want to be treated generously, act that way toward everyone – including bosses, employees, investors, co-workers, and partners.

Internally, intentional generosity creates a virtuous cycle of supporting one another, and yields better work through true collaboration. The byproduct is a positive environment of abundance – not scarcity – maximizing everyone’s benefit rather than defending individual territory.

This plays out at Loup Ventures in a powerful way: compensation. As a startup venture fund, our operating budget doesn’t support a big team. But our research-driven strategy requires lots of hard work. So, we’ve all committed to below-market pay near-term in hopes of above-market returns long-term. This is basic risk-reward, but the risk is also mitigated by the choice to be generous with each other in terms of time, learning, and development, not just foregone wages.

Externally, we try to live out the same generosity across all stakeholders. While we only invest in 1% of the startups we meet, many of the no’s have a continued relationship with us as we look for unique ways we can help them. Remember, however, that intentional generosity is also a tool – and the continued relationship could benefit us down the road if and when we get another opportunity to invest.

It feels better to give than to receive. Too many people have this backwards. The satisfaction of giving is much greater than receiving. Giving is accompanied by a sense of accomplishment and fulfillment because, put simply, you have something to give. While giving is more rewarding, the model does not work unless you also receive generously. And part of being a generous person is receiving generously. The combination of giving and receiving fosters a culture of abundance over scarcity – an abundance of teamwork, support, and thoughtfulness – We think it’s a better way to work.

To Our Readers: Thank You. If you’ve read this far, we appreciate your interest in our work. Giving and receiving generously starts with the daily practice of generosity and gratitude. We’re grateful for your support, your interest in our work, and your role in getting Loup Ventures off the ground in 2017.

We’re grateful for your support, your interest in our work, and your role in getting Loup Ventures off the ground in 2017.

You’ve been helpful beyond measure and we hope you’ve found our insights to be helpful, too. Happy Thanksgiving.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio.  Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Do You Have What It Takes to Be a Great Founder?

Every VC says they only invest in great founders, but the majority of venture-backed businesses still end in relative failure. Does that mean we as VCs are just bad judges of founders or do we not know what great founders look like? This is a question we’ve obsessed over since we started Loup Ventures — trying to define what makes a great founder and how to test for it. It’s hard. Great founders come from a host of different backgrounds, educations, genders, ethnicities. We’ve identified 10 traits across two categories that make great founders at the seed stage: Innate and Dynamic.

Innate Qualities of a Great Founder

Innate traits are character elements that are difficult to impossible to learn — either the founder has them or they don’t. Regardless of the type of business a founder starts, there are five imperative innate traits for all great founders:

  • Intelligence
  • Integrity
  • Commitment to suffering
  • Focused curiosity
  • Resourcefulness

Warren Buffett has talked about a few of these traits as things he looks for in his managers. Naval Ravikant has also talked about a few of them, so they shouldn’t come as much of a surprise. Intelligence is probably the most obvious of the innate traits. To start a valuable company, a founder must have some kind of smarts because intelligence leads to interesting insights about a market (see the next section). These insights translate into vision, which is the only truly defensible element and most important asset of any startup business. Vision is how an entrepreneur attracts talent and creates strategy.

 

Pure book smarts matter, but emotional intelligence is important too. A founder has to deeply understand his or her customers to deliver products they want, not just products the founder wants to build. A founder also has to deeply understand his or her employees and what motivates them to sustain high levels of productivity.

Integrity is the current buzz word in the startup world. We used to think about integrity as honesty, but that doesn’t seem to fully encompass the spirit of the trait. Honesty is a requirement because it means the founder learns from his or her mistakes. Dishonesty assumes problems are someone else’s fault, which means it’s impossible to learn. Ownership is a popular modern term for honesty – taking responsibility for things that happen whether they’re purely in your control or not.

The interesting component about integrity as it relates to startups is that great founders need to be willing to break rules to build valuable businesses. However, there’s a line between what’s acceptable and what’s not, and sometimes it’s blurry. Salesforce.com hired fake protestors to disrupt a Siebel conference in its early days. Clever guerilla marketing. The cases of Hampton Creek, Theranos, and Zenefits are clearly in the unacceptable camp. The ride sharing legal disputes are blurrier, although we agree that the laws are outdated and ride sharing is a significant net positive to the world. In any case, dishonesty and unethical behavior are contagious, so integrity must come from the top and be a guiding light for any startup.

The third quality of great founders is a commitment to suffering for at least five years. This might sound more extreme than necessary, but starting a company is a rollercoaster of suffering. You need to be comfortable with hearing no over and over and not let that destroy your will. You need to be able to withstand low periods that are inevitable — unexpected customer or employee losses, investor rejections, tax bills, fights with cofounders. Entrepreneurs don’t necessarily need to revel in difficulty, but it helps. We like to track the number of times we hear no during the week to reduce the negative reinforcement of it.

Why five years of suffering? It usually takes at least two years before you have any reasonable traction to show that your business might be working, then another few years of driving growth to create something that looks like a moat. Then you can afford to breathe. A little.

Focused curiosity might seem like an oxymoron, but curiosity that is targeted at a specific market leads to a commitment to testing new things. Testing new things leads to new business opportunities and products. Curiosity may be particularly necessary for seed stage founders (our focus) because their businesses are so nascent and require constant iteration. A lack of curiosity at the early stage leads to stagnation, which leads to death.

An early stage startup is an unending series of challenges. This is doubly true for first time founders who not only have to figure out how to deliver their specific offering to market, but how to operate a business in general. The final innate trait, resourcefulness, gives founders the ability to thrive in the face of persistent tests. A great founder is not one that says he or she couldn’t do something because they didn’t have enough capital or it was too difficult. They figure it out and keep figuring it out.

Dynamic Qualities of a Great Founder

Where the innate traits are binary and fixed, the dynamic traits of a great founder are five qualities that exist on a spectrum and evolve over time:

  • Market insight
  • Operational capability
  • Product sense
  • Growth
  • Leadership

Market insight is our term for the popular “founder/market fit.” What we want to see from a founder is that he or she has spent a lot of time thinking about and experimenting on a problem they’ve identified. In that sense, market insights are a byproduct of the innate intelligence trait being applied to a specific problem over a length of time. Founder/market fit to us implies that the founder has spent time involved in a market, thus the fit; however, prior market experience isn’t necessary for great founders. Jeff Bezos didn’t have founder/market fit when he started Amazon. He never ran a bookstore before, but he had a market insight about the Internet changing the way people shopped. The founders of Uber never worked in the livery business, but they had an insight about mobile changing the way people arranged transport. Airbnb is another example, and there are many others.

The other four traits are relatively straight forward business-related qualities. Operational capability is the founder’s ability to deliver their product or service and serve customers. Product sense is the founder’s ability to create a product or service that unexpectedly delights consumers. Product sense is what enables a founder to reach product/market fit. Growth is the founder’s ability to market and sell the product or service. Leadership is the founder’s ability to organize his or her team to meet objectives.

All five of these traits work in conjunction with one another, and all five are necessary for an early stage founder to possess in some degree. However, numerous factors influence the relative importance of the dynamic qualities of a founder. In other words, some of the dynamic traits need to be more developed depending on type of the founder’s company. For example, in a highly social company, a founder’s product sense seems to matter more than any other trait because user growth will have to be organically rapid for the company to service. The immediate experience of the users will be what keeps them engaged and sharing the product with others. An enterprise founder should require stronger growth capabilities to directly sell their B2B product, software or otherwise. Hardware companies tend to need stronger operational capability given the manufacturing requirements of their product.

The above observations were specific to seed stage companies, but stage of the investment also impacts the relative importance of the dynamic qualities in a founder. At the A/B round, product should be somewhat established, so market insights and growth might matter more as the founder tries to leverage his or her unique vision into some sort of durable advantage. In a pre-IPO or public company, the importance of leadership matters significantly more because of the likely larger number of employees at the company.

If You’ve Got It, Go for It

It’s boring to hear every VC say they only fund great founders, but it really is true, and their criteria probably isn’t much different from ours. Early stage companies are extremely fragile. VCs obsess over the quality of founders because it’s one of the few variables we can control. Recognizing these qualities in oneself is also an important variable an entrepreneur can control. Whether you’re running a small business or hoping to build the next Google, you must have all the innate traits and the correct balance of dynamic traits to be great. If you know you have them, then focus on your goal and be great. Hopefully we can help you along the way.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Humans Are a Bigger Existential Risk Than AI

Elon Musk continues to warn us of the potential dangers of AI, from debating the topic with Mark Zuckerberg to saying it’s more dangerous than North Korea. He’s called for regulating AI, just as we regulate other industries that can be dangerous to humans. However, Musk and the other AI debaters underestimate the biggest threat to humanity in the AI era: humans.

For the purposes of the current debate, there are three potential outcomes debaters of artificial intelligence propose:

  1. AI is the greatest invention in human history and could lead to prosperity for all.
  2. A malevolent AI could destroy humanity.
  3. An “unwitting” AI could destroy humanity.

There are few arguments in between worth considering. If the first possibility was not the ultimate benefit, then the development of AI wouldn’t be worth exploring given the ultimate risks (2, 3).

There’s certainly a non-zero chance that a malevolent AI destroys humanity if one were to develop; however, malevolence requires intent, which would require at least human level intelligence (artificial general intelligence, or AGI), and that is probably several decades away.

There’s also a non-zero chance that a benign AI destroys humanity because of some effort that conflicts with human survival. In other words, the AI destroys humanity as collateral damage relative to some other goal. We’ve seen early AI systems begin to act on their own in benign ways where humans were able to stop them. A more advanced AI with a survival instinct might be more difficult to stop.

There’s also a wild card relative to the first outcome that the two sides of the AI debate. On the road to scenario one, the positive outcome and probably the most likely outcome, humans will need to adapt to a new world where jobs are scarce or radically different than work we know it today. Humans will need to find new purpose outside of work, likely in the uniquely human capabilities of creativity, community, and empathy, the things that robots cannot authentically provide. This radical change will likely scare many. They may rebel with hate toward robots and the humans that embrace them. They may band behind leaders that promise to keep the world free of AI. This could leave us with a world looking more like the Walking Dead than utopia.

Since the advent of modern medicine, humans have been the most probable existential threat to humanity. The warning bells on AI are valid given the severity of the potential negative outcomes (even if unlikely), and some form of AI regulation makes sense, but it must be paired with plans to make sure we address the human element of the technology as well. We need to prepare humans for a post-work world in which different skills are valuable. We need to consider how to distribute the benefits of AI to the broader population via a basic income. We need to transform how people think about their purpose. These are the biggest problems we face as we prepare to enter the Automation Age, perhaps even bigger than the technical challenges of creating the AI that will take us there.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Machines Taking Jobs: Why This Time Is Different

Will AI and robotics revolutionize human labor or not? 

More than half of all US jobs could be disrupted by automation in the next several decades; at least that’s our opinion. About half the people we talk to disagree. Those that disagree think AI will open up new job opportunities by enhancing human abilities. A common element to their argument is that we’ve always had technical innovation and human work has evolved with it. A few examples would be the cotton gin, the printing press, and the automobile. All of these inventions threatened jobs of their era, but they ended up creating more jobs than they destroyed. So why is this time different?

Because, for the first time in history, we don’t need to rely on human intelligence to operate the machines of the future. The common denominator among those three examples and countless other technical innovations is that they were simply dumb tools. There was no on-board intelligence. Humans using those tools provided the intelligence layer. Humans were the brains of the cotton gins, printing presses, and automobiles. If the human operator saw or heard a problem, they fixed it and continued working. Today, the intelligence layer can be provided by computers through computer vision, natural language processing, machine learning, etc. Human intelligence is no longer required.

You might say that machines aren’t nearly as smart as humans, so they aren’t as capable as humans. But in reality, they don’t need to be. AI required to operate a machine only needs to have very limited domain knowledge, not human level intelligence (a.k.a. artificial general intelligence). Think about driving a car. You aren’t using 100% of your total intelligence to drive a car. A large portion is thinking about other things, like disagreeing with this article, singing along with the radio, and probably texting. An autonomous driving system only needs to be capable of processing image data, communicating with computers from other devices related to driving, like other vehicles, traffic signals, and maybe even the road itself, making dynamic calculations based on those data inputs and turning those calculations into actions performed by the vehicle. Any incremental intelligence not related to those core functions is irrelevant for an autonomous driving system.

The magnitude of the technological change is also significantly different in this current wave of advancements in AI and robotics. This wave is more akin to the advent of the farm when humans were still gatherers, or the advent of the factory when we were still farmers. Farms not only organized the production of food, but also encouraged the development of community and trade. Factories organized the production of all goods, encouraged the development of cities, and enabled our modern economic system by institutionalizing the trade of labor for wages. Automation will result in equivalent fundamental changes to the philosophy of production by taking it out of the hands of humans. This could result in societal changes of greater freedom of location and a basic income. In a way, the Automation Age may be an enhanced return to the hunter/gatherer period of humanity where basic needs were provided, originally by nature, in the future by machines. Except in the Automation Age, our purpose will be to explore what it means to be human instead of simply survive.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.

Bad Culture Doesn’t Scale

The most important lesson from Uber’s travails is that bad culture doesn’t scale. Talented teams with bad culture can build fantastic businesses, but not businesses that last. A unicorn with bad culture is a unicorn with a bomb strapped to its back — it’s only a matter of time before bad culture catches up and forces disruptive change. Sometimes bad culture rears its ugly head quickly, as it did with Zenefits. Sometimes it doesn’t happen until after multi-billion dollar per year business is established, as it did with Uber.

The culture at Uber wasn’t a secret. It had always been known as an aggressive one, and that culture deserves some credit for helping Uber transform the ride hailing industry; however, the bigger and more established a company becomes, the harder it is to maintain bad culture. Rumors spread, lawsuits happen, and good hires leave because it wasn’t what they signed up for. The media will report every painstaking detail. Advanced companies like Uber also face public backlash from customers, impacting revenue. If Uber were a publicly traded company, the stock would be down at least 30% in the past month given the CEO turmoil. Maybe down 50% for the year adding in the Google lawsuit and other well-publicized troubles.

During our time as public equity analysts, we’ve had the opportunity to cover some great, lasting companies like Apple, Amazon, Google, and Facebook. A common thread between all four of those companies is great culture. When Steve Jobs passed away, we wrote that his greatest achievement wasn’t the iPhone, the iPod, or the Mac, but Apple itself. He left behind a culture of good people driving revolutionary innovation. That might sound simple, but not compromising on your values and consistently hiring the right people that share those values is hard. It’s especially hard for a startup trying to build quickly while bearing the pressure of venture investor expectations.

It’s hard to determine the long-term fallout of Uber’s culture problem. The company has “verbed” itself, much like Google, which allows it a significant brand advantage. One of our teammates has joked that he would, “uber us a Lyft.” With broad leadership change, including the departure of its CEO, Uber has a chance to grow new roots and overcome the negative culture that’s now detracting far more than it ever added.

Disclaimer: We actively write about the themes in which we invest: artificial intelligence, robotics, virtual reality, and augmented reality. From time to time, we will write about companies that are in our portfolio. Content on this site including opinions on specific themes in technology, market estimates, and estimates and commentary regarding publicly traded or private companies is not intended for use in making investment decisions. We hold no obligation to update any of our projections. We express no warranties about any estimates or opinions we make.