November 2020 - Tape Sucks: Inside Data Domain, A Silicon Valley Growth Story by Frank Slootman

This month we read a short, under-discussed book by current Snowflake and former ServiceNow and Data Domain CEO, Frank Slootman. The book is just like Frank - direct and unafraid. Frank has had success several times in the startup world and the story of Data Domain provides a great case study of entrepreneurship. Data Domain was a data deduplication company, offering a 20:1 reduction of data backed up to tape casettes by using new disk drive technology.

Tech Themes

Data Domain’s 2008 10-K prior to being acquired

1. First time CEO at a Company with No Revenue. Frank is an immigrant to the US, coming from the Netherlands shortly after graduating from the University of Rotterdam. After being rejected by IBM 10+ times, he joined Burroughs corporation, an early mainframe provider which subsequently merged with its direct competitor Sperry for $4.8B in 1986. Frank then spent some time at Compuware and moved back to the Netherlands to help it integrate the acquisition of Uniface, an early customizable report building software. After spending time there, he went to Borland software in 1997, working his way up the product management ranks but all the while being angered by time spent lobbying internally, rather than building. Frank joined Data Domain in the Spring of 2003 - when it had no customers, no revenue, and was burning cash. The initial team and VC’s were impressive - Kai Li, a computer science professor on sabbatical from Princeton, Ben Zhu, an EIR at USVP, and Brian Biles, a product leader with experience at VA Linux and Sun Microsystems. The company was financed by top-tier VC’s New Enterprise Associates and Greylock Partners, with Aneel Bhusri (Founder and current CEO of Workday) serving as initial CEO and then board chairman. This was a stacked team and Slootman knew it: “I’d bring down the average IQ of the company by joining, which felt right to me.” The Company had been around for 18 months and already burned through a significant amount of money when Frank joined. He knew he needed to raise money relatively soon after joining and put the Company’s chances bluntly: “Would this idea really come together and captivate customers? Nobody knew. We, the people on the ground floor, were perhaps, the most surprised by the extraordinary success we enjoyed.”

2. Playing to his Strengths: Capital Efficiency. One of the big takeaways from the Innovators by Walter Issacson was that individuals or teams at the nexus of disciplines - primarily where the sciences meet the humanities, often achieved breakthrough success. The classic case study for this is Apple - Steve Jobs had an intense love of art, music, and design and Steve Wozniak was an amazing technologist. Frank has cultivated a cross-discipline strength at the intersection of Sales and Technology. This might be driven by Slootman’s background is in economics. The book has several references to economic terms, which clearly have had an impact on Frank’s thinking. Data Domain espoused capital efficiency: “We traveled alone, made few many-legged sales calls, and booked cheap flights and hotels: everybody tried to save a dime for the company.” The results showed - the business went from $800K of revenue in 2004 to $275 million by 2008, generating $75M in cash flow from operations. Frank’s capital efficiency was interesting and broke from traditional thinking - most people think to raise a round and build something. Frank took a different approach: “When you are not yet generating revenue, conservation of resource is the dominant theme.” Over time, “when your sales activity is solidly paying for itself,” the spending should shift from conservative to aggressive (like Snowflake is doing this now). The concept of sales efficiency is somewhat talked about, but given the recent fundraising environment, is often dismissed. Sales efficiency can be thought of as: “How much revenue do I generate for every $1 spent in sales and marketing?” Looking at the P&L below, we see Data Domain was highly efficient in its sales and marketing activity - the company increased revenue $150M in 2008, despite spending $115M in sales and marketing (a ratio of 1.3x). Contrast this with a company like Slack which spent $403M to acquire $230M of new revenue (a ratio of 0.6x). It gets harder to acquire customers at scale, so this efficiency is supposed to come down over time but best in class is hopefully above 1x. Frank clearly understands when to step on the gas with investing, as both ServiceNow and Snowflake have remained fairly efficient (from a sales perspective at least) while growing to a significant scale.

3. Technology for Technology’s Sake. “Many technologies are conceived without a clear, precise notion of the intended use.” Slootman hits on a key point and one that the tech industry has struggled to grasp throughout its history. So many products and companies are established around budding technology with no use case. We’ve discussed Magic Leap’s fundraising money-pit (still might find its way), and Iridium Communications, the massive satellite telephone that required people to carry a suitcase around to use it. Gartner, the leading IT research publication (which is heavily influenced by marketing spend from companies) established the Technology Hype Cycle, complete with the “Peak of inflated expectations,” and the “Trough of Disillusionment” for categorizing technologies that fail to live up to their promise. There have been several waves that have come and gone: AR/VR, Blockchain, and most recently, Serverless. Its not so much that these technologies were wrong or not useful, its rather that they were initially described as a panacea to several or all known technology hindrances and few technologies ever live up to that hype. Its common that new innovations spur tons of development but also lots of failure, and this is Slootman’s caution to entrepreneurs. Data Domain was attacking a problem that existed already (tape storage) and the company provided what Clayton Christensen would call a sustaining innovation (something that Slootman points out). Whenever things go into “winter state”, like the internet after the dot-com bubble, or the recent Crpyto Winter which is unthawing as I write; it is time to pay attention and understand the relevance of the innovation.

Business Themes

1. Importance of Owning Sales. Slootman spends a considerable amount of this small book discussing sales tactics and decision making, particularly with respect to direct sales and OEM relationships. OEM deals are partnerships with other companies whereby one company will re-sell the software, hardware, or service of another company. Crowdstrike is a popular product with many OEM relationships. The Company drives a significant amount of its sales through its partner model, who re-sell on behalf of Crowdstrike. OEM partnerships with big companies present many challenges: “First of all, you get divorced from your customer because the OEM is now between you and them, making customer intimacy challenging. Plus, as the OEM becomes a large part of your business, for all intents and purposes they basically own you without paying for the privilege…Never forget that nobody wants to sell your product more than you do.” The challenges don’t end there. Slootman points out that EMC discarded their previous OEM vendor in the data deduplication space, right after acquiring Data Domain. On top of that, the typical reseller relationship happens at a 10-20% margin, degrading gross margins and hurting ability to invest. It is somewhat similar to the challenges open-source companies like MongoDB and Elastic have run into with their core software being…free. Amazon can just OEM their offering and cut them out as a partner, something they do frequently. Partner models can be sustainable, but the give and take from the big company is a tough balance to strike. Investors like organic adoption, especially recently with the rise of freemium SaaS models percolating in startups. Slootman’s point is that at some point in enterprise focused businesses, the Company must own direct sales (and relationships) with its customers to drive real efficiency. After the low cost to acquire freemium adopters buy the product, the executive team must pivot to traditional top down enterprise sales to drive a successful and enduring relationship with the customer.

2. In the Thick of Things. Slootman has some very concise advice for CEOs: be a fighter, show some humanity, and check your ego at the door. “Running a startup reduces you to your most elementary instincts, and survival is on your mind most of the time…The CEO is the ‘Chief Combatant,’ warrior number one.” Slootman views the role of CEO as a fighter, ready to be the first to jump into the action, at all times. And this can be incredibly productive for business as well. Tony Xu, the founder and CEO of Doordash, takes time out every month to do delivery for his own company, in order to remain close to the customer and the problems of the company. Jeff Bezos famously still responds and views emails from customers at jeff@amazon.com. Being CEO also requires a willingness to put yourself out there and show your true personality. As Slootman puts it: “People can instantly finger a phony. Let them know who you really are, warts and all.” As CEO you are tasked with managing so many people and being involved in all aspects of the business, it is easy to become rigid and unemotional in everyday interactions. Harvard Business School professor and former leader at Uber distills it down to a simple phrase: “Begin With Trust.” All CEO’s have some amount of ego, driving them to want to be at the top of their organization. Slootman encourages CEO’s to be introspective, and try to recognize blind spots, so ego doesn’t drive day-to-day interactions with employees. One way to do that is simple: use the pronoun “we” when discussing the company you are leading. Though Slootman doesn’t explicitly call it out - all of these suggestions (fighting, showing empathy, getting rid of ego) are meant to build trust with employees.

3. R-E-C-I-P-E for a Great Culture. The last fifth of the book is all focused on building culture at companies. It is the only topic Slootman stays on for more than a few chapters, so you know its important! RECIPE was an acronym created by the employees at Data Domain to describe the company’s values: Respect, Excellence, Customer, Integrity, Performance, Execution. Its interesting how simple and focused these values are. Technology has pushed its cultural delusion’s of grandeur to an extreme in recent years. The WeWork S-1 hilariously started with: “We are a community company committed to maximum global impact. Our mission is to elevate the world’s consciousness.” But none of Data Domain’s values were about changing the world to be a better place - they were about doing excellent, honest work for customers. Slootman is lasered focused on culture, and specifically views culture as an asset - calling it: “The only enduring, sustainable form of differentiation. These days, we don’t have a monopoly for very long on talent, technology, capital, or any other asset; the one thing that is unique to us is how we choose to come together as a group of people, day in and day out. How many organizations are there that make more than a halfhearted attempt at this?” Technology companies have taken different routes in establishing culture: Google and Facebook have tried to create culture by showering employees with unbelievable benefits, Netflix has focused on pure execution and transparency, and Microsoft has re-vamped its culture by adopting a Growth Mindset (has it really though?). Google originally promoted “Don’t be evil,” as part of its Code of Conduct but dropped the motto in 2018. Employees want to work for mission-driven organizations, but not all companies are really changing the world with their products, and Frank did not try to sugarcoat Data Domain’s data-duplication technology as a way to “elevate the world’s consciousness.” He created a culture driven by performance and execution - providing a useful product to businesses that needed it. The culture was so revered that post-acquisition, EMC instituted Data Domain’s performance management system. Data Domain employees were looked at strangely by longtime EMC executives, who had spent years in a big and stale company. Culture is a hard thing to replicate and a hard thing to change as we saw with the Innovator’s Dilemma. Might as well use it to help the company succeed!

Dig Deeper

• How Data Domain Evolved in the Cloud World

• Former Data Domain CEO Frank Slootman Gets His Old Band Back Together at ServiceNow

• The Contentious Take-over Battle for Data Domain: Netapp vs. EMC

• 2009 Interview with Frank Slootman After the Acquisition of Data Domain

October 2020 - Working in Public: The Making and Maintenance of Open Source Software by Nadia Eghbal

This month we covered Nadia Eghbal’s instant classic about open-source software. Open-source software has been around since the late seventies but only recently it has gained significant public and business attention.

Tech Themes

The four types of open source communities described in Working in Public

1. Misunderstood Communities. Open source is frequently viewed as an overwhelmingly positive force for good - taking software and making it free for everyone to use. Many think of open source as community-driven, where everyone participates and contributes to making the software better. The theory is that so many eyeballs and contributors to the software improves security, improves reliability, and increases distribution. In reality, open-source communities take the shape of the “90-9-1” rule and act more like social media than you could think. According to Wikipedia, the "90–9–1” rule states that for websites where users can both create and edit content, 1% of people create content, 9% edit or modify that content, and 90% view the content without contributing. To show how this applies to open source communities, Eghbal cites a study by North Carolina State Researchers: “One study found that in more than 85% of open source projects the research examined on Github, less than 5% of developers were responsible for 95% of code and social interactions.” These creators, contributors, and maintainers are developer influencers: “Each of these developers commands a large audience of people who follow them personally; they have the attention of thousands of developers.” Unlike Instagram and Twitch influencers, who often actively try to build their audiences, open-source developer influencers sometimes find the attention off-putting - they simply published something to help others and suddenly found themselves with actual influence. The challenging truth of open source is that core contributors and maintainers give significant amounts of their time and attention to their communities - often spending hours at a time responding to pull requests (requests for changes / new features) on Github. Evan Czaplicki’s insightful talk entitled “The Hard Parts of Open Source,” speaks to this challenging dynamic. Evan created the open-source project, Elm, a functional programming language that compiles Javascript, because he wanted to make functional programming more accessible to developers. As one of its core maintainers, he has repeatedly been hit with requests of “Why don’t you just…” from non-contributing developers angrily asking why a feature wasn’t included in the latest release. As fastlane creator, Felix Krause put it, “The bigger your project becomes, the harder it is to keep the innovation you had in the beginning of your project. Suddenly you have to consider hundreds of different use cases…Once you pass a few thousand active users, you’ll notice that helping your users takes more time than actually working on your project. People submit all kinds of issues, most of them aren’t actually issues, but feature requests or questions.” When you use open-source software, remember who is contributing and maintaining it - and the days and years poured into the project for the sole goal of increasing its utility for the masses.

2. Git it? Git was created by Linus Torvalds in 2005. We talked about Torvalds last month, who also created the most famous open-source operating system, Linux. Git was born in response to a skirmish with Larry McAvoy, the head of proprietary tool BitKeeper, over the potential misuse of his product. Torvalds went on vacation for a week and hammered out the most dominant version control system today - git. Version control systems allow developers to work simultaneously on projects, committing any changes to a centralized branch of code. It also allows for any changes to be rolled back to earlier versions which can be enormously helpful if a bug is found in the main branch. Git ushered in a new wave of version control, but the open-source version was somewhat difficult to use for the untrained developer. Enter Github and GitLab - two companies built around the idea of making the git version control system easier for developers to use. Github came first, in 2007, offering a platform to host and share projects. The Github platform was free, but not open source - developers couldn’t build onto their hosting platform - only use it. GitLab started in 2014 to offer an alternative, fully-open sourced platform that allowed individuals to self-host a Github-like tracking program, providing improved security and control. Because of Github’s first mover advantage, however, it has become the dominant platform upon which developers build: “Github is still by far the dominant market player: while it’s hard to find public numbers on GitLab’s adoption, its website claims more than 100,000 organizations use its product, whereas GitHub claims more than 2.9 million organizations.” Developers find GitHub incredibly easy to use, creating an enormous wave of open source projects and code-sharing. The company added 10 million new users in 2019 alone - bringing the total to over 40 million worldwide. This growth prompted Microsoft to buy GitHub in 2018 for $7.5B. We are in the early stages of this development explosion, and it will be interesting to see how increased code accessibility changes the world over the next ten years.

3. Developing and Maintaining an Ecosystem Forever. Open source communities are unique and complex - with different user and contributor dynamics. Eghbal tries to segment the different types of open source communities into four buckets - federations, clubs, stadiums, and toys - characterized below in the two by two matrix - based on contributor growth and user growth. Federations are the pinnacle of open source software development - many contributors and many users, creating a vibrant ecosystem of innovative development. Clubs represent more niche and focused communities, including vertical-specific tools like astronomy package, Astropy. Stadiums are highly centralized but large communities - this typically means only a few contributors but a significant user base. It is up to these core contributors to lead the ecosystem as opposed to decentralized federations that have so many contributors they can go in all directions. Lastly, there are toys, which have low user growth and low contributor growth but may actually be very useful projects. Interestingly, projects can shift in and out of these community types as they become more or less relevant. For example, developers from Yahoo open-sourced their Hadoop project based on Google’s File System and Map Reduce papers. The initial project slowly became huge, moving from a stadium to a federation, and formed subprojects around it, like Apache Spark. What’s interesting, is that projects mature and change, and code can remain in production for a number of years after the project’s day in the spotlight is gone. According to Eghbal, “Some of the oldest code ever written is still running in production today. Fortran, which was first developed in 1957 at IBM, is still widely used in aerospace, weather forecasting, and other computational industries.” These ecosystems can exist forever, but the costs of these ecosystems (creation, distribution, and maintenance) are often hidden, especially the maintenance aspect. The cost of creation and distribution has dropped significantly in the past ten years - with many of the world’s developers all working in the same ecosystem on GitHub - but it has also increased the total cost of maintenance, and that maintenance cost can be significant. Bootstrap co-creator Jacob Thornton likens maintenance costs to caring for an old dog: “I’ve created endlessly more and more projects that have now turned [from puppies] into dogs. Almost every project I release will get 2,000, 3,000 watchers, which is enough to have this guilt, which is essentially like ‘I need to maintain this, I need to take care of this dog.” Communities change from toys to clubs to stadiums to federations but they may also change back as new tools are developed. Old projects still need to be maintained and that code and maintenance comes down to committed developers.

Business Themes

1. Revenue Model Matching. One of the earliest code-hosting platforms was SourceForge, a company founded in 1999. The Company pioneered the idea of code-hosting - letting developers publish their code for easy download. It became famous for letting open-source developers use the platform free of charge. SourceForge was created by VA Software, an internet bubble darling that saw its stock price decimated when the bubble finally burst. The challenge with scaling SourceForge was a revenue model mismatch - VA Software made money with paid advertising, which allowed it to offer its tools to developers for free, but meant its revenue model was highly variable. When the company went public, it was still a small and unproven business, posting $17M in revenue and $31M in costs. The revenue model mismatch is starting to rear its head again, with traditional software as a service (SaaS) recurring subscription models catching some heat. Many cloud service and API companies are pricing by usage rather than a fixed, high margin subscription fee. This is the classic electric utility model - you only pay for what you use. Snowflake CEO Frank Slootman (who formerly ran SaaS pioneer ServiceNow) commented: “I also did not like SaaS that much as a business model, felt it not equitable for customers.” Snowflake instead charges based on credits which pay for usage. The issue with usage-based billing has traditionally been price transparency, which can be obfuscated with customer credit systems and incalculable pricing, like Amazon Web Services. This revenue model mismatch was just one problem for SourceForge. As git became the dominant version control system, SourceForge was reluctant to support it - opting for its traditional tools instead. Pricing norms change, and new technology comes out every day, it’s imperative that businesses have a strong grasp of the value they provide to their customers and align their revenue model with customers, so a fair trade-off is created.

2. Open Core Model. There has been enormous growth in open source businesses in the past few years, which typically operate on an open core model. The open core model means the Company offers a free, normally feature limited, version of its software and also a proprietary, enterprise version with additional features. Developers might adopt the free version but hit usage limits or feature constraints, causing them to purchase the paid version. The open-source “core” is often just that - freely available for anyone to download and modify; the core's actual source code is normally published on GitHub, and developers can fork the project or do whatever they wish with that open core. The commercial product is normally closed source and not available for modification, providing the business a product. Joseph Jacks, who runs Open Source Software (OSS) Capital, an investment firm focused on open source, displays four types of open core business model (pictured above). The business models differ based on how much of the software is open source. Github, interestingly, employs the “thick” model of being mostly proprietary, with only 10% of its software truly open-sourced. Its funny that the site that hosts and facilitates the most open source development is proprietary. Jacks nails the most important question in the open core model: “How much stays open vs. How much stays closed?” The consequences can be dire to a business - open source too much and all of a sudden other companies can quickly recreate your tool. Many DevOps tools have experienced the perils of open source, with some companies losing control of the project it was supposed to facilitate. On the flip side, keeping more of the software closed source goes against the open-source ethos, which can be viewed as organizations selling out. The continuous delivery pipeline project Jenkins has struggled to satiate its growing user base, leading to the CEO of the Jenkins company, CloudBees, posting the blog post entitled, “Shifting Gears”: “But at the same time, the incremental, autonomous nature of our community made us demonstrably unable to solve certain kinds of problems. And after 10+ years, these unsolved problems are getting more pronounced, and they are taking a toll — segments of users correctly feel that the community doesn’t get them, because we have shown an inability to address some of their greatest difficulties in using Jenkins. And I know some of those problems, such as service instability, matter to all of us.” Striking this balance is incredibly tough, especially in a world of competing projects and finite development time and money in a commercial setting. Furthermore, large companies like AWS are taking open core tools like Elastic and MongoDB and recreating them in proprietary fashions (Elasticsearch Service and DocumentDB) prompting company CEO’s to appropriately lash out. Commercializing open source software is a never-ending battle against proprietary players and yourself.

3. Compensation for Open Source. Eghabl characterizes two types of funders of open-source - institutions (companies, governments, universities) and individuals (usually developers who are direct users). Companies like to fund improved code quality, influence, and access to core projects. The largest groups of contributors to open source projects are mainly corporations like Microsoft, Google, Red Hat, IBM, and Intel. These corporations are big enough and profitable enough to hire individuals and allow them to strike a comfortable balance between time spent on commercial software and time spent on open source. This also functions as a marketing expense for the big corporations; big companies like having influencer developers on payroll to get the company’s name out into the ecosystem. Evan You, who authored Vue.js, a javascript framework described company backed open-source projects: “The thing about company-backed open-source projects is that in a lot of cases… they want to make it sort of an open standard for a certain industry, or sometimes they simply open-source it to serve as some sort of publicity improvement to help with recruiting… If this project no longer serves that purpose, then most companies will probably just cut it, or (in other terms) just give it to the community and let the community drive it.” In contrast to company-funded projects, developer-funded projects are often donation based. With the rise of online tools for encouraging payments like Stripe and Patreon, more and more funding is being directed to individual open source developers. Unfortunately though, it is still hard for many open source developers to pursue open source on individual contributions, especially if they work on multiple projects at the same time. Open source developer Sindre Sorhus explains: “It’s a lot harder to attract company sponsors when you maintain a lot of projects of varying sizes instead of just one large popular project like Babel, even if many of those projects are the backbone of the Node.js ecosystem.” Whether working in a company or as an individual developer, building and maintaining open source software takes significant time and effort and rarely leads to significant monetary compensation.

Dig Deeper

• List of Commercial Open Source Software Businesses by OSS Capital

• How to Build an Open Source Business by Peter Levine (General Partner at Andreessen Horowitz)

• The Mind Behind Linux (a talk by Linus Torvalds)

• What is open source - a blog post by Red Hat

• Why Open Source is Hard by PHP Developer Jose Diaz Gonzalez

• The Complicated Economy of Open Source

September 2020 - Women of Color in Tech by Susanne Tedrick

This month we dove into Susanne Tedrick’s new book, Women of Color in Tech. Tedrick provides an excellent overview of the challenges many women of color face when trying to enter into and stay in the technology industry. The mix of real-world advice, personal experience, and industry stories combine to form a comprehensive resource for anyone in technology or looking to enter the field.

Tech Themes

1. The Current State. Tedrick starts the book with uncomfortable statistics. Only 26% of computing roles are held by women; Black women hold 3% and Hispanic women hold 2% of computing roles. In addition, the trends aren’t positive - 26% is a 9% decrease since 1990. According to the Ascend Foundation, a Pan-Asian organization for business professionals, from 2007 to 2015, black women experienced a 13% decrease in professional roles in technology. While distressing, there are some green shoots, a 2012 paper by Heather Gonzalez and Jeffrey Kuenzi pointed out that science and engineering graduate program enrollments grew 65%, 55%, and 50% for Hispanic/Latino, American Indian/Alaska Native, and African American students, respectively. So why is this? Tedrick acknowledges that there is no one single answer, instead, its a combination of circumstances starting at early adolescence. Tedrick introduces the idea of “STEM Deserts” or areas where STEM education is not offered. These deserts disproportionally affect high poverty schools (schools where 75% or more of the students are eligible for free lunch and breakfast). Almost half of these schools contain large Black and Hispanic populations. Once women of color arrive at college it gets harder: “Coupling [student debt] with professor’s biases, a lack of meaningful support at home or within their community, and few to no peers with whom they can identify in their academic programs, many young women of color struggle to get through their programs.” For the few that conquer all of these challenges, the workplace introduces a whole new set of issues. Tedrick cites the Kapor Center’s Tech Leavers Study: “Thirty percent of women of color respondents claimed that they were passed over for promotions and 24% report being stereotyped.” According to a Harvard Business Review article written by feminist legal scholar Joan Williams, “77% of black women report having to prove themselves over and over; their success discounted and their expertise questioned.” When you compile all of these challenges throughout a lifetime, it becomes an incredibly difficult journey for black women in tech.

2. Technical Roles and the Building Blocks of the Internet. Tedrick introduces many key organizational roles in technology including business analysis, consulting, data science, information security, product management, project management, software development, technical sales, technical support, user experience design, and web design. After introducing each one, she provides a prescriptive guide for individuals looking to learn more - hitting on key skills, educational requirements, and the latest trends. While I can’t cover every role here, one underappreciated position / sub-segment of technology Tedrick discusses is computer networking. Ultimately, networking was the benefit that unlocked the internet to the masses. Protocols like TCP/IP, VoIP, and HTTP are crucial to the functioning internet. These protocols offer ways for computers to communicate with one another in a consistent manner. The IP (Internet Protocol) provides basic addressing for computers and TCP provides the continual delivery of ordered and reliable bytes from one computer to another in what are called packets. A packet is a pre-defined standard for sending data. VoIP is an extension of this protocol specifically for transcoding audio and video voice signals into packets. HTTP is the way you request the data found at a location: http://techbookofthemonth.com tells the browser to fetch the website at that URL. A lot of basic networking features are typically baked into the operating system, which for most consumers today is Linux. Linux is an open-source operating system that handles all of the things that makes your computer run: memory, CPU, connected devices, graphics, desktop environment, and the ability to run applications. However, Linux programming is still not a commonly learned skill. Tedrick quotes Tameika Reed, a senior infrastructure engineer and founder of Women in Linux: “We have people who are getting degrees and PhDs and so on. . . . When it comes down to Linux, which runs in 90 percent of most companies, and it’s time to troubleshoot something, they don’t know how to troubleshoot the basics of the foundation. I look at Linux as the foundations of getting into tech.” Red Hat, which was acquired by IBM for $34 billion in 2019, offers an enterprise version of Linux which comes with support, guaranteed versioning, and additional security. While computer networking is not a flashy industry, it underpins so much that it remains very interesting.

3. Technology Skills. Chapter six lays out a great way to assess your own skills and understand where you need improvement. These skills can require additional schooling via college, trade schools, or massive-open-online-courses (MOOCs) like Coursera but other ways to complement this learning include hackathons, conferences, networking, and volunteering. Tedrick wanted to improve her own skills so she volunteered to help set up a conference: “To improve my web design, WordPress, and conference organization skills, I volunteered my services for a leadership conference being held by IEEE Women in Engineering for four months in 2016. I helped to build and maintain the event website using WordPress, as well as helped people with registration and refunds. This experience greatly improved my understanding of web design, search engine optimization (SEO), event promotion, and collaborating with remote teams (I was based in Chicago, while much of the event team and registrants were based in and around Detroit, Michigan). In the process, I learned more about the different fields of engineering and broadened my network with incredible engineering students and professionals.” The book is incredibly helpful for skill-building - it gives you the exact things you need to learn to be successful in specific positions and it even clears up some myths of the technology industry. One common myth is that “Tech Careers Require Constant, Hands-On Programming.” As evidenced by the myriad of roles listed above, the technology industry involves so much more than programming. In addition, Tech careers exist outside of the top five big-name companies like Microsoft, Google, Facebook, Amazon, and Netflix and even exist at non-tech companies too. One critical skill that Tedrick highlights for a number of different technical roles is communication. Communication is not often mentioned when discussing software engineering, but Tedrick picks up on its huge importance, and the necessary ability to communicate to technical and non-technical audiences. On top of sharing with non-technical audiences, engineers need to know how to communicate accurate deadlines to managers and ask for help when unsure of how to implement a challenging new feature. Communication is not just speaking, its also listening and empathetically understanding where others are coming from, to establish common ground and grow mutual understanding.

Business Themes

1. Tedrick’s Story and Grit. Susanne’s personal stories appear throughout the book and perfectly complement the substantial amount of how-to information and advice. Chapter nine talks about the daily challenges of many women of color in tech and their lack of support to solve those challenges. Susanne’s own story is one of incredible determination and perseverance: “My mother had been diagnosed with a brain tumor when I was very young. This initial tumor led to more health issues for her over the years, including a decline into dementia, a loss of some of her short-term memory, and impacted mobility. The latter half of her life was spent in and out of hospitals, having numerous operations and medical incidents. My father was left to care for me and my sister, while also supporting several other family members in one house. Between work and caring for my mom, he couldn’t be around much, and fortunately, some nearby relatives and family friends helped to raise and care for us. As there was only one income (already too high to qualify for most public assistance programs) and my mother needed many medications, there were times where a choice had to be made between eating, having phone service, making critical house repairs, or having the lights stay on. This went on for nearly two decades, up until my mother’s death. It wasn’t until well into my adult life that I realized I was living in ‘survival mode’ and just trying to exist. I was spending most of my time trying to find happiness in my life; having a meaningful and engaging career was not an immediate goal or one I thought was achievable for me.” After working in administrative roles and taking on a couple of different jobs, she managed to attend Northwestern while continuing to work. “I used much of my vacation and holiday time from work not only to study but to attend conferences, interviews, boot camps, and the like. I did homework during lunch breaks or before the start of a full workday, only to go to class for several hours in the same evening.” Tedrick has risen to be an award-winning public speaker, author, and technologist at IBM (oh and she’s also run a couple of marathons). Her story is truly inspirational!

2. Culture, Intersectionality, and Bias. We’ve discussed Clayton Christensen’s Resources-Processes-Values framework before and how they impact the discovery of emerging technologies. Often the processes create a culture and set of habitual routines that can be difficult to change. The culture of big technology has been anti-women for a long time. As Tedrick points out, women of color not only have to deal with this challenge but also repeated racial abuse, microaggressions, and tokenism. Kimberlé Crenshaw called this intersectionality, or the idea that a person's social identities (e.g., gender, caste, sex, race, class, sexuality, religion, disability, physical appearance, height, etc.) combine to create unique modes of discrimination and privilege. Tedrick points out an example of this with Sheryl Sandberg’s famous novel, Lean In. The book became a bestseller and made Sheryl Sandberg a household name (to those that didn’t already know her as COO of Facebook). However, as Tedrick points out: “The central problem with the book, which Sandberg herself later acknowledged, is that it assumed that the reader had certain privileges that many women of color do not have: completely supportive households that don’t require much of their time and attention, work cultures that allow expression of their thoughts without fear of being fired or held back, and access to career mentors to help them become stronger leaders. This lack of understanding of where the reader may be coming from and experiencing caused much of Sandberg’s advice to ring hollow for women of color.” The book ignores the structural challenges that many women of color face. Michelle Obama put it bluntly: “It’s not always enough to lean in, because that shit doesn’t work all the time.” When building culture at an organization, it’s super important to think about how that culture addresses each social identity at the company. Furthermore, it’s not the responsibility of diverse individuals to build that culture. Tedrick sums it up well: “Addressing tokenism, much like addressing bias, unfortunately, is not something that you alone can address. It is also not our responsibility to address this. It is up to organizations and their leaders to correct and address tokenism so that women of color are fully engaged.”

3. Negotiating Compensation. Understanding pay and compensation are critical to understanding any job offer. Frequently job candidates are remiss to ask for additional compensation because they fear retribution like the offer is pulled and given to someone else and worry about sounding greedy before even joining a new company. As Susanne found out after receiving her first traditional job, this can lead to lower salaries, especially when adjusting for location. In addition, Susanne points out the enormous gender pay gap that occurs at organizations: “It’s no secret that women—and specifically, women of color—are underpaid in about every industry, not just tech. While it is on companies to fix their approaches to compensation, it is our right and duty to demand fair compensation for our work.” A study of the technology industry done by job search marketplace, Hired, shows that black women were paid $0.89 on the dollar compared to white males. This is the lowest across White, Asian, Black, and Hispanic men and women in the technology sector. For LGBTQI+ individuals, the wage gap is $0.90 to $1 of compensation for non-LGBTQI+. While pay gap detail for black LGBTQI+ community is under-studied, according to The National LGBTQ Task Force’s 2011, 48% of trans and gender non-conforming black individuals experienced discrimination in the hiring process. Outside of the technology industry, the pay gap is even more stark with Black women earning $0.62 for every dollar earned by a White male. To address many of these challenges, and ensure that candidates get as close to a fair offer as possible, Tedrick lays out a framework for considering a new job, from pay to benefits to location. Tedrick advises individuals to first research local salaries for the role they are taking on. Armed with data, Tedrick suggests candidates try to be confident, respectful, and flexible in all discussions and to emphasize the unique value they bring to the organization.

Dig Deeper

• Work Smart & Start Smart: Salary Negotiation for Women of Color

• Anita Borg and the history of one of the largest professional organizations for women in technology

• How the World’s most prevalent operating system was built by a 21-year old in Finland

• Black Girls Code: Empowering Young Black Women to Become Innovators

• Tedrick’s Twitter, website, and talk with the Women’s National Book Association

August 2020 - Venture Deals by Brad Feld and Jason Mendelson

This month we checked out an excellent book for founders, investors, and those interested in private company financings. The book hits on a lot of the key business and legal terms that aren’t discussed in typical startup books, making it useful no matter what stage of the entrepreneurial journey you are on.

Tech Themes

1. The Rise of Founder Friendly VC. Writing on his blog, Feld Thoughts, which was the original genesis for Venture Deals, Brad Feld mentioned that: “From 2010 forward, the entire VC market shifted into a mode that many describe as ‘founder friendly.’ Investor reputation mattered at both the angel and VC level.” In the 80’s and 90’s, because there was so little competition among venture capital firms, it was common for firms to dictate terms to company founders. The VC firms were the ones with the cash, and the founders didn’t have many options to choose from. If you wanted to build a big, profitable, public company, the only way to get there was by taking venture capital money. This trend started to unwind during the internet bubble, when founders started to maintain more and more of their businesses before the IPO. In fact, as this Harvard Business Review article points out, it was actually common to fire the founder/CEO prior to a public offering in favor of more seasoned leaders. This trend was bucked by Netscape, which eschewed traditional wisdom, going public less than a year from founding, with an unprofitable business. The Netscape IPO was clearly a royal coming-together of technology history. Tracing it all the way back - George Winthrop Fairchild started IBM in 1911; in the late 50’s, Arthur Rock convinced Fairchild’s son, Sherman to fund the traitorous eight (eight employees who left competitor Shockley Semiconductor) to start Fairchild Semiconductor; Eugene Kleiner (one of the traitorous eight) starts Kleiner Perkins, a venture capital firm that eventually invested in Netscape. Kleiner Perkins would also invest in Google (frequently regarded as one of the best and riskiest startup investments ever). Google was the first internet company to go public with a dual-class share structure where the founders would own a disproportionate amount of the voting rights of the company. Marc Andreessen, the founder of Netscape, loved this idea and eventually launched his own venture capital firm called Andreessen Horowitz, which ushered in a new generation of founder-friendly investing. At one point Andreessen was even quoted saying: “It is unsafe to go public today without a dual-class share structure.” Some notable companies with dual class shares include several Andreessen companies such as Facebook, Zynga, Box, and Lyft. Recently some have questioned whether founder friendly terms have pushed too far with some major flameouts from companies with the structure including Theranos, WeWork, and Uber.

2. How to Raise Money. Feld has several recommendations for fundraising that are important including having a target round size, demo, financial projections, and VC syndicate. Feld contends that CEOs who offer a range of varying round sizes to VC’s don’t really understand their business goals and use of proceeds. By having a concrete round size it shows that the CEO understands roughly how much money it will take to get to the next milestone or said another way, it shows the CEO understands the runway (in months) needed to build that new product or feature. It shows command of the financing and vision of the business. Feld encourages founders to provide a demo, because: “while never required, many investors respond to things we can play with, so even if you are an early stage company, a prototype or demo is desirable.” Beyond the explicit point here, the demo shows confidence in the product and at least some ability to sell, which is obviously a key aspect in eventually scaling the business. Another aspect of scaling the business is the financial model, but as Feld states, “the only thing that can be known about a pre-revenue company’s financial projections is that they are wrong.” While the numbers are meaningless for really early stage companies, for those that have a few customers it can be helpful to get a sense of long-term gross margins and aspects of the company you hope to invest in and / or change over time. Lastly, Feld gives advice for building a VC syndicate, or group of VC investors. Frequently lead investors will commit a certain dollar amount of the round, and it will be up to the founder/CEO to go find a way to build out the round. This can be incredibly challenging as detailed by Moz founder, Rand Fishkin, who thought he had a deal in hand only to see it be taken away. There are multiple bids in the VC fundraising process, one called an indication of interest, which is non-binding and normally provides a range on valuation, one called a letter of intent, which is slightly more detailed and may include legal terms of the deal such as board representation, liquidation preference, and governance terms, and then final legal documentation. A lot of time, the early bids can be withdrawn based off of poor market feedback or when a company misses its financial projections (like Moz did in its process). Understanding the process and the materials needed to complete the deal is helpful at setting expectations for founders.

3. Warrants, SPACs, and IPOs. With SPACMania in full-swing, we wanted to dive into SPACs and see how they work. We’ve discussed SPACs before, with regards to Chamath’s Social Capital merger with Virgin Galactic. But how do traditional SPAC financings work and why is there a rush of famous people, such as LinkedIn founder Reid Hoffman, to raise them? A SPAC or Specialty Purpose Acquisition Company is a blank-check company which goes public with the goal of acquiring a business, thereby taking it public. SPACs can be focused on industry or size of company and they are most frequently led by operational leaders and / or private equity firms. The reason SPACs have been gaining in popularity is that public markets investors are seeking more risk and a few high profile SPAC deals, namely DraftKings and Nikola, have traded better than expected. Most companies that are going public today are older, more mature businesses, and the public markets have been generally favorable to somewhat suspect ventures (Nikola is an electric truck company that has never produced a single truck, but is worth $14B on hype alone). VC firms and companies see the ability to get outsized returns on their investments because so many people are clamoring to find returns above the basically 0% offered by treasury bonds. The S&P 500 P/E ratio is now at around 26x compared to a historical average around 16x, meaning the market seems to be overvalued compared to prior times. SPACs typically come with an odd structure. A unit in a SPAC normally consists of one common share of stock and one warrant, which is the ability to purchase shares for $0.01 after a SPAC merges with its target company. The founders of the SPAC also receive founder shares, normally 20% of the business. Once the target is found, SPACs will often coordinate a PIPE (Private Investment in Public Equity), where a large private investor will invest mainly primary (cash to the balance sheet) capital into the business. This has emerged as a hip, new alternative to traditional IPOs, keeping with the theme of innovation in public offerings like direct listings, however, its unclear that this really benefits the company going public. Often the merged companies are the subject of substantial dilution by the SPAC sponsors and PIPE investors, lowering the overall equity piece management maintains. However, given the somewhat high valuations companies are receiving in the public markets (Zoom at 80x+ LTM Revenue, Shopify at 59x LTM Revenue), it may be worth the dilution.

Business Themes

1. How VC’s Make Money. In VC, the typical fund structure includes a general partnership (GP) and limited partners (LPs). The GP is the investors at the VC firm and the limited partners are the institutional investors that provide the money for the VC firm to invest. A typical structure involves the GP investing 1% of their own money (99% comes from LPs) and then getting paid an annual 2% management fee as well as 20% carried interest, or the profit made from investments. Using the example from the book: “Start with the $100 million fund. Assume that it's a successful fund and returns 3× the capital, or $300 million. In this case, the first $100 million goes back to the LPs, and the remaining profit, or $200 million, is split 80 percent to the LPs and 20 percent to the GPs. The VC firm gets $40 million in carried interest and the LPs get the remaining $160 million. And yes, in this case everyone is very happy.” Understanding how investors make money can help the entrepreneur better understand why VC’s pressure companies. As Feld points out, sometimes VC’s are trying to raise a new fund or have invested the majority of the fund already and thus do not care as much about some investments.

2. Growth at all costs. There has been a concerted focus in VC on the get big quick motto. Nobody better exemplifies this than Masayoshi Son and the $100B VC his firm Softbank raised a few years ago. With notable big bets on current losers like WeWork and Oyo, which are struggling during this pandemic, its unclear whether this motto remains true. Eric Paley, a Managing Partner at Founder Collective, expertly quantifies the potential downsides of a risk-it-all strategy: “Investors today have overstuffed venture funds, and lots of capital is sloshing around the startup ecosystem. As a result, young startups with strong teams, compelling products and limited traction can find themselves with tens of millions of dollars, but without much real validation of their businesses. We see venture investors eagerly investing $20 million into a promising company, valuing it at $100 million, even if the startup only has a few million in net revenue. Now the investors and the founders have to make a decision — what should determine the speed at which this hypothetical company, let’s call it “Fuego,” invests its treasure chest of money in the amazing opportunity that motivated the investors? The investors’ goal over the next roughly 24 months is for the company to become worth at least three times the post-money valuation — so $300 million would be the new target pre-money valuation for Fuego’s next financing. Imagine being a company with only a few million in sales, with a success hurdle for your next round of $300 million pre-money. Whether the startup’s model is working or not, the mantra becomes ‘go big or go home.’” This issue is key when negotiating term sheets with investors and understanding board dynamics. As Feld calls out: “The voting control issues in the early stage deals are only amplified as you wrestle with how to keep control of your board when each lead investor per round wants a board seat. Either you can increase your board size to seven, nine, or more people (which usually effectively kills a well-functioning board), or more likely the board will be dominated by investors.” As an entrepreneur, you need to be cognizant of the pressure VC firms will put on founders to grow at high rates, and this pressure is frequently applied by a board. Often late stage startups have 10 people+ on their board. UiPath, a private venture-backed startup that has raised over $1B and is valued at $10B, has 12 people on its board. With all of the different firms having their own goals, boards can become ineffective. Whenever startups are considering fundraising, it’s important to realize the person you are raising from will be an ongoing member of the company and voice on the board and will most likely push for growth.

3. Liquidation Preference. One of the least talked about terms in venture capital among startup circles is liquidation preference. Feld describes liquidation preference as: “a certain multiple of the original investment per share is returned to the investor before the common stock receives any consideration.” Startup culture has tended to view fundraises as stamps of approval and success, but thats not always the case. As the book discusses, preference can lead to very negative outcomes for founders and employes. For example, let’s say a company at $10M in revenue raises $100 million with a 1x liquidation preference at a $400 million pre-money valuation ($500M post money). The company is pressured by its VCs to grow quickly but it has issues with product market fit and go to market; five years go by and the company is at $15M in revenue. At this point the VCs are not interested in funding any more, and the board decides to try to sell the company. A buyer offers $80 million and the board accepts it. At this point, all $80M has to go back to the original investors who had the 1x liquidation preference. All of the common stockholders and the founders, get nothing. Its not the desired outcome by any means, but its important to know. Some companies have not heeded this advice and continued to raise at massive valuations including Notion which has raised $10M at a $800 million valuation, despite being rumored to be around $15M in revenue. The company raised at a $1.6B valuation (an obvious 2x) after being rumored to be at $30M in revenue. While not taking dilution is nice as a founder, it also sets up a massive hurdle for the company and seriously cramps returns. A 3x return (which is low for VC investors) means selling the company for $4.8B, which is no small feat.

Dig Deeper

• Feld Thoughts: Brad Feld’s Blog

• The Ultimate Guide to Liquidation Preferences

• Startup Boards: A deep dive by Mark Suster, VC at Upfront Ventures

• The meeting that showed me the truth about VCs on TechCrunch

• SPOTAK: The Six Traits Marc Lore Looks for When Hiring

July 2020 - Innovator's Dilemma by Clayton Christensen

This month we review the technology classic, the Innovator’s Dilemma, by Clayton Christensen. The book attempts to answer the age-old question: why do dominant companies eventually fail?

Tech Themes

1. The Actual Definition of Disruptive Technology. Disruption is a term that is frequently thrown around in Silicon Valley circles. Every startup thinks its technology is disruptive, meaning it changes how the customer currently performs a task or service. The actual definition, discussed in detail throughout the book, is relatively specific. Christensen re-emphasizes this distinction in a 2015 Harvard Business Review article: "Specifically, as incumbents focus on improving their products and services for their most demanding (and usually most profitable) customers, they exceed the needs of some segments and ignore the needs of others. Entrants that prove disruptive begin by successfully targeting those overlooked segments, gaining a foothold by delivering more-suitable functionality—frequently at a lower price. Incumbents, chasing higher profitability in more-demanding segments, tend not to respond vigorously. Entrants then move upmarket, delivering the performance that incumbents' mainstream customers require, while preserving the advantages that drove their early success. When mainstream customers start adopting the entrants' offerings in volume, disruption has occurred." The book posits that there are generally two types of innovation: sustaining and disruptive. While disruptive innovation focuses on low-end or new, small market entry, sustaining innovation merely continues markets along their already determined axes. For example, in the book, Christensen discusses the disk drive industry, mapping out the jumps which pack more memory and power into each subsequent product release. There is a slew of sustaining jumps for each disruptive jump that improves product performance for existing customers but doesn't necessarily get non-customers to become customers. It is only when new use cases emerge, like rugged disk usage and PCs arrive, that disruption occurs. Understanding the specific definition can help companies and individuals better navigate muddled tech messaging; Uber, for example, is shown to be a sustaining technology because its market already existed, and the company didn't offer lower prices or a new business model. Understanding the intricacies of the definition can help incumbents spot disruptive competitors.

2. Value Networks. Value networks are an underappreciated and somewhat confusing topic covered in The Innovator's Dilemma's early chapters. A value network is defined as "The context within which a firm identifies and responds to customers' needs, solves problems, procures input, reacts to competitors, and strives for profit." A value network seems all-encompassing on the surface. In reality, a value network serves to simplify the lens through which an organization must make complex decisions every day. Shown as a nested product architecture, a value network attempts to show where a company interacts with other products. By distilling the product down to its most atomic components (literally computer hardware), we can see all of the considerations that impact a business. Once we have this holistic view, we can consider the decisions and tradeoffs that face an organization every day. The takeaway here is that organizations care about different levels of performance for different products. For example, when looking at cloud computing services at AWS, Azure, or GCP, we see Amazon EC2 instances, Azure VMs, and Google Cloud VMs with different operating systems, different purposes (general, compute, memory), and different sizes. General-purpose might be fine for basic enterprise applications, while gaming applications might need compute-optimized, and real-time big data analytics may need a memory-optimized VM. While it gets somewhat forgotten throughout the book, this point means that organizations focused on producing only compute-intensive machines may not be the best for memory-intensive, because the customers of the organization may not have a use for them. In the book's example, some customers (of bigger memory providers) looked at smaller memory applications and said there was no need. In reality, there was massive demand in the rugged, portable market for smaller memory disks. When approaching disruptive innovation, it's essential to recognize your organization's current value network so that you don't target new technologies at those who don't need it.

3. Product Commoditization. Christensen spends a lot of time describing the dynamics of the disk drive industry, where companies continually supplied increasingly smaller drives with better performance. Christensen's description of commoditization is very interesting: "A product becomes a commodity within a specific market segment when the repeated changes in the basis of competition, completely play themselves out, that is, when market needs on each attribute or dimension of performance have been fully satisfied by more than one available product." At this point, products begin competing primarily on price. In the disk drive industry, companies first competed on capacity, then on size, then on reliability, and finally on price. This price war is reminiscent of the current state of the Continuous Integration / Continuous Deployment (CI/CD) market, a subsegment of DevOps software. Companies in the space, including Github, CircleCI, Gitlab, and others are now competing primarily on price to win new business. Each of the cloud providers has similar technologies native to their public cloud offerings (AWS CodePipeline and CloudFormation, GitHub Actions, Google Cloud Build). They are giving it away for free because of their scale. The building block of CI/CD software is git, an open-source version control system founded by Linux founder Linus Torvalds. With all the providers leveraging a massive open-source project, there is little room for true differentiation. Christensen even says: "It may, in fact, be the case that the product offerings of competitors in a market continue to be differentiated from each other. But differentiation loses its meaning when the features and functionality have exceeded what the market demands." Only time will tell whether these companies can pivot into burgeoning highly differentiated technologies.

Business Themes

1. Resources-Processes-Value (RPV) Framework. The RPV framework is a powerful lens for understanding the challenges that large businesses face. Companies have resources (people, assets, technology, product designs, brands, information, cash, relationships with customers, etc.) that can be transformed into greater value products and services. The way organizations go about converting these resources is the organization's processes. These processes can be formal (documented sales strategies, for example) or informal (culture and habitual routines). Processes are the big reasons organizations struggle to deal with emerging technologies. Because culture and habit are ingrained in the organization, the same process used to launch a mature, slow-growing market may be applied to a fast-growing, dynamic sector. Christensen puts it best: "This means the very mechanisms through which organizations create value are intrinsically inimical to change." Lastly, companies have values, or "the standards by which employees make prioritization decisions." When there is a mismatch between the resources, processes, and values of an organization and the product or market that an organization is chasing, its rare the business can be successful in competing in the disruptive market. To see this misalignment in action, Christensen describes a meeting with a CEO who had identified the disruptive change happening in the disk-drive market and had gotten a product to market to meet the growing market. In response to a publication showing the fast growth of the market, the CEO lamented to Christensen: "I know that's what they think, but they're wrong. There isn't a market. We've had that drive in our catalog for 18 months. Everyone knows we've got it, but nobody wants it." The issue was not the product or market demand, but the organization's values. As Christensen continues, "But among the employees, there was nothing about an $80 million, low-end market that solved the growth and profit problems of a multi-billion dollar company – especially when capable competitors were doing all they could to steal away the customers providing those billions. And way at the other end of the company there was nothing about supplying prototype companies of 1.8-inch drives to an automaker that solved the problem of meeting the 1994 quotas of salespeople whose contacts and expertise were based so solidly in the computer industry." The CEO cared about the product, but his team did not. The RPV framework helps evaluate large companies and the challenges they face in launching new products.

2. How to manage through technological change. Christensen points out three primary ways of managing through disruptive technology change: 1. "Acquire a different organization whose processes and values are a close match with the new task." 2. "Try to change the processes and values of the current organization." 3. "Separate out an independent organization and develop within it the new processes and values that are required to solve the new problem." Acquisitions are a way to get out ahead of disruptive change. There are so many examples but two recent ones come to mind: Microsoft's acquisition of Github and Facebook's acquisition of Instagram. Microsoft paid a whopping $7.5B for Github in 2018 when the Github was rumored to be at roughly $200M in revenue (37.5x Revenue multiple!). Github was undoubtedly a mature business with a great product, but it didn't have a ton of enterprise adoption. Diane Greene at Google Cloud, tried to get Sundar Pichai to pay more, but he said no. Github has changed Azure's position within the market and continued its anti-Amazon strategy of pushing open-source technology. In contrast to the Github acquisition, Instagram was only 13 employees when it was acquired for $1B. Zuckerberg saw the threat the social network represented to Facebook, and today the acquisition is regularly touted as one of the best ever. Instagram was developing a social network solely based on photographs, right at the time every person suddenly had an excellent smartphone camera in their pocket. The acquisition occurred right when the market was ballooning, and Facebook capitalized on that growth. The second way of managing technological change is through changing cultural norms. This is rarely successful, because you are fighting against all of the processes and values deeply embedded in the organization. Indra Nooyi cited a desire to move faster on culture as one of her biggest regrets as a young executive: "I’d say I was a little too respectful of the heritage and culture [of PepsiCo]. You’ve got to make a break with the past. I was more patient than I should’ve been. When you know you have to make a change, at some point you have to say enough is enough. The people who have been in the company for 20-30 years pull you down. If I had to do it all over again, I might have hastened the pace of change even more." Lastly, Christensen prescribes creating an independent organization matched to the resources, processes, and values that the new market requires. Three great spin-out, spin-in examples with different flavors of this come to mind. First, Cisco developed a spin-ins practice whereby they would take members of their organization and start a new company that they would fund to develop a new process. The spin-ins worked for a time but caused major cultural issues. Second, as we've discussed, one of the key reasons AWS was born was that Chris Pinkham was in South Africa, thousands of miles away from Amazon Corporate in Seattle; this distance and that team's focus allowed it to come up with a major advance in computing. Lastly, Mastercard started Mastercard Labs a few years ago. CEO Ajay Banga told his team: "I need two commercial products in three years." He doesn't tell his CFO their budget, and he is the only person from his executive team that interacts with the business. This separation of resources, processes, and values allows those smaller organizations to be more nimble in finding emerging technology products and markets.

3. Discovering Emerging Markets.

   The resources-processes-values framework can also show us why established firms fail to address emerging markets. Established companies rely on formal budgeting and forecasting processes whereby resources are allocated based on market estimates and revenue forecasts. Christensen highlights several important factors for tackling emerging markets, including focusing on ideas, failure, and learning. Underpinning all of these ideas is the impossibility of predicting the scale and growth rate of disruptive technologies: "Experts' forecasts will always be wrong. It is simply impossible to predict with any useful degree of precision how disruptive products will be used or how large their markets will be." Because of this challenge, relying too heavily on these estimates to underpin financial projections can cause businesses to view initial market development as a failure or not worthy of the companies time. When HP launched a new 1.3-inch disk drive, which could be embedded in PDAs, the company mandated that its revenues had to scale up to $150M within three years, in line with market estimates. That market never materialized, and the initiative was abandoned as a failed investment. Christensen argues that because disruptive technologies are threats, planning has to come after action, and thus strategic and financial planning must be discovery-based rather than execution-based. Companies should focus on learning their customer's needs and the right business model to attack the problem, rather than plan to execute their initial vision. As he puts it: "Research has shown, in fact, that the vast majority of successful new business ventures, abandoned their original business strategies when they began implementing their initial plans and learned what would and would not work." One big fan of Christensen's work is Jeff Bezos, and its easy to see why with Amazon's focus on releasing new products in this discovery manner. The pace of product releases is simply staggering (~almost one per day). Bezos even talked about this exact issue in his 2016 shareholder letter: "The senior team at Amazon is determined to keep our decision-making velocity high. Speed matters in business – plus a high-velocity decision making environment is more fun too. We don't know all the answers, but here are some thoughts. First, never use a one-size-fits-all decision-making process. Many decisions are reversible, two-way doors. Those decisions can use a light-weight process. For those, so what if you're wrong? I wrote about this in more detail in last year's letter. Second, most decisions should probably be made with somewhere around 70% of the information you wish you had. If you wait for 90%, in most cases, you're probably being slow." Amazon is one of the first large organizations to truly embrace this decision-making style, and clearly, the results speak for themselves.

Dig Deeper

• What Jeff Bezos Tells His Executives To Read

• Github Cuts Subscription Price by More Than Half

• Ajay Banga Opening Address at MasterCard Innovation Forum 2014

• Clayton Christensen Describing Disruptive Innovation

• Why Cisco’s Spin-Ins Never Caught On

June 2020 - Bad Blood by John Carreyrou

This month we review John Carreyrou’s chilling story of the epic meltdown of a company, Theranos. We explore bad decision making, the limits of technology and the importance of strong corporate governance. The saddest thing and the reason Bad Blood hits so hard is that Theranos was a startup that seemed to have everything: a breakthrough blood analyzer, tons of funding, excellent board representation, and a smart, visionary female CEO. But underneath, it was a twisted cult of distrust with an evil leader.

Tech Themes

1. The limits of technology. Sometimes technology sounds too good to be true. Theranos’ Edison and miniLab blood analyzers were supposed to tell you everything you could ever want to know about your blood. But they didn’t work and never had a shot to work. Stanford professor Phyllis Gardener even told Elizabeth Holmes (Theranos’ founder/CEO) early-on that an early patch-like design of the product would never work: “[Holmes] just kind of blinked and nodded and left. It was just a 19-year-old talking who’d taken one course in microfluidics, and she thought she was gonna make something of it.” It was debunked by almost every scientist as wild fantasy even prior to its commercial use and subsequent fall from grace. There is something so human about wanting to believe there are no limits to technology. In today’s day of fake technology marketing, it’s easy for messaging to slowly take over a company if left unchecked. Think about Snap’s famous declaration, “Snap Inc. is a camera company.” or Dropbox’s S-1 mission statement: “Unleash the world’s creative energy by designing a more enlightened way of working.” These statements ignore what these businesses fundamentally do - advertising and storage. Sometimes there are massive leaps forward, like the transistor, networked computing, and the internet, but even these took many many years to push to fruition. When humans hear a compelling pitch, it is natural to want to remove those limits of technology because the result is so astounding, but we have to remain skeptical or risk another Theranos.

2. The reality distortion field. Elizabeth Holmes was obsessed with Steve Jobs. Mired in this deep fixation, she also managed to subscribe to one of Jobs’ interesting habits: the reality-distortion field. While we’ve discussed the reality distortion field before in relation to Jobs, Holmes seemed to take it to a new level. Jobs would demand something incredible be done and a lot of times his amazing team could come up with the solution. Holmes also believed this but failed to consider two things: fundamental biology and her team. Biology, at its core, is just not as flexible as the hardware and software that Apple was building. Jobs demanded an excellent product, Holmes demanded a biological impossibility. Beyond searching to enable a biological impossibility, which to be frank, can pop up after years of research (see CRISPR), Holmes operated the Theranos cult as a dictator, ruthlessly seeking out dissenters and punishing or firing them. While Jobs challenged his team repeatedly while being a huge asshole, the team, for the most part, stayed in tact (Phil Schiller, Tony Fadell, Jony Ive, Scott Forstall, and Eddy Cue). There were certainly those who got fired or left, but Holmes active rooting out of non-believers severely limited the chances of success at the company. The additional levels of secrecy were even extreme for a stealth technology startup. Startup founders need to drink the kool-aid sometimes, it comes with being visionary, but getting so drunk on power and image can only lead to personal and business demise as was the case with Theranos.

3. When startups turn bad. Tons of startups fail, but only a few turn truly malicious. Theranos was one of those few. The company tested people’s blood and gave individuals fake, untested medical results, including indicators of cancer diagnoses! Even when reviewing other major business failures and frauds - Jeff Skilling at Enron and Bernie Madoff’s Ponzi Scheme - nothing compares to Theranos. While it could be argued that Enron and Madoff’s schemes did more and broader financial hurt to society, at least they were never physically endangering individuals. The only comparisons that may be warranted are Boeing and the Fyre Festival. The brainchild of famous clown, Billy McFarland, the Fyrefest certainly endangered people by marooning them on an island with little food. Furthermore, Boeing’s incredibly incoherent internal review process which knowingly led to the production of a faulty airline software system, also endangered people - including two flights that crashed because of its system. Did Elizabeth Holmes set out to build a dangerous device, knowingly defraud investors, and endanger the public? Probably not. It was one decision after another. It was firing CFO Henry Mosley who called out fake projections; it was hiring Boies Schiller to pressure former employees; it was enlisting Sunny Balwani to “run” the company. It was what Clayton Christensen calls marginal thinking - the idea that the incremental bad decision or the incremental costs of doing something frequently outweigh the full costs of doing something. The incremental cost of firing the CFO who wouldn’t make fake numbers was simply easier than facing the difficult reality that the product sucked, and they had pushed through too much investor money to start again. When things turn bad, at startups or other businesses, a trail of marginal decision making can normally be found.

Business Themes

1. The Pressure to Succeed. Stress seems to be a part of business, but the pressure can sometimes get too big to handle. Public companies, in particular, face growth targets from wall street analysts and investors. One earnings miss or even a more modest beat than expected can completely derail a stock (See pluralsight and alteryx graphs to the right). Public company CEOs and CFOs can be fired or have compensation withheld for poor stock performance. So when a young hot biotechnology startup wanted to launch a partnership with Walgreens, Dr. J and the Walgreens team were more than ready to fast track the potential partnership. Despite not being allowed to use the bathroom, see the lab or see a partial demo of the product, Walgreens pushed through a deal so that longtime competitor, CVS, wouldn’t get the deal. As then head of the Theranos/Walgreens pilot said, "We can’t not pursue this. We can’t risk a scenario where CVS has a deal with them in six months and it ends up being real.” When the partnership was announced, even the press release sounded oddly formulaic: “Theranos’ proprietary laboratory infrastructure minimizes human error through extensive automation to produce high quality results.” There was no demo. There was no product. There was only pressure at Walgreens to beat CVS and pressure at Theranos to make something from a fake device.

2. The Importance of Corporate Governance. Corporate Governance has historically rarely been discussed outside of academic settings but has come into sharper focus over the past few years. Some have recently tried to bring some of the prominent corporate governance issues such as member compensation and option grants for executives to the forefront. Warren Buffet even commented on boards in his 2019 annual shareholder letter: “Director compensation has now soared to a level that inevitably makes pay a subconscious factor affecting the behavior of many non-wealthy members. Think, for a moment, of the director earning $250,000-300,000 for board meetings consuming a pleasant couple of days six or so times a year. And job security now? It’s fabulous. Board members may get politely ignored, but they seldom get fired. Instead, generous age limits – usually 70 or higher – act as the standard method for the genteel ejection of directors.” Boards are meant to help guide the company through strategic challenges, ensure the business is focused on the right things, and evaluate the CEO. Theranos’ Board of Directors was a laughable hodgepodge of old white men: George P. Shultz (former U.S. Secretary of State), William Perry (former U.S. Secretary of Defense), Henry Kissinger (former U.S. Secretary of State), Sam Nunn (former U.S. Senator), Bill Frist (former U.S. Senator and heart-transplant surgeon), Gary Roughead (Admiral, USN, retired), James Mattis (General, USMC), Richard Kovacevich (former Wells Fargo Chairman and CEO), and Riley Bechtel. The average age of the directors in 2012 was ~72 years old and few of these men could offer real strategic guidance in pursuing novel biotechnology. On top of that, as Carreyrou points out, “In December 2013, [Holmes] forced through a resolution that assigned one hundred votes to every share she owned, giving her 99.7% of the voting rights.” George Shultz even said later in a deposition, “We never took any votes at Theranos. It was pointless. Elizabeth was going to decide whatever she decided.” The episode brings more clarity to those CEOs and companies who hide behind their Board of Directors, who promise governance for investors, but rarely deliver on anything beyond pandering to the CEO’s whims. In another ludicrous comparison, Apple and Steve Jobs specifically have also been accused of shoddy corporate governance. In 2007, Apple famously backdated Jobs options, allowing him to make an instant profit, and did not even bother to report that it had issued the options. The best companies are not immune, and investors and employees should be aware of the qualifications and monetary interests of a company’s board members.

3. Search and Destroy. Only the Paranoid Survive, right? Wrong. There is such thing as too much paranoia. When you combine that paranoia with a manipulative persona, you get Elizabeth Holmes. It’s hard to believe that any startup or founder would need the level of security and secrecy that dominated the culture at Theranos. The list of weird security and legal gray areas include: personal security for Holmes, laboratory developed tests (instead of FDA approved tests), copious and vigorously enforced NDAs, siloed teams with no communication, and false representation in the media. Organizations are often secret and many startups operate in stealth to not give away details to competitors. Some larger companies launch new divisions in separate locations from their office, like Amazon a9. The Company hired private investigators (through its powerful law firm Boies Schiller) to threaten and track former employees including Erika Chung and Tyler Schulz. Tyler Schulz, grandson of board member George Schulz, was one of the key informants to author John Carreyrou. After he accused Elizabeth and Sunny of lying and potentially harming patients, he resigned and tried to convince his grandfather that it was all a sham. His grandfather agreed to speak with him one-on-one and at the end of the conversation surprised Tyler with two attorneys from Boies Schiller who almost forced Tyler to sign a confidentiality agreement. Tyler refused, which eventually led to the publication of Carreyrou’s first article. As early board member Avie Tevanian put it, “I had seen so many things that were bad go on. I would never expect anyone would behave the way that she behaved as a CEO. And believe me, I worked for Steve Jobs. I saw some crazy things. But Elizabeth took it to a new level.” Again, sadly, while Theranos may be the pinnacle of secrecy, paranoia and threatening behavior, eBay recently fired six employees for threatening online reviewers. On top of sending live spiders to the reviewers’ household, eBay team members would knock on their doors day or night, to scare the reviewers. How could these employees think this was ok? How could Elizabeth partake in this threatening and manipulative behavior? As Organizational Behavior professor Roderick Kramer reminds us: “‘Reality’ is not a fixed entity but rather a tissue of facts, impressions, and interpretations that can be manipulated and perverted by clever and devious businesses and governments.” Theranos’ fake Edison tests are reminiscent of Enron’s fake trading floor, where 70 low level employees once pretended to be busy to impress wall street analysts. Paranoia and secrecy are powerful weapons when left unchecked, and clearly Theranos' wielded those weapons to the fullest extent.

Dig Deeper

• HBO Documentary: “The Inventor: Out for Blood in Silicon Valley” has many interviews and deep analysis on Theranos

• When Paranoia Makes Sense by Organizational Behavior Professor Roderick Kramer

• Theranos criminal trial set to begin March 9, 2021

• Ex-Theranos CEO Elizabeth Holmes says 'I don't know' 600-plus times in never-before-broadcast deposition tapes

• Holmes’ famous Mad Money Interview: “First they think you're crazy, then they fight you, and then all of a sudden you change the world.”

• Theranos’ still active Twitter account

May 2020 - Hitchhiker's Guide to the Galaxy by Douglas Adams

We want to recognize the craziness of the world today and the saddening police brutality and systemic racism that continues to occur in the US. This month we opted for a fiction book that may provide a minor break from that current, depressing reality. We want to acknowledge that our reality is messed up, and as a book club we are committed to reading more books about diversity in tech and more books written by a diverse set of authors.

Tech Themes

1. The Computer knows the answer. There is an overwhelming feeling in society today, that the computer should be able to tell us the answer. Predictive models are everywhere, from personalized AI workflows to sports gambling. Society has become accustomed to the idea that computers will solve problems for us. Interestingly, the novel portrays technology in the opposite light. Marvin, the robot on Zaphod Beeblebrox’s ship is so knowledgeable that even the most complex task seems meaninglessly easy. As a result, Marvin is constantly depressed. Deep Thought, the most powerful computer in history, takes seven million years to come up with an answer to the question of what life is all about. The simplistic forty-two answer, prompts the crowd to ask what the question was to which the answer is forty-two. The computer suggests that earth will provide that question. These examples somewhat reverse the expectations of technology to the reader. We normally think of technology as providing the answer, simplifying our lives and dehumanizing us. At the end of the story it is not Marvin’s heroism that saves the crew from being killed by the Blagulon Kappa cops who are after the Heart of Gold, it is his depression. When Marvin seizes control of the cops computer and explains his life-view, they commit suicide. In these instances, the role of technology is reversed - it is emotion and human nature that can help save the world and provide the answers to the universe.

2. Not so obvious, Space Travel and Towels. “A towel, it says, is about the most massively useful thing an interstellar hitchhiker can have.” Something so simple as a towel - which seems relatively unimportant in everyday life - is an absolute necessity for space travel and hitchhiking through the galaxy. Frequently throughout technological history, the simple and unimportant things are overlooked in favor of tackling more complex problems and solutions. The largest data breach in history occurred when Equifax overlooked an expired certificate. During early development of the ENIAC, one of the first computing machines, software was looked at as unimportant and was relegated to early female programmers. Little did these sexist hardware programmers realize that software would become the most important aspect of computing. When the first iPhone released, Microsoft CEO Steve Ballmer laughed at the the device, saying it was too expensive and unable to cater to business customers because it didn’t have a keyboard. The incredibly sad, failed launch of space shuttle Challenger was due to cold temperatures causing rubber joint rings to become too stiff for appropriate sealing. Sometimes the value of a technology or a towel is not inherently obvious.

3. The Guide, the Whole Earth Catalog and the Internet. “The reason why it was published in the form of a micro sub meson electronic component is that if it were printed in normal book form, an interstellar hitchhiker would require several inconveniently large buildings to carry it around in.” The Hitchhiker’s Guide to The Galaxy is a massive electronic guide to help hitchhikers move throughout space. This interestingly mirrors the current state of the internet, which didn’t exist when Douglas Adams wrote Hitchhiker’s Guide to the Galaxy in the early 70s. Prior to the internet, this type of alternative information could be found in the Whole Earth Catalog, a famous magazine that Steve Jobs once called “Google in paperback form, thirty-five years before Google came along.” The Whole Earth Catalog was created by Stewart Brand, a famous writer and technologist, who actually participated with Douglas Englebart in the Mother of All Demos, which featured the introduction of the mouse and video conferencing. Brand wanted a way to publish material that wouldn’t be found in traditional textbooks, including product reviews of the latest technology. When the internet was starting to launch, Brand created The WELL (Whole Earth ‘Lectronic Link) to continue to provide interesting alternative articles and essays. The WELL is credited with being one of the first internet forums, which was originally accessed via dial-up bulletin board system. The internet today very much mirrors the Hitchhiker’s guide to the galaxy: its content is enormous, it isn’t necessarily factual (the Guide is not completely factual either, but based on experience), and its content spans all possible information needed to survive. On top of that, the packaging is described as suspiciously similar to modern smartphones: “He also had a device which looked rather like a largish electronic calculator. This had about a hundred tiny flat press buttons and a screen about four inches square on which any one of a million ‘pages’ could be summoned at a moment's notice.” The internet and mobile computing have come a long way in 50 years; it will be great to watch what happens in the next 50!

Business Themes

1. The Business of Space: SpaceX / Virgin Galactic. Elon Musk and Chamath Palihapitiya are outspoken, visionary billionaires. Elon has an incredible track record of under-delivering but still exceeding most people’s wildest expectations. Chamath was an early employee at Facebook and is now a part owner of the Golden State Warriors. He is CEO of a VC-firm turned “technological holding company” and the creator of three public SPACs, one of which now represents Virgin Galactic. A SPAC or Specialty Purpose Acquisition Company is a blank-check company with no commercial operations. A SPAC is normally led by experts in a specific space like software or real estate and these executives raise money to acquire a company. The money raised in an IPO sits in an interest bearing account until the blank-check company has found a company to acquire. If no deal is completed after two years, the SPAC will give money back to their investors. Chamath purchased 49% of Richard Branson's Virgin Galactic space company in 2019. Space is impossibly big and its natural to think that someone who can develop the technology to unlock that vastness to humans would also unlock a fortune. As the Guide puts it: “‘Space,’ it says, ‘is big. Really big. You just won’t believe how vastly, hugely, mindbogglingly big it is. I mean, you may think it’s a long way down the road to the chemist’s, but that’s just peanuts to space.’” But the business of space is in its earliest days. SpaceX relies almost completely on government contracted work which means the company needs an incredible amount of funding to survive because of the capital investment and the uncertain, non-recurring nature of these space contracts. Interestingly, the development of early commercial air travel, in the 1920’s, also had a similar funding issue, and it was up to the Guggenheim family, rich from mining profits, to set up a fund to exclusively contribute to the development of Western Air Express, the world’s first commercial airliner. Virgin Galactic is taking a piece out of Tesla’s playbook by selling future space rides ahead of any commercial launch. Public markets investors including reddit’s wallstreetbets community is piling into Virgin Galactic at the literal moonshot risk of it becoming the space company (Income statement above). Space has always been a billionaire passion, the question remains - can it be a business?

2. Moore’s Law and Murphy’s Law. Murphy’s law states: “Anything that can go wrong, will go wrong.” Hitchhiker’s Guide to the Galaxy explores this notion repeatedly as Arthur continually finds himself in unbelievably bad circumstances; his house is demolished, his planet is destroyed, he is captured by Vogons, and sure-death missles approach the ship as the crew descends on Magarathea. Arthur continues to survive these dangers with the help of the improbability drive, which the book states is a “a wonderful new method of crossing interstellar distances in a few seconds; without all that tedious mucking about in hyperspace. As the Improbability Drive reaches infinite improbability, it passes through every conceivable point in every conceivable universe almost simultaneously. In other words, you're never sure where you'll end up or even what species you'll be when you get there. It's therefore important to dress accordingly.” In comparison to Murphy’s law, Moore’s Law is the idea that computing power doubles every 18 months. A 2006 Economist article explained Moore’s Law as the opposite of Murphy’s Law: “But his law seems safe for at least another decade—or two to three chip generations—which is as far as he has ever dared to look into the future. As things are made at scales approaching individual atoms, he says, there will surely be limitations. Then again, the law has often met obstacles that appeared insurmountable, before soon surmounting them. In that sense, Mr Moore says, he now sees his law as more beautiful than he had realised. “Moore's Law is a violation of Murphy's Law. Everything gets better and better.” While Moore’s Law has surely reached its current limitations, the question remains where do chips go from here? Some have posited that chips will push towards function specific hardware or purpose built for specific computing tasks like NVIDIA’s graphics cards. The space is large and complex - with companies like Apple licensing ARM technology to build their famous A13 chip while other companies have focused on specific parts of the value chain like TSMC. A big question that still remains is how cloud companies will scale hardware to meet continuing demand from customers. Arthur Dent, like Elon Musk, continues to benefit from infinite improbability - maybe quantum computing is the only way to know if Elon will succeed and what happens next in chip design.

3. Mentorship. Slartibarfast is a wise, old, planet creator who is plopped into the story to provide Arthur with answers to so many incredible questions. Slartibartfast explains the creation of earth and the interaction with Deep Thought. The interactions between Arthur and Slartibartfast are somewhat akin to traditional business mentorship - when you have none of the answers or you have preconceived ideas of how everything came to be, a mentor can quickly dispel your ideas and provide deep answers. Mentorship has been popular in Silicon Valley, with Bill Campbell mentoring Steve Jobs and several others. Bill was also instrumental in several decisions Ben Horowitz contemplated as he took Opsware through its spinout and sale of its managed services division. Mentors help change perspective and provide guidance.

Dig Deeper

• Discussion of how the Whole Earth Catalog pushed 1960s CounterCulture

• List of the Latest OpenAI models for predictive image generation and interaction prediction

• Chamath says “Let Them Get Wiped Out!” when talking about hedge funds during the coronarvirus downturn

• The resurgence of a business model formerly considered fraud - SPACs

• Apple releases A13 bionic chip and it works incredibly fast

April 2020 - Good To Great by Jim Collins

Collins’ book attempts to answer the question - Why do good companies continue to be good companies? His analysis across several different industries provides meaningful insights into strong management and strategic practices.

Tech Themes

1. Packard’s Law. We’ve discussed Packard’s law before when analyzing the troubling acquisition history of AOL-Time Warner and Yahoo. As a reminder, Packard’s law states: “No company can consistently grow revenues faster than its ability to get enough of the right people to implement that growth and still become a great company. [And] If a company consistently grows revenue faster than its ability to get enough of the right people to implement that growth, it will not simply stagnate; it will fall.” Given Good To Great is a management focused book, I wanted to explore an example of this law manifesting itself in a recent management dilemma. Look no further than ride-sharing giant, Uber. Uber’s culture and management problems have been highly publicized. Susan Fowler’s famous blog post kicked off a series of blows that would ultimately lead to a board dispute, the departure of its CEO, and a full-on criminal investigation. Uber’s problems as a company, however, can be traced to its insistence to be the only ride-sharing service throughout the world. Uber launched several incredibly unprofitable ventures, not only a price-war with its local competitor Lyft, but also a concerted effort to get into China, India, and other locations that ultimately proved incredibly unprofitable. Uber tried to be all things transportation to every location in the world, an over-indulgence that led to the Company raising a casual $20B prior to going public. Dara Khosrowshahi, Uber’s replacement for Travis Kalanick, has concertedly sold off several business lines and shuttered other unprofitable ventures to regain financial control of this formerly money burning “logistics” pit. This unwinding has clearly benefited the business, but also limited growth, prompting the stock to drop significantly from IPO price. Dara is no stranger to facing travel challenges, he architected the spin-out of Expedia with Barry Diller, right before 9/11. Only time will tell if he can refocus the Company as it looks to run profitably. Uber pushed too far in unprofitable locations, and ran head on into Packard’s law, now having to pay the price for its brash push into unprofitable markets.

2. Technology Accelerators. In Collins’ Good to Great framework (pictured below), technology accelerators act as a catalyst to momentum built up from disciplined people and disciplined thought. By adapting a “Pause, think, crawl, walk, run” approach to technology, meaning a slow and thoughtful transition to new technologies, companies can establish best practices for the long-term, instead of short term gains from technology faux-feature marketing. Technology faux-feature marketing, which is decoupled from actual technology has become increasingly popular in the past few years, whereby companies adopt a marketing position that is actually complete separate from their technological sophistication. Look no further than the blockchain / crypto faux-feature marketing around 2018, when Long Island iced-tea changed its name to Long Island Blockchain, which is reminiscent of companies adding “.com” to their name in the early 2000’s. Collins makes several important distinctions about technology accelerators: technology should only be a focus if it fits into a company’s hedgehog concept, technology accelerators cannot make up for poor people choices, and technology is never a primary root cause of either greatness or decline. The first two axioms make sense, just think of how many failed, custom software projects have begun and never finished; there is literally an entire wikipedia page dedicated to exactly that. The government has also reportedly been a famous dabbler in homegrown, highly customized technology. As Collins notes, technology accelerators cannot make up for bad people choices, an aspect of venture capital that is overlooked by so many. Enron is a great example of an interesting idea turned sour by terrible leadership. Beyond the accounting scandals that are discussed frequently, the culture was utterly toxic, with employees subjected to a “Performance Review Committee” whereby they were rated on a scale of 1-5 by their peers. Employees rated a 5 were fired, which meant roughly 15% of the workforce turned over every year. The New York Times reckoned Enron is still viewed as a trailblazer for the way it combined technology and energy services, but it clearly suffered from terrible leadership that even great technology couldn’t surmount. Collins’ most controversial point is arguably that technology cannot cause greatness or decline. Some would argue that technology is the primary cause of greatness for some companies like Amazon, Apple, Google, and Microsoft. The “it was just a better search engine” argument abounds discussions of early internet search engines. I think what Collins’ is getting at is that technology is malleable and can be built several different ways. Zoom and Cloudflare are great examples of this. As we’ve discussed, Zoom started over 100 years after the idea for video calling was first conceived, and several years after Cisco had purchased Webex, which begs the question, is technology the cause of greatness for Zoom? No! Zoom’s ultimate success the elegance of its simple video chat, something which had been locked up in corporate feature complexity for years. Cloudflare presents another great example. CDN businesses had existed for years when Cloudflare launched, and Cloudflare famously embedded security within the CDN, building on a trend which Akamai tried to address via M&A. Was technology the cause of greatness for Cloudflare? No! It’s way cheaper and easier to use than Akamai. Its cost structure enabled it to compete for customers that would be unprofitable to Akamai, a classic example of a sustaining technology innovation, Clayton Christensen’s Innovator’s Dilemma. This is not to say these are not technologically sophisticated companies, Zoom’s cloud ops team has kept an amazing service running 24/7 despite a massive increase in users, and Cloudflare’s Workers technology is probably the best bet to disrupt the traditional cloud providers today. But to place technology as the sole cause for greatness would be understating the companies achievements in several other areas.

3. Build up, Breakthrough Flywheel. Jeff Bezos loves this book. Its listed in the continued reading section of prior TBOTM, The Everything Store. The build up, breakthrough flywheel is the culmination of disciplined people, disciplined thought and disciplined action. Collins’ points out that several great companies frequently appear like overnight successes; all of a sudden, the Company has created something great. But that’s rarely the case. Amazon is a great example of this; it had several detractors in the early days, and was dismissed as simply an online bookseller. Little did the world know that Jeff Bezos had ideas to pursue every product line and slowly launched one after the other in a concerted fashion. In addition, what is a better technology accelerator than AWS! AWS resulted from an internal problem of scaling compute fast enough to meet growing consumer demand for their online products. The company’s tech helped it scale so well that they thought, “Hey! Other companies would probably like this!” Apple is another classic example of a build-up, breakthrough flywheel. The Company had a massive success with the iPod, it was 40% of revenues in 2007. But what did it do? It cannablized itself and pursued the iPhone, with several different teams within the company pursuing it individually. Not only that, it created a terrible first version of an Apple phone with the Rokr, realizing that design was massively important to the phone’s success. The phone’s technology is taken for granted today, but at the time the touch screen was simply magical!

Business Themes

1. Level 5 Leader. The first part and probably the most important part of the buildup, breakthrough, flywheel is disciplined people. One aspect of Good to Great that inspired Collins’ other book Built to Last, is the idea that leadership, people, and culture determine the long-term future of a business, even after current leadership has moved on from the business. To set an organization up for long-term success, executives need to display level five leadership, which is a mix of personal humility and professional will. Collins’ leans in on Lee Iacocca as an example of a poor leader, who focused more on personal celebrity and left Chrysler to fail, when he departed. Level 5 leadership has something that you don’t frequently see in technology business leaders, humility. The technology industry seems littered with far more Larry Ellison and Elon Musk’s than any other industry, or maybe its just that tech CEOs tend to shout the loudest from their pedestals. One CEO that has done a great job of representing level five leadership is Shantanu Narayen, who took the reigns of Adobe in December 2007, right on the cusp of the financial crisis. Narayen, who’s been described as more of a doer than a talker, has dramatically changed Adobe’s revenue model, moving the business from a single sale license software business focused on lower ACV numbers, to an enterprise focused SaaS business. This march has been slow and pragmatic but the business has done incredibly well, 10xing since he took over. Adobe CFO, Mark Garrett, summarized it best in a 2015 McKinsey interview: “We instituted open dialogue with employees—here’s what we’re going through, here’s what it might look like—and we encouraged debate. Not everyone stayed, but those who did were committed to the cloud model.”

2. Hedgehog Concept. The Hedgehog concept (in the picture wheel to the right) is the overlap of three questions: What are you passionate about?, What are you the best in the world at?, and What drives your economic engine? This overlap is the conclusion of Collins’ memo to Confront the Brutal Facts, something that Ben Horowitz emphasizes in March’s TBOTM. Once teams have dug into their business, they should come up with a simple way to center their focus. When companies reach outside their hedgehog concept, they get hurt. The first question, about organizational passion, manifests itself in mission and value statements. The best in the world question manifests itself through value network exercises, SWOT analyses and competitive analyses. The economic engine is typically shown as a single metric to define success in the organization. As an example, let’s walk through an example with a less well-known SaaS company: Avalara. Avalara is a provider of tax compliance software for SMBs and enterprises, allowing those businesses to outsource complex and changing tax rules to software that integrates with financial management systems to provide an accurate view of corporate taxes. Avalara’s hedgehog concept is right on their website: “We live and breathe tax compliance so you don't have to.” Its simple and effective. The also list a slightly different version in their 10-K, “Avalara’s motto is ‘Tax compliance done right.’” Avalara is the best at tax compliance software, and that is their passion; they “live and breath” tax compliance software. What drives Avalara’s economic engine? They list two metrics right at the top of their SEC filings, number of core customers and net revenue retention. Core customers are customers who have been billed more than $3,000 in the last twelve months. The growth in core customers allows Avalara to understand their base of revenue. Tax compliance software is likely low churn because filing taxes is such an onerous process, and most people don’t have the expertise to do it for their corporate taxes. They will however suffer from some tax seasonality and some customers may churn and come back after the tax period has ended for a given year. Total billings allows Avalara to account for this possibility. Avalara’s core customers have grown 32% in the last twelve months, meaning its revenue should be following a similar trajectory. Net retention allows the company to understand how customer purchasing behavior changes over time and at 113% net retention, Avalara’s overall base is buying more software from Avalara than is churning, which is a positive trend for the company. What is the company the best in the world at? Tax compliance software for SMBs. Avalara views their core customer as greater than $3,000 of trailing twelve months revenue, which means they are targeting small customers. The Company’s integrations also speak to this - Shopify, Magento, NetSuite, and Stripe are all focused on SMB and mid-market customers. Notice that neither SAP nor Oracle ERP is in that list of integrations, which are the financial management software providers that target large enterprises. This means Avalara has set up its product and cost structure to ensure long-term profitability in the SMB segment; the enterprise segment is on the horizon, but today they are focused on SMBs.

3. Culture of Discipline. Collins describes a culture of discipline as an ability of managers to have open and honest, often confrontational conversation. The culture of discipline has to fit within a culture of freedom, allowing individuals to feel responsible for their division of the business. This culture of discipline is one of the first things to break down when a CEO leaves. Collins points on this issue with Lee Iaccoca, the former CEO of Chrysler. Lee built an intense culture of corporate favoritism, which completely unraveled after he left the business. This is also the focus of Collins’ other book, Built to Last. Companies don’t die overnight, yet it seems that way when problems begin to abound company-wide. We’ve analyzed HP’s 20 year downfall and a similar story can be shown with IBM. In 1993, IBM elected Lou Gerstner as CEO of the company. Gerstner was an outsider to technology businesses, having previously led the highly controversial RJR Nabisco, after KKR completed its buyout in 1989. He has also been credited with enacting wholesale changes to the company’s culture during his tenure. Despite the stock price increasing significantly over Gerstner’s tenure, the business lost significant market share to Microsoft, Apple and Dell. Gerstner was also the first IBM CEO to make significant income, having personally been paid hundreds of millions over his tenure. Following Gerstner, IBM elected insider Sam Palmisano to lead the Company. Sam pushed IBM into several new business lines, acquired 25 software companies, and famously sold off IBM’s PC division, which turned out to be an excellent strategic decision as PC sales and margins declined over the following ten years. Interestingly, Sam’s goal was to “leave [IBM] better than when I got there.” Sam presided over a strong run up in the stock, but yet again, severely missed the broad strategic shift toward public cloud. In 2012, Ginni Rometty was elected as new CEO. Ginni had championed IBM’s large purchase of PwC’s technology consulting business, turning IBM more into a full service organization than a technology company. Palmisano has an interesting quote in an interview with a wharton business school professor where he discusses IBM’s strategy: “The thing I learned about Lou is that other than his phenomenal analytical capability, which is almost unmatched, Lou always had the ability to put the market or the client first. So the analysis always started from the outside in. You could say that goes back to connecting with the marketplace or the customer, but the point of it was to get the company and the analysis focused on outside in, not inside out. I think when you miss these shifts, you’re inside out. If you’re outside in, you don’t miss the shifts. They’re going to hit you. Now acting on them is a different characteristic. But you can’t miss the shift if you’re outside in. If you’re inside out, it’s easy to delude yourself. So he taught me the importance of always taking the view of outside in.” Palmisano’s period of leadership introduced a myriad of organizational changes, 110+ acquisitions, and a centralization of IBM processes globally. Ginni learned from Sam that acquisitions were key toward growth, but IBM was buying into markets they didn’t fully understand, and when Ginni layered on 25 new acquisitions in her first two years, the Company had to shift from an outside-in perspective to an inside-out perspective. The way IBM had historically handled the outside-in perspective, to recognize shifts and get ahead of them, was through acquisition. But when the acquisitions occured at such a rapid pace, and in new markets, the organization got bogged down in a process of digestion. Furthermore, the centralization of processes and acquired businesses is the exact opposite of what Clayton Christensen recommends when pursuing disruptive technology. This makes it obvious why IBM was so late to the cloud game. This was a mainframe and services company, that had acquired hundreds of software businesses they didn’t really understand. Instead of building on these software platforms, they wasted years trying to put them all together into a digestible package for their customers. IBM launched their public cloud offering in June 2014, a full seven years after Microsoft, Amazon, and Google launched their services, despite providing the underlying databases and computing power for all of their enterprise customers. Gerstner established the high-pay, glamorous CEO role at IBM, which Palmisano and Ginni stepped into, with corporate jets and great expense policies. The company favored increasing revenues and profits (as a result of acquisitions) over the recognition and focus on a strategic market shift, which led to a downfall in the stock price and a declining mindshare in enterprises. Collins’ understands the importance of long term cultural leadership. “Does Palmisano think he could have done anything differently to set IBM up for success once he left? Not really. What has happened since falls to a new coach, a new team, he says.”

Dig Deeper

• Level 5 Leadership from Darwin Smith at Kimberly Clark

• From Good to Great … to Below Average by Steven Levitt - Unpacking underperformance from some of the companies Collins’ studied

• The Challenges faced by new CEO Arvind Krishna

• Overview of Cloudflare Workers

• The Opposite of the Buildup, Breakthrough, Flywheel - the Doom Loop

March 2020 - The Hard Thing About Hard Things by Ben Horowitz

Ben Horowitz, GP of the famous investment fund Andreessen Horowitz, addresses the not-so-pleasant aspects of being a founder/CEO during a crisis. This book provides an excellent framework for anyone going through the struggles of scaling a business and dealing with growing pains.

Tech Themes

1. The importance of Netscape. Now that its been relegated to history by the rise of AOL and internet explorer, its hard to believe that Netscape was ever the best web browser. Founded by Marc Andreessen, who had founded the first web browser, Mosaic (as a teenager!), Netscape would go on to achieve amazing success only to blow up in the face of competition and changes to internet infrastructure. Netscape was an incredible technology company, and as Brian McCullough shows in last month’s TBOTM, Netscape was the posterchild for the internet bubble. But for all the fanfare around Netscape’s seminal IPO, little is discussed about its massive and longstanding technological contributions. In 1995, early engineer Brendan Eich created Javascript, which still stands as the dominant front end language for the web. In the same year, the Company developed Secure Socket Layer (SSL), the most dominant basic internet security protocol (and reason for HTTPS). On top of those two fundamental technologies, Netscape also developed the internet cookie, in 1994! Netscape is normally discussed as the amazing company that ushered many of the first internet users onto the web, but its rarely lauded for its longstanding technological contributions. Ben Horowitz, author of the Hard Thing About Hard Things was an early employee and head of the server business unit for Netscape when it went public.

2. Executing a pivot. Famous pivots have become part of startup lore whether it be in product (Glitch (video game) —> Slack (chat)), business model (Netflix DVD rental —> Streaming), or some combo of both (Snowdevil (selling snowboards online) —> Shopify (ecommerce tech)). The pivot has been hailed as necessary tool in every entrepreneur’s toolbox. Though many are sensationalized, the pivot Ben Horowitz underwent at LoudCloud / Opsware is an underrated one. LoudCloud was a provider of web hosting services and managed services for enterprises. The Company raised a boatload ($346M) of money prior to going public in March 2001, after the internet bubble had already burst. The Company was losing a lot of money and Ben knew that the business was on its last legs. After executing a 400 person layoff, he sold the managed services part of the business to EDS, a large IT provider, for $63.5M. LoudCloud had a software tool called Opsware that it used to manage all of the complexities of the web hosting business, scaling infrastructure with demand and managing compliance in data centers. After the sale was executed, the company’s stock fell to $0.35 per share, even trading below cash, which meant the markets viewed the Company as already bankrupt. The acquisition did something very important for Ben and the Opsware team, it bought them time - the Company had enough cash on hand to execute until Q4 2001 when it had to be cash flow positive. To balance out these cash issues, Opsware purchased Tangram, Rendition Networks, and Creekpath, which were all software vendors that helped manage the software of data centers. This had two effects - slowing the burn (these were profitable companies), and building a substantial product offering for data center providers. Opsware started making sales and the stock price began to tick up, peaking the attention of strategic acquirers. Ultimately it came down to BMC Software and HP. BMC offered $13.25 per share, the Opsware board said $14, BMC countered with $13.50 and HP came in with a $14.25 offer, a 38% premium to the stock price and a total valuation of $1.6B, which the board could not refuse. The Company changed business model (services —> software), made acquisitions and successfully exited, amidst a terrible environment for tech companies post-internet bubble.

3. The Demise of the Great HP. Hewlett-Packard was one of the first garage-borne, silicon valley technology companies. The company was founded in Palo Alto by Bill Hewlett and Dave Packard in 1939 as a provider of test and measurement instruments. Over the next 40 years, the company moved into producing some of the best printers, scanners, calculators, logic analyzers, and computers in the world. In the 90s, HP continued to grow its product lines in the computing space, and executed a spinout of its manufacturing / non-computing device business in 1999. 1999 marks the tragic beginning of the end for HP. The first massive mistake was the acquisition of Compaq, a flailing competitor in the personal computer market, who had acquired DEC (a losing microprocessor company), a few years earlier. The acquisition was heavily debated, with Walter Hewlett, son of the founder and board director at the time, engaging in a proxy battle with then current CEO, Carly Firorina. The new HP went on to lose half of its market value and incur heavy job losses that were highly publicized. This started a string of terrible acquisitions including EDS, 3COM, Palm Inc., and Autonomy for a combined $28.8B. The Company spun into two divisions - HP Inc. and HP Enterprise in 2015 and each had their own spinouts and mergers from there (Micro Focus and DXC Technology). Today, HP Inc. sells computers and printers, and HPE sells storage, networking and server technology. What can be made of this sad tale? HP suffered from a few things. First, poor long term direction - in hindsight their acquisitions look especially terrible as a repeat series of massive bets on technology that was already being phased out due to market pressures. Second, HP had horrible corporate governance during the late 90s and 2000s - board in-fighting over acquisitions, repeat CEO fiirings over cultural issues, chairman-CEO’s with no checks, and an inability to see the outright fraud in their Autonomy acquisition. Lastly, the Company saw acquisitions and divestitures as band-aids - new CEO entrants Carly Fiorina (from AT&T), Mark Hurd (from NCR), Leo Apotheker (from SAP), and Meg Whitman (from eBay) were focused on making an impact at HP which meant big acquisitions and strategic shifts. Almost none of these panned out, and the repeated ideal shifts took a toll on the organization as the best talent moved elswehere. Its sad to see what has happened at a once-great company.

Business Themes

1. Ill, not sick: going public at the end of the internet bubble. Going public is supposed to be the culmination of a long entrepreneurial journey for early company employees, but according to Ben Horowitz’s experience, going public during the internet bubble pop was terrible. Loudcloud had tried to raise money privately but struggled given the terrible conditions for raising money at the beginning of 2001. Its not included in the book but the reason the Company failed to raise money was its obscene valuation and loss. The Company was valued at $1.15B in its prior funding round and could only report $6M in Net Revenue on a $107M loss. The Company sought to go public at $10 per share ($700M valuation), but after an intense and brutal roadshow that left Horowitz physically sick, they settled for $6.00 per share, a massive write-down from the previous round. The fact that the banks were even able to find investors to take on this significant risk at this point in the business cycle was a marvel. Timing can be crucial in an IPO as we saw during the internet bubble; internet “businesses” could rise 4-5x on their first trading day because of the massive and silly web landgrab in the late 90s. On the flip side, going public when investors don’t want what you’re selling is almost a death sentence. Although they both have critical business and market issues, WeWork and Casper are clear examples of the importance of timing. WeWork and Casper were late arrivals on the unicorn IPO train. Let me be clear - both have huge issues (WeWork - fundamental business model, Casper - competition/differentiation) but I could imagine these types of companies going public during a favorable time period with a relatively strong IPO. Both companies had massive losses, and investors were especially wary of losses after the failed IPOs of Lyft and Uber, which were arguably the most famous unicorns to go public at the time. Its not to say that WeWork and Casper wouldn’t have had trouble in the public markets, but during the internet bubble these companies could’ve received massive valuations and raised tons of cash instead of seeking bailouts from Softbank and reticent public market investors.

2. Peactime / Wartime CEO. The genesis of this book was a 2011 blog post written by Horowitz detailing Peacetime and Wartime CEO behavior. As the book and blog post describe, “Peacetime in business means those times when a company has a large advantage vs. the competition in its core market, and its market is growing. In times of peace, the company can focus on expanding the market and reinforcing the company’s strengths.” On the other hand, to describe Wartime, Horowitz uses the example of a previous TBOTM, Only the Paranoid Survive, by Andy Grove. In the early 1980’s, Grove realized his business was under serious threat as competition increased in Intel’s core business, computer memory. Grove shifted the entire organization whole-heartedly into chip manufacturing and saved the company. Horowitz outlines several opposing behaviors of Peacetime and Wartime CEOs: “Peacetime CEO knows that proper protocol leads to winning. Wartime CEO violates protocol in order to win; Peacetime CEO spends time defining the culture. Wartime CEO lets the war define the culture; Peacetime CEO strives for broad based buy in. Wartime CEO neither indulges consensus-building nor tolerates disagreements.” Horowitz concludes that executives can be a peacetime and wartime CEO after mastering each of the respective skill sets and knowing when to shift from peacetime to wartime and back. The theory is interesting to consider; at its best, it provides an excellent framework for managing times of stress (like right now with the Coronavirus). At its worst, it encourages poor CEO behavior and cut throat culture. While I do think its a helpful theory, I think its helpful to think of situations that may be an exception, as a way of testing the theory. For example, lets consider Google, as Horowitz does in his original article. He calls out that Google was likely entering in a period of wartime in 2011 and as a result transitioned CEOs away from peacetime Eric Schmidt to Google founder and wartime CEO, Larry Page. Looking back however, was it really clear that Google was entering wartime? The business continued to focus on what it was clearly best at, online search advertising, and rarely faced any competition. The Company was late to invest in cloud technology and many have criticized Google for pushing billions of dollars into incredibly unprofitable ventures because they are Larry and Sergey’s pet projects. In addition, its clear that control had been an issue for Larry all along - in 2011, it came out that Eric Schmidt’s ouster as CEO was due to a disagreement with Larry and Sergey over continuing to operate in China. On top of that, its argued that Larry and Sergey, who have controlling votes in Google, stayed on too long and hindered Sundar Pichai’s ability to effectively operate the now restructured Alphabet holding company. In short, was Google in a wartime from 2011-2019? I would argue no, it operated in its core market with virtually no competition and today most Google’s revenues come from its ad products. I think the peacetime / wartime designation is rarely so black and white, which is why it is so hard to recognize what period a Company may be in today.

3. Firing people. The unfortunate reality of business is that not every hire works out, and that eventually people will be fired. The Hard Thing About Hard Things is all about making difficult decisions. It lays out a framework for thinking about and executing layoffs, which is something that’s rarely discussed in the startup ecosystem until it happens. Companies mess up layoffs all the time, just look at Bird who recently laid off staff via an impersonal Zoom call. Horowitz lays out a roughly six step process for enacting layoffs and gives the hard truths about executing the 400 person layoff at LoudCloud. Two of these steps stand out because they have been frequently violated at startups: Don’t Delay and Train Your Managers. Often times, the decision to fire someone can be a months long process, continually drawn out and interrupted by different excuses. Horowitz encourages CEOs to move thoughtfully and quickly to stem leaks of potential layoffs and to not let poor performers continue to hurt the organization. The book discusses the Law of Crappy People - any level of any organization will eventually converge to the worst person on that level; benchmarked against the crappiest person at the next level. Once a CEO has made her mind up about the decision to fire someone, she should go for it. As part of executing layoffs, CEOs should train their managers, and the managers should execute the layoffs. This gives employees the opportunity to seek direct feedback about what went well and what went poorly. This aspect of the book is incredibly important for all levels of entrepreneurs and provides a great starting place for CEOs.

Dig Deeper

• Most drastic company pivots that worked out

• Initial thoughts on the Opsware - HP Deal from 2007

• A thorough history of HP’s ventures, spin-offs and acquisitions

• Ben’s original blog post detailing the pivot from service provider to tech company

• The First (1995-01) and Second Browser War (2004 - 2017)

February 2020 - How the Internet Happened: From Netscape to the iPhone by Brian McCullough

Brian McCullough, host of the Internet History Podcast, does an excellent job of showing how the individuals adopted the internet and made it central to their lives. He follows not only the success stories but also the flame outs which provide an accurate history of a time of rapid technological change.

Tech Themes

1. Form to Factor: Design in Mobile Devices. Apple has a long history with mobile computing, but a few hiccups in the early days are rarely addressed. These hiccups also telegraph something interesting about the technology industry as a whole - design and ease of use often trump features. In the early 90’s Apple created the Figaro, a tablet computer that weighed eight pounds and allowed for navigation through a stylus. The issue was it cost $8,000 to produce and was 3/4 of an inch thick, making it difficult to carry. In 1993, the Company launched the Newton MessagePad, which cost $699 and included a calendar, address book, to-do list and note pad. However, the form was incorrect again; the MessagePad was 7.24 in. x 4.5 in. and clunky. With this failure, Apple turned its attention away from mobile, allowing other players like RIM and Blackberry to gain leading market share. Blackberry pioneered the idea of a full keyboard on a small device and Marc Benioff, CEO of salesforce.com, even called it, “the heroin of mobile computing. I am serious. I had to stop.” IBM also tried its hand in mobile in 1992, creating the Simon Personal Communicator, which had the ability to send and receive calls, do email and fax, and sync with work files via an adapter. The issue was the design - 8 in. by 2.5 in. by 1.5 in. thick. It was a modern smartphone, but it was too big, clunky, and difficult to use. It wasn’t until the iPhone and then Android that someone really nailed the full smart phone experience. The lessons from this case study offer a unique insight into the future of VR. The company able to offer the correct form factor, at a reasonable price can gain market share quickly. Others who try to pioneer too much at a time (cough, magic leap), will struggle.

2. How to know you’re onto something. Facebook didn’t know. On November 30, 2004, Facebook surpassed one million users after being live for only ten months. This incredible growth was truly remarkable, but Mark Zuckerberg still didn’t know facebook was a special company. Sean Parker, the founder of Napster, had been mentoring Zuckerberg the prior summer: “What was so bizarre about the way Facebook was unfolding at that point, is that Mark just didn’t totally believe in it and wanted to go and do all these other things.” Zuckerberg even showed up to a meeting at Sequoia Capital still dressed in his pajamas with a powerpoint entitled: “The Top Ten Reasons You Should Not Invest.” While this was partially a joke because Sequoia has spurned investing in Parker’s latest company, it represented how immature the whole facebook operation was, in the face of rapid growth. Facebook went on to release key features like groups, photos, and friending, but most importantly, they developed their revenue model: advertising. The quick user growth and increasing ad revenue growth got the attention of big corporations - Viacom offered $2B in cash and stock, and Yahoo offered $1B all cash. By this time, Zuckerberg realized what he had, and famously spurned several offers from Yahoo, even after users reacted negatively to the most important feature that facebook would ever release, the News Feed. In today’s world, we often see entrepreneur’s overhyping their companies, which is why Silicon Valley was in-love with dropout founders for a time, their naivite and creativity could be harnessed to create something huge in a short amount of time.

3. Channel Partnerships: Why apple was reluctant to launch a phone. Channel partnerships often go un-discussed at startups, but they can be incredibly useful in growing distribution. Some industries, such as the Endpoint Detection and Response (EDR) market thrives on channel partnership arrangements. Companies like Crowdstrike engage partners (mostly IT services firms) to sell on their behalf, lowering Crowdstrike’s customer acquisition and sales spend. This can lead to attractive unit economics, but on the flip side, partners must get paid and educated on the selling motion which takes time and money. Other channel relationships are just overly complex. In the mid 2000’s, mobile computing was a complicated industry, and companies hated dealing with old, legacy carriers and simple clunky handset providers. Apple tried the approach of working with a handset provider, Motorola, but they produced the terrible ROKR which barely worked. The ROKR was built to run on the struggling Cingular (would become AT&T) network, who was eager to do a deal with Apple in hopes of boosting usage on their network. After the failure of the ROKR, Cingular executives begged Jobs to build a phone for the network. Normally, the carriers had specifications for how phones were built for their networks, but Jobs ironed out a contract which exchanged network exclusivity for complete design control, thus Apple entered into mobile phones. The most important computing device of the 2000’s and 2010’s was built on a channel relationship.

Business Themes

1. AOL-Time Warner: the merger destined to fail. To fully understand the AOL-Time Warner merger, you must first understand what AOL was, what it was becoming, and why it was operating on borrowed time. AOL started as an ISP, charging customers $9.95 for five hours of dial-up internet access, with each additional hour costing $2.95. McCullough describes AOL: “AOL has often been described as training wheels for the Internet. For millions of Americans, their aol.com address was their first experience with email, and thus their first introduction to the myriad ways that networked computing could change their lives.” AOL grew through one of the first viral marketing campaigns ever; AOL put CDs into newspapers which allowed users to download AOL software and get online. The Company went public in March of 1992 and by 1996 the Company had 2.1 million subscribers, however subscribers were starting to flee to cheaper internet access. It turned out that building an ISP was relatively cheap, and the high margin cash flow business that AOL had built was suddenly threatened by a number of competitors. AOL persisted with its viral marketing strategy, and luckily many americans still had not tried the internet yet and defaulted to AOL as being the most popular. AOL continued to add subscribers and its stock price started to balloon; in 1998 alone the stock went up 593%. AOL was also inking ridiculous, heavily VC funded deals with new internet startups. Newly public Drkoop, which raised $85M in an IPO, signed a four year $89M deal to be AOL’s default provider of health content. Barnes and Noble paid $40M to be AOL’s bookselling partner. Tel-save, a long distance phone provider signed a deal worth $100M. As the internet bubble continued to grow, AOL’s CEO, Steve Case realized that many of these new startups would be unable to fufill their contractual obligations. Early web traffic reporting systems could easily be gamed, and companies frequently had no business model other than attract a certain demographic of traffic. By 1999, AOL had a market cap of $149.8B and was added to the S&P 500 index; it was bigger than both Disney and IBM. At this time, the world was shifting away from dial-up internet to modern broadband connections provided by cable companies. One AOL executive lamented: “We all knew we were living on borrowed time and had to buy something of substance by using that huge currency [AOL’s stock].” Time Warner was a massive media company, with movie studios, TV channels, magazines and online properties. On Jan 10, 2000, AOL merged with Time Warner in one of the biggest mergers in history. AOL owned 56% of the combined company. Four days later, the Dow peaked and began a downturn which would decimate hundreds of internet businesses built on foggy fundamentals. Acquisitions happen for a number of reasons, but imminent death is not normally considered by analysts or pundits. When you see acquisitions, read the press release and understand why (at least from a marketing perspective), the two companies made a deal. Was the price just astronomical (i.e. Instagram) or was their something very strategic (i.e. Microsoft-Github)? When you read the press release years later, it should indicate whether the combination actually was proved out by the market.

2. Acquisitions in the internet bubble: why acquisitions are really just guessing. AOL-Time Warner shows the interesting conundrum in acquisitions. HP founder David Packard coined this idea somewhat in Packard’s law: “No company can consistently grow revenues faster than its ability to get enough of the right people to implement that growth and still become a great company. If a company consistently grows revenue faster than its ability to get enough of the right people to implement that growth, it will not simply stagnate; it will fall.” Author of Good to Great, Jim Collins, clarified this idea: “Great companies are more likely to die of ingestion of too much opportunity, than starvation from too little.” Acquisitions can be a significant cause of this outpacing of growth. Look no further than Yahoo, who acquired twelve companies between September 1997 and June 1999 including Mark Cuban’s Broadcast.com for $5.7B (Kara Swisher at WSJ in 1999), GeoCities for $3.6B, and Y Combinator founder Paul Graham’s Viaweb for $48M. They spent billions in stock and cash to acquire these companies! Its only fitting that two internet darlings would eventually end up in the hands of big-telecom Verizon, who would acquire AOL for $4.4B in 2015, and Yahoo for $4.5B in 2017, only to write down the combined value by $4.6B in 2018. In 2013, Yahoo would acquire Tumblr for $1.1B, only to sell it off this past year for $3M. Acquisitions can really be overwhelming for companies, and frequently they don’t work out as planned. In essence, acquisitions are guesses about future value to customers and rarely are they as clean and smart as technology executives make them seem. Some large organizations have gotten good at acquisitions - Google, Microsoft, Cisco, and Salesforce have all made meaningful acquisitions (Android, Github, AppDynamics, ExactTarget, respectively).

3. Google and Excite: the acquisition that never happened. McCullough has an incredible quote nestled into the start of chapter six: “Pioneers of new technologies are rarely the ones who survive long enough to dominate their categories; often it is the copycat or follow-on names that are still with us to this day: Google, not AltaVista, in search; Facebook, not Friendster, in social networks.” Amazon obviously bucked this trend (he mentions that), but in search he is absolutely right! In 1996, several internet search companies went public including Excite, Lycos, Infoseek, and Yahoo. As the internet bubble grew bigger, Yahoo was the darling of the day, and by 1998, it had amassed a $100B market cap. There were tons of companies in the market including the players mentioned above and AltaVista, AskJeeves, MSN, and others. The world did not need another search engine. However, in 1998, Google founders Larry Page and Sergey Brin found a better way to do search (the PageRank algorithm) and published their famous paper: “The Anatomy of a Large-Scale Hypertextual Web Search Engine.” They then went out to these massive search engines and tried to license their technology, but no one was interested. Imagine passing on Goolge’s search engine technology. In an over-ingestion of too much opportunity, all of the search engines were trying to be like AOL and become a portal to the internet, providing various services from their homepages. From an interview in 1998, “More than a "portal" (the term analysts employ to describe Yahoo! and its rivals, which are most users' gateway to the rest of the Internet), Yahoo! is looking increasingly like an online service--like America Online (AOL) or even CompuServe before the Web.” Small companies trying to do too much (cough, uber self-driving cars, cough). Excite showed the most interest in Google’s technology and Page offered it to the Company for $1.6M in cash and stock but Excite countered at $750,000. Excite had honest interest in the technology and a deal was still on the table until it became clear that Larry wanted Excite to rip out its search technology and use Google’s instead. Unfortunately that was too big of a risk for the mature Excite company. The two companies parted ways and Google eventually became the dominant player in the industry. Google’s focus was clear from the get-go, build a great search engine. Only when it was big enough did it plunge into acquisitions and development of adjacent technologies.

Dig Deeper

• Raymond Smith, former CEO of Bell Atlantic, describing the technology behind the internet in 1994

• Bill Gates’ famous memo: THE INTERNET TIDAL WAVE (May 26, 1995)

• The rise and fall of Netscape and Mosaic in one chart

• List of all the companies made famous and infamous in the dot-com bubble

• Pets.com S-1 (filing for IPO) showin a $62M net loss on $6M in revenue

• Detail on Microsoft’s antitrust lawsuit

January 2020 - The Innovators by Walter Isaacson

Isaacson presents a comprehensive history of modern day technology, from Ada Lovelace to Larry Page. He weaves in intricate detail around the development of the computer, which provides the landscape on which all the major players of technological history wander.

Tech Themes

1. Computing Before the Computer. In the Summer of 1843, Ada Lovelace, daughter of the poet Lord Byron, wrote the first computer program, detailing a way of repeatedly computing Bernoulli numbers. Lovelace had been working with Charles Babbage, an English mathematician who had conceived of an Analytical Engine, which could be used as a general purpose arithmetic logic unit. Originally, Babbage thought his machine would only be used for computing complex mathematical problems, but Ada had a bigger vision. Ada was well educated and artistic like her father. She knew that the general purpose focus of the Analytical Engine could be an incredible new technology, even hypothesizing, “Supposing, for instance, that the fundamental relations, of pitched sounds in the science of harmony and musical composition were susceptible to such expression and adaptations, the engine might compose elaborate and scientific pieces of music of any degree of complexity.” 176 years later, in 2019, OpenAI released a deep neural network that produces 4 minute musical compositions, with ten different instruments.

   2. The Government, Education and Technology. Babbage had suggested using punch cards for computers, but Herman Hollerith, an employee of the U.S. Census Bureau, was the first to successfully implement them. Hollerith was angered that the decennial census took eight years to successfully complete. With his new punch cards, designed to analyze combinations of traits, it took only eight. In 1924, after a series of mergers, the company Hollerith founded became IBM. This was the first involvement of the US government with computers. Next came educational institutions, namely MIT, where by 1931 Vanneaver Bush had built a Differential Analyzer (pictured below), the world’s first analog electric computing machine. This machine would be copied by the U.S. Army, University of Pennsylvania, Manchester University and Cambridge University and iterated on until the creation of the Electronic Numerical Integrator and Computer (ENIAC), which firmly established a digital future for computing machines. With World War as a motivator, the invention of the computer was driven forward by academic institutions and the government.

Business Themes

1. Massive Technological Change is Slow. Large technological change almost always feels sudden, but it rarely ever is. Often, new technological developments are relegated to small communities, like Homebrew computing club, where Steve Wozniak handed out mock-ups for the Apple Computer, which was the first to map a keyboard to a screen for input. The development of the transistor (1947) preceded the creation of the microchip (1958) by eleven years. The general purpose chip, a.k.a. the microprocessor popped up thirteen years after that (1971), when Intel introduced the 4004 into the business world. This phenomenon was also true with the internet. Packet switching was first discovered in the early 1960s by Paul Baran, while he was at the RAND Corporation. The Transmission Control Protocol and Internet Protocol were created fifteen years after that (1974) by Vint Cerf and Bob Kahn. The HyperText Transfer Protocol (HTTP) and the HyperText Markup Language (HTML) were created sixteen years after that in 1990 by Tim Berners-Lee. The internet wasn’t in widespread use until after 2000. Introductions of new technologies often seem sudden, but they frequently call on technologies of the past and often involve a corresponding change that address the prior limiting factor of a previous technology. What does that mean for cloud computing, containers, and blockchain? We are probably earlier in the innovation cycle than we can imagine today. Business does not always lag the innovation cycle, but is normally the ending point in a series of innovations.

2. Teams are Everything. Revolution and change happens through the iteration of ideas through collaborative processes. History provides a lot of interesting lessons when it comes to technology transformation. Teams with diverse backgrounds, complementary styles and a mix of visionary and operating capabilities executed the best. As Isaacson notes: “Bell Labs was a classic example. In its long corridors in suburban New Jersey, there were theoretical physicists, experimentalists, material scientists, engineers, a few businessmen, and even some telephone pole climbers with grease under their fingernails.” Bell Labs created the first transistor, a semiconductor that would be the foundation of Intel’s chips, where Bob Noyce and Gordon Moore (yes – Moore’s Law) would provide the vision, and Andy Grove would provide the focus.

Dig Deeper

• Alan Turing and the Turing Machine

• The Deal that Ruined IBM and Catapulted Microsoft

• Grace Hopper and the First Compiler

• ARPANET and the Birth of the Internet

December 2019 - The Moon is a Harsh Mistress by Robert A. Heinlein

This futuristic, anti-establishment thriller is one of Elon Musk’s favorite books. While Heinlein’s novel can drag on with little action, The Moon is a Harsh Mistress presents an interesting war story and predicts several technological revolutions.

Tech Themes

1. Mike, the self-aware computer and IBM. Mycroft Holmes, Heinlein’s self-aware, artificially intelligent computer is a friendly, funny and focused companion to Manny, Wyoh and Prof throughout the novel. Mike’s massive hardware construction is analogous to the way companies are viewing Artificial Intelligence today. Mike’s AI is more closely related to Artificial General Intelligence, which imagines a machine that can go beyond the standard Turing Test, with further abilities to plan, learn, communicate in natural language and act on objects. The 1960s were filled with predictions of futuristic robots and machines. Ideas were popularized not only in books like The Moon is a Harsh Mistress but also in films like 2001: A Space Odyssey, where the intelligent computer, HAL 9000, attempts to overthrow the crew. In 1965, Herbert Simon, a noble prize winner, exclaimed: “machines will be capable, within twenty years, of doing any work a man can do.” As surprising as it may seem today, the dominant technology company of the 1960’s was IBM, known for its System/360 model. Heinlein even mentions Thomas Watson and IBM at Mike’s introduction: “Mike was not official name; I had nicknamed him for Mycroft Holmes, in a story written by Dr. Watson before he founded IBM. This story character would just sit and think--and that's what Mike did. Mike was a fair dinkum thinkum, sharpest computer you'll ever meet.” Mike’s construction is similar to that of present day IBM Watson, who’s computer was able to win Jeopardy, but has struggled to gain traction in the market. IBM and Heinlein approached the computer development in a similar way, Heinlein foresaw a massive computer with tons of hardware linked into it: “They kept hooking hardware into him--decision-action boxes to let him boss other computers, bank on bank of additional memories, more banks of associational neural nets, another tubful of twelve-digit random numbers, a greatly augmented temporary memory. Human brain has around ten-to-the tenth neurons. By third year Mike had better than one and a half times that number of neuristors.” This is the classic IBM approach – leverage all of the hardware possible and create a massive database of query-able information. This actually does work well for information retrieval like Jeopardy, but stumbles precariously on new information and lack of data, which is why IBM has struggled with Watson applications to date.

2. Artificial General Intelligence. Mike is clearly equipped with artificial general intelligence (AGI); he has the ability to securely communicate in plain language, retrieve any of the world’s information, see via cameras and hear via microphones. As discussed above, Heinlein’s construction of Mike is clearly hardware focused, which makes sense considering the book was published in the sixties, before software was considered important. In contrast to the 1960s, today, AGI is primarily addressed from an algorithmic, software angle. One of the leading research institutions (excluding the massive tech companies) is OpenAI, an organization who’s mission is: “To ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity.” OpenAI was started by several people including Elon Musk and Sam Altman, founder of Y Combinator, a famous startup incubator based in Silicon Valley. OpenAI just raised $1 billion from Microsoft to pursue its artificial algorithms and is likely making the most progress when it comes to AGI. The organization has released numerous modules that allow developers to explore the wide-ranging capabilities of AI, from music creation, to color modulation. But software alone is not going to be enough to achieve full AGI. OpenAI has acknowledged that the largest machine learning training runs have been run on increasingly more hardware: “Of course, the use of massive compute sometimes just exposes the shortcomings of our current algorithms.” As we discussed before (companies are building their own hardware for this purpose, link to building their own hardware), and the degradation of Moore’s Law imposes a serious threat to achieving full Artificial General Intelligence.

3. Deep Learning, Adam Selene, and Deep Fakes. Heinlein successfully predicted machine’s ability to create novel images. As the group plans to take the rebellion public, Mike is able to create a depiction of Adam Selene that can appear on television and be the face of the revolution: “We waited in silence. Then screen showed neutral gray with a hint of scan lines. Went black again, then a faint light filled middle and congealed into cloudy areas light and dark, ellipsoid. Not a face, but suggestion of face that one sees in cloud patterns covering Terra. It cleared a little and reminded me of pictures alleged to be ectoplasm. A ghost of a face. Suddenly firmed and we saw "Adam Selene." Was a still picture of a mature man. No background, just a face as if trimmed out of a print. Yet was, to me, "Adam Selene." Could not he anybody else.” Image generation and manipulation has long been a hot topic among AI researchers. The research frequently leverages a technique called Deep Learning, which is a play on classically used Artificial Neural Networks. A 2012 landmark paper from the University of Toronto student Ilya Sutskever, who went on to be a founder at OpenAI, applied deep learning to the problem of image classification with incredible success. Deep learning and computer vision have been inseparable ever since. One part of research focuses on a video focused image superimposition technique called Deep Fakes, which became popular earlier this year. As shown here, these videos are essentially merging existing images and footage with a changing facial structure, which is remarkable and scary at the same time. Deep fakes are gaining so much attention that even the government is focused on learning more about them. Heinlein was early to the game, imaging a computer could create a novel image. I can only imagine how he’d feel about Deep Fakes.

Business Themes

1. Video Conferencing. Manny and the rest of the members of the revolution communicate through encrypted phone conversations and video conferences. While this was certainly ahead of its time, video conferencing was first imagined in the late 1800s. Despite a clear demand for the technology, it took until the late 2000s arguably, to reach appoint where mass video communication was easily accessible for businesses (Zoom Video) and individuals (FaceTime, Skype, etc.) This industry has constantly evolved and there are platforms today that offer both secure chat and video such as Microsoft Teams and Cisco Webex. The entire industry is a lesson in execution. The idea was dreamed up so long ago, but it took hundreds of years and multiple product iterations to get to a de-facto standard in the market. Microsoft purchased Skype in 2011 for $8.5B, the same year that Eric Yuan founded Zoom. This wasn’t Microsoft’s first inroads into video either, in 2003, Microsoft bought Placeware and was supposed to overtake the market. But they didn’t and Webex continued to be a major industry player before getting acquired by Cisco. Over time Skype popularity has waned, and now, Microsoft Teams has a fully functioning video platform separate from Skype – something that Webex did years ago. Markets are constantly in a state of evolution, and its important to see what has worked well. Skype and Zoom both succeeded by appealing to free users, Skype initially focused on free consumers, and Zoom focused on free users within businesses. WebEx has always been enterprise focused but they had to be, because bandwidth costs were too high to support a video platform. Teams will go to market as a next-generation alternate/augmentation of Outlook; it will be interesting to see what happens going forward.

2. Privacy and Secure Communication. As part of the revolution’s communication, a secure, isolated message system is created whereby not only are conversations fully encrypted and undetected by authorities but also individuals are unable to speak with more than two others in their revolution tree. Today, there are significant concerns about secure communication – people want it, but they also do not. Facebook has declared that they will implement end to end encryption despite warnings from the government not to do so. Other mobile applications like Telegram and Signal promote secure messaging and are frequently used by reporters for anonymous tips. While encryption is beneficial for those messaging, it does raise concerns about who has access to what information. Should a company have access to secure messages? Should the government have access to secure messages? Apple has always stayed strong in its privacy declaration, but has had its own missteps. This is a difficult question and the solution must be well thought out, taking into account unintended consequences of sweeping regulation in any direction.

3. Conglomerates. LuNoHo Co is the conglomerate that the revolution utilized to build a massive catapult and embezzle funds. While Mike’s microtransaction financial fraud is interesting (“But bear in mind that an auditor must assume that machines are honest.”), the design of LuNoHo Co. which is described as part bank, part engineering firm, and part oil and gas exploitation firm, interestingly addresses the conventional business wisdom of the times. In the 1960s, coming out of World War II, conglomerates began to really take hold across many developing nations. The 1960s were a period of low interest rates, which allowed firms to perform leveraged buyouts of other companies (using low interest loans), sometimes in a completely unrelated set of industries. Activision was once part of Vivendi, a former waste management, energy, construction, water and property conglomerate. The rationale for these moves was often that a much bigger organization could centralize general costs like accounting, finance, legal and other costs that touched every aspect of the business. However, when interest rates rose in the late 70s and early 80s, several conglomerate profits fell, and the synergies promised at the outset of the deal turned out to be more difficult to realize than initially assumed. Conglomerates are incredibly popular in Asia, often times supported by the government. In 2013, McKinsey estimated: “Over the past decade, conglomerates in South Korea accounted for about 80 percent of the largest 50 companies by revenues. In India, the figure is a whopping 90 percent. Meanwhile, China’s conglomerates (excluding state-owned enterprises) represented about 40 percent of its largest 50 companies in 2010, up from less than 20 percent a decade before.” Softbank, the famous Japanese conglomerate and creator of the vision fund, was originally a shrink-wrap software distributor but now is part VC and part Telecommunications provider. We’ve discussed the current state of Chinese internet conglomerates, Alibaba and Tencent who each own several different business lines. Over the coming years, as internet access in Asia grows more pervasive and the potential for economic downturn increases, it will be interesting to see if these conglomerates break apart and focus on their core businesses.

Dig Deeper

• The rise and fall of Toshiba

• Using Artificial Intelligence to Create Talking Images

• MIT Lecture on Image Classification via Deep Learning

• 2019 Trends in the Video Conferencing Industry

• The Moon is a Harsh Mistress may be a movie

November 2019 - Brotopia: Breaking Up the Boys' Club of Silicon Valley by Emily Chang

This book details a number of factors that have discouraged women’s participation and promotion in the tech industry. Emily Chang gives a brief history of the circumstances that have pushed women away from the industry and then covers its current issues - weaving in great insights and actionable takeaways along the way.

Tech Themes

1. The Antisocial Programmer. As the necessity for technological talent began to rise in the early 1960s, many existing companies were unsure how to hire the right people. To address this shortfall in know-how, companies used standard aptitude tests, like IBM’s Programmer Aptitude Test, to examine whether a candidate was capable of applying the right problem solving skills on the job. Beyond these standard aptitude tests, companies leveraged personality exams. In 1966, a large software company called System Development Corporation hired William Cannon and Dallis Perry to build a personality test that could shed light on the right personalities needed on the job. To build this personality test, Cannon and Perry profiled 1,378 programmers on a range of personality traits. Of those 1,378 profiled, only 186 were women. After compiling their findings, the final report stated: “[Programmers] dislike activities involving close personal interaction; they are generally more interested in things than people.” Furthermore, Cannon and Perry’s 82-page paper made no reference to women at all, referring to the surveyed group as men, for the entire paper. A combination of aptitude tests and Cannon-Perry’s personality test became the industry standard for recruiting, and soon companies were mistakenly focused on stereotypical antisocial programmers. Antisocial personality disorder is three times more common in men than women. Given how early the tech industry was, compared to what it is now, this decision to hire a majority of anti-social men has propagated throughout the industry, with senior leaders continually reinforcing incorrect hiring standards.

2. Women in Computer Science. According to the book, “there was an overall peak in bachelor’s degrees awarded in computer science in the mid-1980s, and a peak in the percentage of women receiving those degrees at nearly 40 percent. And then there was a steep decline in both.” It was at this time in the mid-1980s that computer science departments began to turn away anyone who was not a pre-qualified, academic top performer. There was too much demand with a constrained supply of qualified teachers, so only the best kids were allowed into top programs. This caused students to view computer science as hyper-competitive and unwelcoming to individuals without significant experience. Today, women earn only 18% of computer science degrees – a statistic that shocks many in the industry. Researchers at NPR found that intro CS courses play a key role in this problem – with many teachers still assuming students have prior familiarity with coding. Furthermore, women are socialized in a number of ways to achieve perfection, so when brand new code is not working well, women are more likely to feel discouraged. It is imperative to encourage women to try computer science if they have interest, to combat these negative trends.

3. PayPal and Perpetuating Cycles. After the dot-com bubble burst in the early 2000s, several newly minted millionaires did the natural thing after selling a company for millions of dollars, became a venture capitalists. One of the major success stories of the era was PayPal. Among those newly minted millionaires were the PayPal mafia: Peter Thiel, Keith Rabois, Elon Musk, Max Levchin, David Sacks, and Reid Hoffman. Thiel and Rabois have a history of suggesting a meritocratic process of hiring where only the most qualified academic candidate should land the job, not taking into account diversity of any form. Furthermore, in his book Zero to One (which we’ve discussed before), Thiel proposes startups should hire only “nerds of the same type.” The mafia began investing in several new companies, seeding friends who were likely to perpetuate the cycle of recruiting friends and hiring based on status alone. Rabois, who is currently a venture capitalist has remarked: “Once you have alignment, then I think you can have a wide swath of people, views and perspectives.” These ideas seem more like justification for hiring large groups of white males who were friends of PayPal executives than a truly “meritocratic” process, which is not the best way of building a successful, diverse organization. Roger McNamee, founder of technology private equity firm, Silver Lake, suggests: “They didn’t just perpetuate it; they turned it into a fine art. They legitimized it… The guys were born into the right part of the gene pool, they wind up at the right company, at the right moment in time, they all leave together and [go on] to work together. I give them full credit for it but calling it a meritocracy is laughable.”

Business Themes

1. The Women at Early Google. A lot of people know the story of Sergey Brin meeting co-founder Larry Page. But few are aware of when Sergey and Larry met Susan Wojcicki, who is now CEO of YouTube. Sergey and Larry were looking for office space, and through a mutual friend, were introduced to Susan Wojcicki, who worked in marketing at Intel at the time. Though she didn’t jump on board immediately, Susan eventually came around and was instrumental in launching two of Google’s most important products: AdWords and AdSense. Wojcicki would soon be working closely with a newly recruited, Marissa Mayer, who after graduating from Stanford with a degree in Symbolic Systems, joined Google to help build AdWords and design Google’s front-end. Wojcicki and Mayer would soon be joined by Sheryl Sandberg, who came to Google in 2001 as Vice President of Online Sales and Operations. Another now-famous early female employee was Kim Scott, author of Radical Candor, who joined the company in 2004. All of these early, powerful female leaders, with the continued urging of Larry and Sergey (who wanted to achieve a 50/50 ratio of male to female employees) helped build a strong culture of female leadership. But as the Company scaled it lost sight of its gender diversity goals – “In 2017, women accounted for 31% of employees overall, 25% of leadership roles and 20% of technical roles.” Google claims it lost touch as it scaled, when the need for hiring outpaced the ability to find qualified and diverse candidates – but that sounds like an easy cop out.

2. Startups and Party Culture. Atari and Trilogy Software pioneered the idea of a work-hard, play-hard startup cultures. Nolan Bushnell of Atari would throw wild parties and have employees (including Steve Jobs) work late into the night, building for the company. Trilogy, a provider of sales and marketing software, extended this idea even further. It started with hiring, where, according to a former engineer, Trilogy’s ethos was: “We’re elite talent. It’s potential and talent, not experience, that has merit.” The Company regularly used complicated brain-teasers in interviews and attracted swaths of anti-social engineers with young and attractive talent recruiters. Joe Liemandt, the CEO of Trilogy, also moved the company to Austin, Texas; executives likened the tactic to marooning members of a cult. Co-founder Christy Jones remarked: “I didn’t go on vacation. We called holidays competitive advantage days because no one else was working. It was a chance to get ahead.” The Company had a strong drinking and partying culture and bares striking cult-like resemblance to WeWork, except it had a sustainable business model. Other technology companies have mixed constant alcohol and long hours, which has led to numerous assault charges at well-known startups including Uber, Zenefits, WeWork and others. Startup and party culture does not need to be so intertwined.

3. Hiring Practices to Encourage Diverse Backgrounds. Stewart Butterfield, the founder of Flickr (sold to Yahoo for $20 million in 2005), has focused on diverse hiring efforts at his new company Slack. According to Brotopia, “In 2017, Slack reported that 43.5% of its employees were women, including 48% of managers and almost 30% of technical employees – far better numbers than any tech company in Silicon Valley.” Butterfield, who grew up on a commune in Canada, recognizes his privilege, and discusses its not insanely difficult to create a diverse environment: “As an already successful, white, male, straight – go down the list – I’m not going to have the relevant experience to determine what makes this a good workplace, so some of that is just being open but really just making it an explicit focus.” Slack’s diverse recruiting team was given explicit instructions to source candidates from underrepresented backgrounds and schools for every new role in the organization. More companies should follow Slack’s lead and adopt explicit gender and diversity goals.

Dig Deeper

• Susan Fowler’s blog post describing terrible conditions at Uber

• Overview of gender and diversity statistics of major technology companies

• The Sex and Drug fueled parties of Silicon Valley VCs

• A recap of the Google Walkout over sexual harassment allegations

• The Tech Industry’s diversity is not improving

October 2019 - The Design of Everyday Things by Don Norman

Psychologist Don Norman takes us through an exploratory journey of the basics in functional design. As the consumerization of software grows, this book’s key principles will become increasingly important.

Tech Themes

1. Discoverability and Understanding. Discoverability and Understanding are two of the most key principles in design. Discoverability answers the questions of, “Is it possible to figure out what actions are possible and where and how to perform them?” Discoverability is absolutely crucial for first time application users because poor discovery of actions leads to low likelihood of repeat use. In terms of Discoverability, Scott Berkun notes that designers should prioritize what can be discovered easily: “Things that most people do, most often, should be prioritized first. Things that some people do, somewhat often, should come second. Things that few people do, infrequently, should come last.” Understanding answers the questions of: “What does it all mean? How is the product supposed to be used? What do all the different controls and settings mean?” We have all seen and used applications where features and complications dominate the settings and layout of the app. Understanding is simply about allowing the user to make sense of what is going on in the application. Together, Discoverability and Understanding lay the ground work for successful task completion before a user is familiar with an application.

2. Affordances, Signifiers and Mappings. Affordances represent the set of possible actions that are possible; signifiers communicate the correct action that should take place. If we think about a door, depending on the design, possible affordances could be: push, slide, pull, twist the knob, etc. Signifiers represent the correct action or the action the designer would like you to perform. In the context of a door, a signifier might be a metal plate that makes it obvious that the door must be pushed. Mappings provide straightforward correspondence between two sets of objects. For example, when setting the brightness on an iPhone, swiping up increases brightness and swiping down decreases brightness, as would be expected by a new user. Design issues occur when there is a mismatch in affordances, signifiers and mappings. Doors provide another great example of poor coordination between affordances, signifiers and mappings - everyone has encountered a door with a handle that says push over it. This normally followed by an uncomfortable pushing and pulling motion to discover the actions possible with the door. Why are there handles if I am supposed to push? Good design and alignment between affordances, signifiers and mappings make life easier for everyone.

3. The Seven Stages of Action. Norman lay outs the psychology underpinning user decisions in seven stages - Goal, Plan, Specify, Perform, Perceive, Interpret, Compare. The first three (Goal, Plan, Specify) represent the clarification of an action to be taken on the World. Once the action is Performed, the final three steps (Perceive, Interpret, Compare) are trying to make sense of the new state of the World. The seven stages of action help generalize the typical user’s interactions with the World. With these stages in mind, designers can understand potential breakdowns in discoverability, understanding, affordances, signifiers, and mappings. As users perform actions within applications, understanding each part of the customer journey allows designers to prioritize feature development and discoverability.

Business Themes

1. The best product does not always win, but... If the best product always won out, large entrenched incumbents across the software ecosystem like IBM, Microsoft, Google, SAP, and Oracle would be much smaller companies. Why are there so many large behemoths that won’t fall? Each company has made deliberate design decisions to reduce the amount of customer churn. While most of the large enterprise software providers suffer from Feature Creep, the product and deployment complexity can often be a deterrent to churn. For example, Enterprise CIOs do not want to spend budget to re-platform from AWS to Azure, unless there was a major incident or continued frustration with ease of use. Interestingly enough though, as we’ve discussed, the transition from license-maintenance software to SaaS, as well as the consumerization of the enterprise, are changing the necessity of good design and user experience. If we look at Oracle for example. The business has made several acquisitions of applications to be built on Oracle Databases. But the poor user experience and complexity of the applications is starting to push Oracle out of businesses.

2. Shipping products on time and on budget. “The day a product development process starts, it is behind schedule and above budget.” The product design process is often long and complex because there is a wide array of disciplines involved in the process. Each discipline thinks they are the most important part of the process and may have different reasons for including a singular feature, which may conflict with good design. To alleviate some of that complexity, Norman suggests hiring design researchers that are separate from the product development focus. These researchers focus on how users are working in the field and are coming up with additional use cases / designs all the time. When the development process kicks off, target features and functionality have already been suggested.

3. Why should business leaders care about good design? We have already discussed how product design can act as a deterrent to churn. If processes and applications become integral to Company function, then there is a low chance of churn, unless there is continued frustration with ease of use. Measuring product market fit is difficult but from a metrics perspective; companies can look at gross churn ($ or customer amount that left / beginning ARR or beginning customers) or NPS to judge how well their product is being received. Good design is a direct contributor to improved NPS and better retention. When you complement good design with several hooks into the customers, churn reduces.

Dig Deeper

• UX Fundamentals from General Assembly

• Why game design is crucial for preventing churn

• Figma and InVision - the latest product development tools

• Examples of bad user experience design

• Introduction to Software Usage Analytics

September 2019 - Ready Player One by Ernest Cline

Ernest Cline’s magical world of virtual reality is explores a potential new medium of communication through an excellent heroic tale.

Tech Themes

1. Wide-ranging applicability and use cases of Virtual Reality. Although the novel was written in 2011, Ernest Cline does an incredible job of detailing the complex and numerous use cases of VR throughout the novel. Cline’s 18 year old main character Wade Watts attends school via VR, where you can have a limitless number of students all learn from the same teacher. Beyond that, different worlds and galaxies are easily conjured up with different themes, time periods and technology taking learning and experience to another level: Wade spends time playing old video games in an effort to unlock certain clues about James Halliday, Wade re-enacts all of Matthew Broderick’s part in the movie War Games in an effort to unlock one of the keys, Aech and Wade frequently hang out in the Basement, a re-created 1980’s recreational room with vintage magazines and game consoles. All of these distinct use cases – education, gaming, social networking, and entertainment – are the promise of Virtual Reality. There is a long way to go before that promise is met.

2. The intersection of the online/offline world. As James Halliday writes in Anorak’s Almanac: “Going outside is highly overrated.” Ready Player One does a great job of exploring the conflation of the online and offline worlds. The book weaves together experiences from this intersection into critical moments of the book including Wade’s escape from the Stacks and his imprisonment by IOI. While there is a tangible feeling that online is the much preferred experience for all the reasons discussed above, it’s the offline in-person events that truly shape the heroic ending of the book. This serves as a reminder that the OASIS is very much a virtual reality and explores the need for in-person human connection. Ironically, this is something Halliday sorely missed out on as shown through his unrequited love for Ogden Morrow’s (co-creator of the OASIS) wife, Kira. As big companies move into our homes through Google Homepods, Amazon Echos, Facebook Portals, the human connection element needs to be maintained.

3. The ability to disguise your identity online. “In the OASIS, you could become whomever and whatever you wanted to be, without ever revealing your true identity, because your anonymity was guaranteed.” This quote about the OASIS is largely true of today’s Internet. Through private browsing, Virtual Private Networks, avoiding Google and ad-tagging websites, people are able to stay anonymous online already. But what the OASIS does in addition, is allow you to modify not only your back-story, but also how you appear to others, something that is very important in VR. While there is no question that Wade, Art3mis and Aech are able to avoid insecurities by masking their identities, eventually those insecurities are revealed, albeit with little consequence. Given the myriad of leaks and breaches in the last few years (Yahoo, Facebook, DoorDash, etc.), as the VR ecosystem continues to grow, increasing amounts of privacy will be needed to maintain anonymity.

Business themes

1. What is the dominant revenue model in VR? The evil villains at Innovative Online Industries (IOI) and their army of sixers have tried several hostile takeover attempts to acquire Halliday’s Gregarious Simulations Systems in order to convert it to a paid user model. IOI is the world’s largest internet service provider and just like other three letter named tech behemoths (cough, IBM, cough), fits the classic evil corporation vibe. Dismissing the potential business and technology conflicts (the world’s largest ISP is probably critical in delivering the OASIS throughout the world), its interesting to theorize what the dominant revenue model of VR may be. Facebook recently launched its VR world to complement its Oculus devices and there have been varied attempts to launch similar software worlds like Rec Room. The big discovery Google made early on was that advertising would be the business model of the web. Facebook copied this as it created social networking and as devices transitioned from desktop to mobile, and image to video, advertising continued to be the dominant mode of content monetization. Is there any reason to think VR will be any different? Potentially. The current dominant model for video gaming is subscriber based, freemium (paying for enhanced abilities, character changes, etc.) or single purchase. While there is no reason these ideas can’t be combined with advertising, the idea of a multi-world VR landscape may reduce some of the targeted ROI you receive from very specific ad-targeting on Instagram and Google today. In a limitless world, advertising to specific people will be difficult. Beyond that, porting the mish-mash of complex technologies used in today’s advertising landscape would add even more challenge.

2. The BIG, evil tech corporation. IOI is the quintessential evil technology company. As the world’s largest ISP, IOI could be a reference to Comcast, which is the United States’ largest ISP and often referenced as one of the most hated companies. Comcast, like other ISPs is always facing the challenge of serving millions of subscribers but unlike other companies, they are monopolistic in certain areas where they are the only viable provider for internet, allowing them to raise prices and treat customers poorly. The big, evil technology corporation cliché has been around for a long time and today’s largest tech companies have all spent sometime being that cliché. This dynamic can arise for many reasons. At Amazon, it’s the continued alienation of open source communities, the anti-competitive behavior around its search algorithm and the smothering of small vendors on its marketplace. Facebook and Google have both faced privacy concerns. Google has been sued for manipulating search on mobile devices. Microsoft was sued for anti-trust issues over browsers. As startups begin to dominate their core businesses, unless they continue innovating, they begin acting defensively to maintain their leading position. Facebook feature copied Snapchat stories almost immediately after they came out. IBM had a book written on them in the 1980s claiming they were anticompetitive. There is a reason corporate communications (WeWork lol) are so important and maintaining the image of a positive change for good. Every major technology company has spent time as the evil one, some have just spent more time than others.

3. Difficulty in creating VR applications. Ready Player One stoked a lot interest in the promise of VR, but the actual implementation is incredibly difficult with the hardware and software we have available as tools today. Moore’s law is slowing and some computer scientists have suggested specific chips to address the demands of newer technologies like Artificial Intelligence, Virtual Reality and Deep Learning. After Facebook acquired Oculus in 2014 for $2.4B, funding continued to flow into VR startups. Magic Leap, the highly secretive and most heavily funded VR startup has raised $2.3B on its own, and after years of development finally released its hardware for over $2,000 per device and its unclear if it makes a profit on any sales yet. More recently, several VR companies have gone bankrupt and laid off employees as product development didn’t reach application or end users before the funding ran out. While the software and hardware continues to improve, a lot still needs to be figured out before VR becomes mainstream.

Dig Deeper

• VR Garden in Montreal

• Oculus co-founder Palmer Lucky’s review of Magic Leap

• Augmented Reality and Virtual Reality in Healthcare

• Deep dive into the secretive Magic Leap

• The real world easter egg hunt from Ready Player One

July 2019 - Alibaba: The House That Jack Ma Built by Duncan Clark

This is an excellent book to understand Jack Ma, Alibaba and the Chinese tech ecosystem.

Tech Themes

1. Start with a Team: Alibaba’s 18 founders. At a young age, Jack Ma taught himself English by offering tours of his hometown Hangzhou to locals coming from English speaking countries. Jack went on to study English at Hangzhou Teachers Institute where he graduated in 1988. Following graduation, he taught English for a few years and because of his English skills, he was selected to go on a trip to America, on behalf of the Hangzhou government. While there, he tried using the internet to look up “beer” and noticed there were very few Chinese web pages. When he got back to China, he started China Pages, a custom website development shop for Chinese businesses. The business received funding from the Ministry of Foreign Trade and Economic Cooperation but was losing out to rival telecom company Hangzhou Communications that had recently started a competitor. China Pages was struggling to help customers realize return on their investments because there was so little business happening online at that time in China. Frustrated by competition and worried about the long-term effects of being funded by the government, Jack rounded up a group of 17 people - some were former students, some colleagues in the government, some employees at China Pages - and started Alibaba. Jack also met and recruited Joe Tsai, the first Taiwanese graduate of Yale Law School, who was then working at Investor AB on private equity investments, to join as CFO and founding board member. The team focused on the business to business market which they felt should gain more traction before business to consumer focused companies like Amazon.

2. Open Door Policies: How China became an economic powerhouse. In 2009, China became the World’s biggest exporter, a trend that until recently, seemed all the more likely to continue. But how did we get to this point in China? In 1979, Deng Xiaoping began a series of economic reforms in China that set the stage for enormous growth. The first major act was allowing Chinese individuals to start businesses, a practice that had been strictly forbidden during the previous political era. Next, Deng announced an Open Door Policy, to allow foreign business and investment to flow into specific, Special Economic Zones. This investment spawned incredible growth in now-famous Chinese regions including Shenzhen, which grew GDP on average of 40% per year from 1981 to 1993 and by 2005 became the world’s 3rd busiest port. This incredible growth has created massive companies and seen incredible innovation but has also created global pollution. How sustainable is this great economic expansion?

3. Right Place at the Right Time: The Importance of Timing in Innovation at Alibaba. When trying to build a business, timing can often be more important than the product itself. This can work in a number of ways - during the internet bubble, several entrepreneurs became millionaires on the backs of grandiose ideas without business models. Alibaba is the perfect example of excellent timing. Alibaba was founded in 1999, right as the internet bubble started to heat up. As valuations rose, institutional investors saw returns skyrocketing; this led Goldman Sachs to open up a dedicated Asia Tech fund, focused on investing small amounts into growing Chinese tech companies. Goldman led Alibaba’s first round in 1999 (a $3.3M fundraise), which allowed Alibaba to grow to significant scale with their tight founding team. The internet bubble also attracted a now re-famous Masayoshi Son, and his software distributor turned VC firm, Softbank, to start investing heavily in the internet. Aliababa was by no means the only fast growing Asian Tech company: Sohu (Founded in 1996 by Charles Zhang), Sina (founded in 1998 by Charles Chao who pioneered the Variable Interest Entity designation in China), and NetEase (Founded in 1997 by Ding Lei) were the famed Asian tech darlings of the day. In March 2001, right before the bubble burst, Softbank led a $20M round into Alibaba (which we discuss more below) that allowed Jack the flexibility to weather the internet bubble storm and keep Alibaba private despite growing losses. Sohu, Sina, and NetEase all needed to IPO and limped out into the public markets at poor valuations (Sohu dropped below $1 per share at one point), which caused a long-term drag on their stock prices and business performance. While Alibaba clearly had reached product-market fit by that time, their fortuitous timing (much like that of Amazon’s bond offering) allowed the Company to stay in business during a tough financial time.

Business Themes

1. Different Approaches to Similar Problems: Amazon vs. Alibaba. Alibaba is often hailed as the Amazon of China, but it’s actually, quite different in many major aspects. As discussed recently in this Stratechery article, Amazon’s core e-commerce business is about controlling inventory and logistics. Amazon buys at whole sale prices from brands, keeps the inventory in their 400+ warehouses and ships them out to customers. Retailers pay Amazon a fee on the sale as commission. While this revenue model is similar to Alibaba’s Tmall, a major brand e-commerce site that charges commissions on sale, Alibaba does not retain any inventory in the process. Furthermore, on Alibaba’s Taobao, independent small merchants can list any item for sale and pay no commissions, instead they pay for higher ranking on the site’s internal search engine, similar to Google’s revenue model. While Amazon boxes are delivered nationwide, primarily by Amazon, in China, Alibaba leverages a slew of 3rd party logistics providers to deliver packages any way possible: via bike, motorcycle, car, or on foot. This impacts profit margins as Amazon has to employ its entire logistics operation (350,000+ people) whereas Alibaba is comparatively smaller at 50,000 employees. Beyond their core e-commerce businesses, both Alibaba and Amazon have cloud computing offerings – as discussed before, AWS is the biggest platform in North America, and Alibaba is the biggest in China. While cloud in China is now growing more quickly than North America, it remains a much smaller piece of the overall global cloud landscape.

2. A Lesson in Investing: Analyzing Goldman, Softbank, and Yahoo’s Returns. Alibaba’s funding history is long and complex but illustrates a common dilemma faced by investors and shareholders in startups. Alibaba’s first funding round was led by Goldman Sachs at a $5M pre-money valuation. The next round was a $20M investment in Alibaba, led by Softbank to acquire 1/3 of the Company. At the next funding round in 2004, Softbank invested in an $82M round and Goldman sold its shares, thereby inking a 6.7x return in about 5 years, which by all means is a great investment. However, if Goldman had held on to that share, as Softbank did with its share, at IPO it would have been worth $12.5B, a 3,600x+ return. This is the dilemma faced by several VCs – do I sell now, ink a great return, and make my limited partners happy? Or do I risk it, let my winners ride and realize a potentially career changing win? Yahoo is another example of this complex dilemma. Yahoo invested $1B in Alibaba in 2005 for a 40% stake in the Company (a funding round that was allegedly hashed out over golf at Pebble Beach). After rebuffing Microsoft’s $44.6B offer to buy the Company, Yahoo’s stock price plummeted. A difficult fight with activist investors ensued, and Jerry Yang was eventually fired. This all set up nicely for new CFO, Scott Thompson to come in and promptly offload half of its Alibaba stake for $7.1B, two years later that would be worth $51B. Yahoo, now owned by Verizon, sold its remaining stake earlier this year, and its expected to net shareholders roughly $40B in value.

3. The Everything Companies: The Holdings of Chinese Internet Giants. The number and variety of companies owned by the major tech giants in China is simply staggering. Alibaba has bet big on a wide variety of companies including delivery giant Meituan-Dianping, Lyft, Snap, bike sharing startup Ofo, Chinese ride-hailing company Didi (which recently merged with Uber’s China business), fintech spinoff Ali-Pay and several others. Tencent, creator of the famous all-in-one application, WeChat, has invested in JD.com, League of Legends creator Riot Games, Fortnite creator Epic Games, and many more. Alibaba and Tencent are so competitive with one another that in recent years, the Companies have made thousands of investments trying to fund the next phase of growth in Chinese Tech. As the economist writes, “Tencent has a portfolio of 600 stakeholdings acquired over the past six years (see chart), many unannounced. There is barely a trace of bombast when Jack Ma, Alibaba’s founder, says that he eventually hopes to see former Alibaba employees running 200 of the top 500 Chinese firms.” It will be interesting to see how these investments mature – in 2018 rival delivery firms Meituan and Dianping had to merge to avoid going bankrupt despite billions in funding from Alibaba and Tencent.

Dig Deeper

• The Rise of China's Innovation Machine by WSJ

• Detail on the Uber-Didi ride-sharing merger in China from Business Insider

• 9:00am - 9:00pm, 6 days a week (9-9-6) is what Jack Ma wants out of his employees

• Jack Ma hated eBay

• Tencent’s Investment in Epic Games / Fortnite

June 2019 - Zero to One by Peter Thiel

Peter Thiel’s contrarian startup classic, Zero to One, is a great book for understanding and building startups.

Tech Themes

1. Zero to One. As Thiel explains in the opening pages, Zero to One is the concept of creating companies that bring new technology into the world: “The single word for vertical, 0 to 1 progress is technology.” This is in contrast to startups that simply copy existing ideas or other products and tackle problems 1 to n. In Thiel’s view, the great equalizer that allows you to create such an idea is proprietary technology. This can come in many forms: Google’s search algorithms, Amazon’s massive book catalog, Apple’s improved design of the iPad or PayPal’s faster integrated Ebay payments. But generally, to capture significant value from a market; the winning technology has to be 10x better than competition. To this end, Thiel says, “Don’t disrupt.... If your company can be summed up by its opposition to already existing firms, it can’t be completely new and it’s probably not going to become a monopoly.” The true way to become a massively successful company is to build something completely new that is 10x better than the way its currently being done. This 10x better product has to be conceived over the long term, with the idea that the final incremental feature added to the product gives it that 10x lift and takes it to monopoly status.

2. Beliefs and Contrarianism. Thiel begins the book with a thought-provoking question: “What important truth do very few people agree with you on?” To Thiel, however you answer this question indicates your courage to challenge conventional wisdom and thus your potential ability to take a novel technology from 0 to 1. Extending this idea, Thiel defines the word startup as, “the largest group of people you can convince of a plan to build a different future.” This sort of Silicon Valley contrarianism is exactly the mindset of Internet bubble entrepreneurs. Thiel continues on this thinking, with another question: “Can you control your future?” and to that question he answers with an emphatic, “Yes.” People are taught to believe that “right place, right time” or “luck” is the greatest contributor to individual success. And as discussed in Good to Great, while many CEOs and prominent executives make this claim, they often don’t believe it and use it much more as a marketing mechanism. Thiel firmly believes in the idea of self-determination, and why shouldn’t he? He’s a white male, Rhodes Scholar and Stanford Law School graduate who has now made billions of dollars. In his mind, you either believe something novel and create that future or you waste your time tackling the problems that exist today. This also conveniently mirrors Thiel’s investing focus and he even calls this out in a chapter detailing venture returns. Venture takes informed speculative bets on which technology will ultimately win out in a market – the best bets are the ones that differ so greatly from the established norm because the likelihood of landing in the monopoly position (though still small) is much greater than a Company that is recreating existing products.

3. Looking for Secrets and Building Startups. The answers to the Thiel question posed above are secrets: knowable but undiscovered truths that exist in the world today. He then poses: “Why has so much of our society come to believe that there are no hard secrets left?” He provides a four part answer:

• Incrementalism – the idea that you only have to hit a minimum threshold for pre-determined success and that over-achieving is frequently met with the same reward as basic achievement

• Risk Aversion – People are more scared than ever about being wrong about a secret they believe

• Complacency – people are fine collecting rents on things that were already established before they were involved

• Flatness – the idea that as globalization continues, the world is viewed as one hyper competitive market for all products

Sticking on his contrarian path, Thiel emphasizes: “The best place to look for secrets is where no else is looking…What are people not allowed to talk about? What is forbidden or taboo?” This question is especially interesting in the context of the latest round of startups going public. A lot of people have argued that the newest wave of startups are tackling problems that are of lower value to society, like food delivery – focused on pleasing an increasingly on-demand, dopamine driven world. Why is that? Have we reached a local maximum in technology for a given period? While you may not completely believe Ray Kurzweil’s Law of Accelerating Returns, the pace of technological evolution has probably not hit a maximum. It could be argued that we have enjoyed a great run with mobile as a dominant computing platform (PCs before that, Mainframes before that, etc.) and that the next wave of startups tackling “important" problems could spring out of such a development.

Business Themes

1. Monopoly profits. Thiel plainly states the overarching goal of business that is normally obfuscated by cult-like Silicon Valley startups: monopoly profits. This touches on a point that has been bouncing its way through the news media (Elizabeth Warren, Stratechery, Spotify/Apple) in recent months with Elizabeth Warren calling for a breakup of Apple, Facebook and Amazon, Spotify claiming the App Store is a monopoly, and others discussing whether these companies are even monopolies. He claims monopolies deserve their bad press and regulation, “only in a world where nothing changes.” Monopolies in a static environment act like rent collectors: “If you corner the market for something, you can jack up the price; others will have no choice but to buy from you.” This is true of many heavy regulated industries today like Utilities. It’s often the case consumers only have one or two providers to choose from at max, so governments regulate the amount utilities can increase prices each year. Thiel then explains what he calls creative monopolists, companies that “give customers more choice by adding entirely new categories of abundance to the world. Creative monopolies aren’t just good for the rest of society: they’re powerful engines for making it better.” Thiel cites a few interesting examples of “monopoly” disruption: Apple iOS outcompeting Microsoft operating systems, IBM hardware being overtaken by Microsoft software, and AT&T’s monopoly prior to being broken up. It should be noted that two of these examples actually did require government regulation – Microsoft was sued in 2001 and AT&T was forced to break up its monopoly. What’s even more interesting, is the prospect of the T-Mobile/Sprint merger being blocked because while the consolidation of the telecom industry could mean increased prices, both T-Mobile and Sprint have struggled to compete with guess who, AT&T and Verizon (who started as a merger with former AT&T company, Bell Atlantic). Whether monopolies are good or bad for society, whether its possible to call tech companies with several different business lines monopolies remains to be seen – but one things for sure – being a monopoly, tech monopoly, or creative monopoly is a great thing for your business.

2. Prioritizing Near Term Growth at the Risk of Long Term Success. Thiel begins his chapter on Last Mover Advantage with an interesting discussion on how investors view LinkedIn’s valuation (since acquired by Microsoft but at the time was publicly traded). At the time, LinkedIn had $1B in revenue and $21M in net income, but was trading at a value of $24B (i.e. 24x LTM Revenue and 1100x+ Net Income). Why was this valued so highly? Thiel provides an interesting answer: “The overwhelming importance of future profits is counterintuitive even in Silicon Valley. For a company to be valuable it must grow and endure, but many entrepreneurs focus on short-term growth. They have an excuse: growth is easy to measure, but durability isn’t.” Thiel then continues with two great examples of short-term focus: “Rapid short-term growth at Zynga and Groupon distracted managers and investors from long-term challenges.” Zynga became famous with Farmville, but struggled to find the next big hit and Groupon posted incredibly fast growth, but couldn’t get sustained repeat customers. This focus on short-term growth is incredibly interesting given the swarm of unicorns going public this year. Both Lyft and Uber grew incredibly quickly, but as the public markets have showed, the ride-sharing business model may not be durable with each company losing billions a year. Thiel continues: “If you focus on near term growth above all else, you miss the most important question you should be asking: will this business still be around a decade from now?” To become a durable tech monopoly, Thiel cites the following important characteristics: proprietary technology, network effects, economies of scale, and branding. It’s interesting to look at these characteristics in the context of a somewhat monopoly disruptor, Zoom Video Communications. CEO Eric Yuan, who was head of engineering at Cisco’s competing WebEx product, built the Company’s proprietary tech stack with all the prior knowledge of WebEx’s issues in mind. Zoom’s software is based on a freemium model, when one user wants to video chat with another, they simply send the invite regardless of whether they have the service already – this isn’t exactly a google-esque network effect but it does increase distribution and usage. Zoom’s technology is efficiently scalable as shown by the fact that its profitable despite incredibly fast growth. Lastly, Zoom’s marketing and branding are excellent and are repeatedly lauded within the press. The question is, are these characteristics really monopoly defining? Or are they simply just good business characteristics? We will have to wait and see how Zoom fairs over the next 10 years to find out.

3. Asymmetric Risk & VC Returns. Thiel started venture capital firm, Founders Fund in 2005 with Ken Howery (who helped start PayPal with Thiel). Thiel notes an interesting phenomena about VC returns that several entrepreneurs don’t truly understand: “Facebook the best investment in our 2005 fund, returned more than all the others combined. Palantir, the second best investment is set to return more than the sum of every investment aside from Facebook…The biggest secret in venture capital is that the best investment in a successful fund equals or outperforms the entire rest of the fund combined.” Venture capital investing, especially at the earliest stages like Seed and Series A (where Founder’s Fund invests) is a game of maximizing the chance of one or two big successes. In the past five to ten years, there has been a significant increase in venture capital investing, and with that a focus among many firms to be founder friendly. As discussed before, these founder friendly cultures have led to super-voting shares (like Snap, FB and others) and unprecedented VC rounds. Even with these changes, there is still a friction at most VC-backed companies: the supposedly value added VC board member doesn’t believe that Company XYZ will be the next Facebook or Palantir, and because of that chooses to spend as little time with them as possible. This has fueled the somewhat anti-VC movement that several entrepreneurs have adopted because as with Elon Musk at PayPal and Zip2, being abandoned by your earliest investors can be devastating.

Dig Deeper

• Facebook Chris Hughes co-founder calls for the breakup of Facebook

• Thiel wrote the first check into Facebook at a $5M valuation

• An overview of the PayPal Mafia

• A new book on scaling quickly by PayPal Mafia member Reid Hoffman

May 2019 - The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone

This book is a great deep dive on the history of Amazon and how it became the global powerhouse that it is today.

Tech Themes

1. The Birth of AWS. We’ve looked at the software transition from on premise, license maintenance software to SaaS hosted in the cloud, but let’s dive deep into how the cloud came to be. The first ideas of AWS go back to 2002 when Bezos met with O’Reilly Media, a book publisher who in order to compete with Amazon, had created a way to scrape the latest book rankings off Amazon’s website. O’Reilly suggested creating a set of tools to let developers access Amazon’s rankings, and in 2003 Amazon launched Amazon Web Services (AWS) to create commerce API’s for third parties. Around this time, Amazon had centralized its IT computing resources in a separate building with hardware professionals operating and maintaining the infrastructure for the entire company. While parts of the infrastructure had improved, Amazon was struggling internally to provision and scale its computing resources. In 2004, Chris Pinkham, head of the infrastructure division, relocated to South Africa to open up Amazon’s first office in Cape Town. His first order of business was to figure out the best way to provision resources internally to allow developers to work on all types of applications on Amazon’s servers. Chris elected to use Xen, a computer that sits on top of infrastructure and acts as a controller to allow multiple projects access the same hardware. This led to the development of Elastic Compute Cloud (EC2). During this time, another group within Amazon was working on solving the problem of storing the millions of gigabytes of data Amazon had created. This team was led by Alan Atlas, who could not escape Bezos’ laser focus: “It would always start out fun and happy, with Jeff’s laugh rebounding against the walls. Then something would happen and the meeting would go south and you would fear for your life. I literally thought I’d get fired after everyone one of those meetings.” In March 2006, Amazon launched the Simple Storage Service (S3), and then a few months later launched EC2. Solving internal problems can lead to incredibly successful companies; Slack, for example, originally started as a game development company but couldn’t get the product off the ground and eventually pivoted into the messaging giant that it is today: “Tiny Speck, the company behind Glitch, will continue. We have developed some unique messaging technology with applications outside of the gaming world and a smaller core team will be working to develop new products.”

2. A9. In the early 2000s, Google arrived on the scene and began to sit in between Amazon and potential sales. Around this time, Amazon’s core business was struggling and a New York Times article even called for Bezos to resign. Google was siphoning off Amazon’s engineers and Bezos knew he had to take big strategic bets in order to ward off Google’s advances. To do that, he hired Udi Manber, a former Yahoo executive with a PhD in computer science who had written the authoritative textbook on Algorithms. In 2003, Udi set up shop in Palo Alto in a new Amazon subsidiary called A9 (shorthand for Algorithms). The new subsidiary’s sole goal was to create a web search engine that could rival Google’s. While A9.com never completely took off, the new development center did improve Amazon’s website search and created Clickriver, the beginning of Amazon’s advertising business, which minted $10B in revenue last year. Udi eventually became VP of Engineering for all of Google’s search products and then its Youtube Division. A9 still exists to tackle Amazon’s biggest supply chain math problems.

3. Innovation, Lab126 and the Kindle. In 2004, Bezos called Steve Kessel into his office and moved him from his current role as head of Amazon’s successful online books business, to run Amazon Digital, a small and not yet successful part of Amazon. This would become a repeating pattern in Kessel’s career who now finds himself head of all of Amazon’s physical locations, including its Whole Foods subsidiary. Bezos gave Kessel an incredibly abstract goal, “Your job is to kill your own business. I want you to proceed as if your goal is to put everyone selling physical books out of a job.” Bezos wanted Kessel to create a digital reading device. Kessel spent the next few months meeting with executives at Apple and Palm (make of then famous Palm Pilots) to understand the current challenges in creating such a device. Kessel eventually settled into an empty room at A9 and launched Lab126 (1 stands for a, 26 for z – an ode to Bezos’s goal to sell every book A-Z), a new subsidiary of Amazon. After a long development process and several supply chain issues, the Company launched the Kindle in 2007.

   Business Themes

4. Something to prove: Jeff Bezos’s Childhood. What do Jeff Bezos, Steve Jobs, Elon Musk and Larry Ellison (founder of Oracle) all have in common? They all had somewhat troubled upbringings. Jobs and Ellison were famously put up for adoption at young ages. Musk’s parents divorced and Elon endured several years of an embattled relationship with his father. Jeff Bezos was born Jeffrey Preston Jorgenson, on January 12, 1964. Ted Jorgenson, Bezos’s biological father, married his mother, Jackie Gise after Gise became pregnant at age sixteen. The couple had a troubled relationship and Ted was immature and an inattentive father. The couple divorced in 1965. Jacklyn eventually met Miguel Bezos, a Cuban immigrant college student, while she was working the late shift at the Bank of New Mexico’s accounting department. Miguel and Jacklyn were married in 1968 and Jeffrey Jorgenson became Jeffrey Bezos. Several books have theorized the maniacal drive of these entrepreneurs relates back to ultimately prove self-worth after being rejected by loved ones at a young age.

5. Anti-Competitive Amazon & the Story of Quidsi. Amazon has an internal group dubbed Competitive Intelligence, that’s sole job is to research the products and services of competitors and present results to Jeff Bezos so he can strategically address any places where they may be losing to the competition. In the late 2000s, Competitive Intelligence began tracking a company known as Quidsi, famous for its site Diapers.com, which provided discount baby products that could be purchased on a recurring subscription basis. Quidsi had grown quickly because it had customized its distribution system for baby products. In 2009, competitive intelligence reached out to Quidsi founder, Marc Lore (founder of Jet.com and currently the head of Walmart e-commerce) saying it was looking to invest in the category. After rebuffing the offer, Quidsi soon noticed that Amazon was pricing its baby products 30% cheaper in every category; the company even tried dropping prices lower only to see Amazon pages reset to even lower prices. After a few months, Quidsi knew they couldn’t remain in a price battle for long and launched a sale of the company. Walmart agreed in principle to acquire the business for $900M but upon further diligence reduced its bid, which prompted Lore to call Amazon. Lore and his executive team went to meet with Amazon, and during the meeting, Amazon launched Amazon Mom, which gave 30% discounts on all baby products and allowed participants to purchase products on a recurring basis. At one point, Amazon’s prices dipped so low it was on track to lose $100M in three months in the diapers category alone. Amazon submitted a $540M bid for Quidsi and subsequently entered into an exclusivity period with the Company. As the end to exclusivity grew nearer, Walmart submitted a new bid at $600M, but the Amazon team threatened full on price war if Quidsi went with Walmart, so on November 8, 2010, Quidsi was acquired by Amazon for $540M. One month after the acquisition, Amazon stopped the Amazon Mom program and raised all of its prices back to normal levels. The Federal Trade Commission reviewed the deal for four months (longer than usual), but ultimately allowed the acquisition because it did not create a monopoly in the sale of baby products. Quidsi was ultimately shut down by Amazon in 2017, because it was unable to operate it profitably.

6. The demanding Jeff Bezos and six page memos. At Amazon, nobody uses powerpoint presentations. Instead, employees write out six page narratives in prose. Bezos believes this helps create clear and concise thinking that gets lost in flashy powerpoint slides. Whenever someone wants to launch new initiative or project, they have to submit a six page memo framed as if a customer might be hearing it for the first time. Each meeting begins with the group reading the document and the discussion begins from there. At times, especially around the release of AWS, these documents grew increasingly complex in length and size given the products being described did not already exist. Bezos often responds intensely to these memos, with bad responses including: “Are you just lazy or incompetent?” and “If I hear that idea again, I’m gonna have to kill myself” and “This document was clearly written by the B team. Can someone get me the A team document? I don’t want to waste my time with the B team document.” Its no wonder Amazon is such a terrible place to work.

Dig Deeper

• How Amazon took the opposite approach that apple took to pricing EC2 and S3

• The failed Amazon Fire Phone and taking big bets

• The S Team - Amazon’s intense executives

• The little-known deal that saved Amazon from the dot-com crash

• Mary Meeker, Amazon and the internet bubble: Amazon.bomb: How the internet's biggest success story turned sour

• Customer Centric: Amazon Celebrates 20 Years Of Stupendous Growth As 'Earth's Most Customer-Centric Company

April 2019 - Only the Paranoid Survive by Andrew S. Grove

This book details how to manage a company through complex industry change. It is incredibly prescient and a great management book.

Tech Themes

1. The decoupling of hardware and software. In the early days of personal computers (1980s) the hardware and software were both provided by the same company. This is complete vertical alignment, similar to what we’ve discussed before with Apple. The major providers of the day were IBM, Digital Equipment Corporation (DEC - Acquired by Compaq which was acquired by HP), Sperry Univac and Wang. When you bought a PC, the sales and distribution, application software, operating system, and chips were all handled by the same Company. This created extreme vendor lock-in because each PC had different and complicated ways of operating. Customers typically stayed with the same vendor for years to avoid the headache of learning the new system. Over time, driven by the increases in memory efficiency, and the rise of Intel (where Andy Grove was employee #3), the PC industry began to shift to a horizontal model. In this model, retail stores (Micro Center, Best Buy, etc.) provided sales and distribution, dedicated software companies provided applications (Apple at the time, Microsoft, Mosaic, etc.), Intel provided the chips, and Microsoft provided the operating system (MS-DOS, then Windows). This decoupling produced a more customized computer for significantly lower cost and became the dominant model for purchasing going forward. Dell computers were the first to really capitalize on this trend.

2. Microprocessors and memory chips. Intel started in 1968 and was the first to market with a microchip that could be used to store computer memory. Demand was strong because it was the first of its kind, and Intel significantly ramped up production to satisfy that demand. By the early eighties, it was a computer powerhouse and the name Intel was synonymous with computer memory. In the mid-eighties, Japanese memory producers began to appear on the scene and could produce higher-quality chips at a cheaper cost. At first, Intel saw these producers as a healthy backup plan when demand exceeded Intel’s supply, but over time it became clear they were losing market share. Intel saw this commoditization and decided to pivot out of the memory business and into the newer, less-competitive microprocessor business. The microprocessor (or CPU) handles the execution of tasks within the computer, while memories simply store the byproduct of that execution. As memory became easier to produce, the cost dropped dramatically and business became more competitive with producers consistently undercutting each other to win business. On the other hand, microprocessors became increasingly important as the internet grew, applications became more complex and computer speed became a top-selling point.

3. Mainframes to PCs. IBM had become the biggest technology company in the world on the backs of mainframes: massive, powerful, inflexible, and expensive mega-computers. As the computing industry began to shift to PCs and move away from a vertical alignment to a horizontal one, IBM was caught flat-footed. In 1981, IBM chose Intel to provide the microprocessor for their PC, which led to Intel becoming the most widely accepted supplier of microprocessors. The industry followed volume - manufacturers focused on producing on top of Intel architecture, developers focused on developing on the best operating system (Microsoft Windows) and over time Intel and Microsoft encroached on IBM’s turf. Grove’s reasoning for this is simple: “IBM was composed of a group of people who had won time and time again, decade after decade, in the battle among vertical computer players. So when the industry changed, they attempted to use the same type of thinking regarding product development and competitiveness that had worked so well in the past.” Just because the company has been successful before, it doesn’t mean it will be successful again when change occurs.

The six forces acting on a business at any time. When one becomes outsized, it can represent a strategic inflection point to the business.

Business Themes

1. Strategic Inflection Points and 10x forces. A strategic inflection point is a fundamental shift in a business, due to industry dynamics. Examples of well known shifts include: mainframes to PCs, vertical computer production to horizontal production, on-premise hardware to the cloud, shrink-wrapped software to SaaS, and physical retail to e-commerce. These strategic inflection points are caused by 10x forces, which represent the underlying shift in the technology or demand that has caused the inflection point. Deriving from the Porter five forces model, these forces can affect your current competitors, complementors, customers, suppliers, potential competitors and substitutes. For Intel, the 10x force came from their Japanese competitors which could produce better quality memories at a substantially lower cost. Recognizing these inflection points can be difficult, and takes place over time in stages. Grove describes it best: “First, there is a troubling sense that something is different. Things don’t work the way they used to. Customers’ attitudes toward you are different. The trade shows seem weird. Then there is a growing dissonance between what your company thinks it is doing and what is actually happening inside the bowels of the organization. Such misalignment between corporate statements and operational actions hints at more than the normal chaos that you have learned to live with. Eventually, a new framework, a new set of understandings, a new set of actions emerges…working your way through a strategic inflection point is like venturing into what i call the valley of death.”

2. The bottoms up, top-down way to “Let chaos reign.” The way to respond to a strategic inflection point comes through experimentation. As Grove says, “Loosen up the level of control that your organization normally is accustomed to. Let people try different techniques, review different products. Only stepping out of the old ruts will bring new insights.” This idea was also recently discussed by Jeff Bezos in his annual shareholder letter - he likened this idea to wandering: “Sometimes (often actually) in business, you do know where you’re going, and when you do, you can be efficient. Put in place a plan and execute. In contrast, wandering in business is not efficient … but it’s also not random. It’s guided – by hunch, gut, intuition, curiosity, and powered by a deep conviction that the prize for customers is big enough that it’s worth being a little messy and tangential to find our way there. Wandering is an essential counter-balance to efficiency. You need to employ both. The outsized discoveries – the “non-linear” ones – are highly likely to require wandering.” When faced with mounting evidence that things are changing, begin the process of strategic wandering. This needs to be coupled with bottom-up actions from middle managers who are exposed to the underlying industry/technology change on a day to day basis. Strategic wandering reinforced with the buy-in and action of middle management can produce major advances as was the case with Amazon Web Services.

3. Traversing the valley of death. The first task in traversing through a strategic inflection point is to create a clear, explainable, mental image of what the business looks like on the other side. This becomes your new focus and the Company’s mantra. For Intel, in 1986, it was, “Intel, the microcomputer company.” This phrase did two things: it broke the previous synonymy of Intel with ‘memory’ and signaled internally a new focus on microprocessors. Next, the Company should redeploy its best resources to its biggest problems, including the CEO. Grove described this process as, “going back to school.” He met with managers and engineers and grilled them with questions to fully understand the state and potential of the inflection point. Once the new direction is decided, the company should focus all of its efforts in one direction without hedging. While it may feel comfortable to hedge, it signals an unclear direction and can be incredibly expensive.

Dig Deeper

• Mapping strategic inflection points to product lifecycles

• Review of grocery strategic inflection points by Coca-cola

• Strategic inflection point for Kimberly Clark in the paper industry: “Sell the Mills”

• Andy Grove survived the Nazi and Communist regimes of Hungary

• Is Facebook at a strategic inflection point?

March 2019 - Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future by Ashlee Vance

This a great book to learn about Elon’s upbringing, his rise to stardom and his crazy life at SpaceX and Tesla.

Tech Themes

1. Owning the manufacturing process. Throughout the book, Vance references the enormous benefits that Tesla and SpaceX receive for developing their technology in-house. The first is a reduced overall cost basis; Musk will routinely demand complex hardware parts be built for way less than the market rate. In one instance, an engineer spent nine months completely recreating an actuator that was already commercially available from several vendors in order to keep prices down. When the engineer emailed Musk to tell him he had completed the months-long project, Musk simply replied: “Ok.” Owning the manufacturing process means higher upfront costs but significantly reduced long-term costs.

2. Significant IP creation. A good example of this is Tesla’s Powerwall batteries. Tesla CTO JB Straubel invented the famous rechargeable lithium-ion batteries that power Tesla’s vehicles, but he also realized that Tesla’s proprietary packaging and cooling systems could work in industrial batteries. In 2015, Tesla launched the Powerwall which has now become the backbone of several energy storage facilities throughout the world. Owning the manufacturing process opened ancillary business opportunities for Tesla.

3. Hardware is hard. As former Musk co-worker, Apple iPod creator, and Nest founder, Tony Fadell, has said “Hardware is Hard, That’s Why They Call it Hardware” Musk’s initial projections were years off for both Tesla and SpaceX. As Musk admitted in 2007, after SpaceX’s first failed launch: “I thought it would be hard, and it's harder than I thought.” Musk’s companies have raised billions of dollars to be able to create the rockets and electric cars that are now industry standards for excellence at cost. While hardware is hard, it could have the greatest potential payoffs by cornering a market and improving processes several times better than near competitors. Let’s think about the iPhone or major tech companies moving toward designing their own chips: Apple, Google, Amazon, Facebook, and Alibaba. These companies have enormous amounts of capital to experiment in hardware and the potential payoff of market domination is theoretically worth that investment and more. Startups, on the other hand, face incredible pressure. Last year drone company Airware burned through $118M in funding before going out of business. It’s hard enough to redesign hardware that has been around for years like cars, chips, or rockets, but adding on a nascent, undeveloped market makes hardware incredibly difficult and risky. It takes a truly special entrepreneur, with VC access to build a brand new hardware startup.

Business Themes

1. Ownership & Control. Elon was famously ousted as CEO of Zip2 and relegated to CTO after a his board of directors insisted his leadership style was too aggressive. Musk met the same fate with X.com/PayPal where he was notified after landing in Hawaii for his honeymoon that several members of the team had delivered letters of no confidence to the board, asking Peter Thiel to be named CEO instead. After PayPal was sold to Ebay, Musk used his $180M post-tax earnings to fund and maintain large ownership percentages of Tesla, SpaceX and Solar City. Ownership and board control are incredibly important issues for founders. When Snap Inc. went public in 2017, co-founders Evan Spiegel and Bobby Murphy owned 48.4% and 47.4% of the voting power in the Company, respectively. While this extreme might present a board governance issue (especially since Snap’s stock is down 78% since IPO), Musk’s travails point out the importance of ownership and control when running a Company.

2. The absolute necessity of fundraising. There are numerous references to times when it seemed all hope was lost and either Tesla or SpaceX would go under. In 2009, Musk loaned money from SpaceX to Tesla to continue payroll through Christmas. In 2012, among mounting criticism of the Tesla roadster and delays in production, Musk struck a handshake deal with Larry Page for Tesla to be acquired by Google for around $6 billion. Fundraising is a difficult part of any entrepreneur’s journey but keeping the lights on and knowing the cash viability of the business are incredibly important for success.

3. Positive cashflow dynamics. Tesla and SpaceX benefit from positive cash flow dynamics: SpaceX signs billion dollar contracts with the government and Tesla users pay $2,500 to sign up to get for the waiting list. In both situations, Musk’s companies get the cash upfront, prior to delivering the product or service. This is particularly important for SpaceX and Tesla because the process of engineering brand new rockets and cars is expensive. By getting the cash upfront, they can quickly invest that money into creating their products and use it to run the day to day operations of the business.

Dig Deeper

• Elon bought a McLaren F1 after selling Zip2

• Elon’s famous tweet about taking Tesla private

• Elon’s challenging relationship with his father

• Elon’s grandparents were thrill seeking pilot adventurers