Contents

• Why does Ethereum matter?

• Understanding Ethereum & Decentralized Finance

• Other applications on top of Ethereum

  • Tokenization

  • Decentralized Autonomous Organizations

  • NFTs

• Connected Business Concepts

  • Related

Why does Ethereum matter?

Ethereum is a cryptocurrency currently ranking at number two in market capitalization after Bitcoin, which is at the top. However, in terms of being used actively, Ethereum is ahead of Bitcoin. While Bitcoin is sent, received, and held only in a singular form, Ethereum allows entities to create different ledgers. These can even be used to create additional cryptocurrencies. The use and transactions using Ethereum have grown consistently over the years ever since it began operations half a decade ago.

Banking can be traced back to 2000BC when merchants began to give loans to farmers and traders. They used to carry goods and the transactions began to be noted down. With each passing century as the interaction between people increased, a more centralized system began to be developed which turned into the banking system that we witness in the world today.

From a small transaction occurring in a remote village through card payment to the mergers of big companies on Wall Street, everything is monitored by the banking system. With every transaction, there are intermediaries between the buyer and the seller.

The control of financial institutions over every transaction that occurs does not sit right with everyone. Banks are seen as an evil force, which controls every aspect of human lives. In order to disrupt the operations of these financial intermediaries and break their control over the money that people have, the concept of Decentralized Finance or DeFi has been introduced. DeFi is inspired by blockchain. Blockchain distributes the copy of transactions occurring over several entities and hence, decentralizes the system so that no single entity can have control over them.

This is important because, in a centralized system, the speed of the transactions is less and people have less direct control over their own money. DeFi is basically an extension using blockchain technologies in going against the centralized systems. With the concept of DeFi, the intermediaries are eliminated between the buyer and seller. All of the financial institutions are cut out using this technology. Loans and insurances, even crowdfunding is controlled by financial institutions and one of the biggest advantages of DeFi is to cut out these intermediaries.

Understanding Ethereum & Decentralized Finance

Decentralized finance (DeFi) refers to an ecosystem of financial products that do not rely on traditional financial intermediaries such as banks and exchanges. Central to the success of decentralized finance is smart contracts, which are deployed on Ethereum (contracts that two parties can deploy without an intermediary). DeFi also gave rise to dApps (decentralized apps), giving developers the ability to build applications on top of the Ethereum blockchain.

Ethereum allows digital transactions in the simplest form but also allows entities to move towards a decentralized system. It protects in terms of being outside the control companies and governments. These institutions are cut out of the picture by the use of Ethereum. Ethereum offers what is known as a “smart contract” by the use of which transactions automatically occur if certain predefined conditions are met.

Smart contracts are protocols designed to facilitate, verify, or enforce digital contracts without the need for a credible third party. These contracts work on an “if/when-then” principle and have some similarities to modern escrow services but without a third party involved in guaranteeing the transaction. Instead, it uses blockchain technology to verify the information and increase trust between the transaction participants.

As a simple example, it can be written in a smart contract that the transaction is to be done on a certain Wednesday if the temperature in San Francisco drops below 30 degrees centigrade according to accuweather.com. Having these smart at the core of the ideology behind Ethereum, numerous applications of DeFi are operating Ethereum.

The biggest application of DeFi is a decentralized exchange (DEX). While online exchanges allow users to exchange currencies either for other currencies or bitcoins, for example, DEXs connect users directly to each other. By this direct connection, all intermediaries are cut out of the picture and the users do not have to worry about trusting anyone with their money.

Another application is known as Stablecoin. The concept behind Stablecoin is basically “tying” the cryptocurrency to an asset that is outside the cryptocurrency. As an example, to stabilize the price it can be tied to the Pound or Dollar. It aims to bring stability to the prices set.

To cut out intermediaries from lending, DeFi is used in the process based on Ethereum. Smart contracts are employed in the process and institutions like banks are removed from acting as intermediaries. Platforms like Compound allow users to borrow cryptocurrencies and provides them with the option of offering their own loans. The platform is responsible for setting the interest rates, which allows users to earn money off the money that they loan out.

An algorithm is used in this process, which changes and adjusts the interest rate based on the demand of the cryptocurrency. The users are not required to give out their identity when giving or borrowing loans, which differentiates them from non-DeFi services. Another application revolves around Prediction Markets.

These are betting platforms like on the outcomes of football matches for example. The concept of DeFi prediction markets is the same as regular prediction markets but they differ on the grounds that while in the typical prediction markets intermediaries exist but in DeFi they are not included and the transactions remain user to user.

The concept of DeFi is attractive to many who seek privacy in their financial transactions. However, there are a lot of risks associated with it as well. For new entrants into the DeFi market, there are a lot of uncertainties. It is not easy to make a distinction between the good and the bad projects. There are bugs within DeFi, which sometimes become permanent, and hence the risk is increased. They become permanent because once the smart contracts are initiated, their rules cannot be changed. So, if the bugs are a part of the contract, they become permanent.

The problems that this system faces are in terms of security as well. Hackers have in the past attacked Ethereum and stole millions in the cryptocurrency. It remains a major concern for investors unsure of the investments they are making. The next step in Ethereum is the launching of Ethereum 2.0. The upgrade will increase the speed of transactions that occur per second. Currently, the transactions are around 15 per second, which will increase to tens of thousands per second.

This will be achieved through a process known as “sharding”. This basically means running many blockchains in parallel and then having them share a common blockchain. This will mean that a potential hacker who wants to tamper with one chain will have to tamper with the common consensus and it will end up costing more than what the hacker could make of it. These developments can increase the reliability of Ethereum as an application of DeFi.

Blockchain companies use sharding to partition databases and increase scalability, allowing them to process more transactions per second. Sharding is a key mechanism underneath the Ethereum Blockchain and one of its critical components. Indeed, sharding enables Blockchain protocols to overcome the Scalability Trilemma (as a Blockchain grows, it stays scalable, secure, and decentralized).

A Proof of Stake (PoS) is a form of consensus algorithm used to achieve agreement across a distributed network. As such it is, together with Proof of Work, among the key consensus algorithms for Blockchain protocols (like the Ethereum’s Casper protocol). Proof of Stake has the advantage of the security, reduced risk of centralization, and energy efficiency.

Other applications on top of Ethereum

Tokenization

An ERC-20 Token stands for “Ethereum Request for Comments,” which is a standard built on top of Ethereum to enable other tokens to be issued. Based on a smart contract that determines its rules, the ERC-20 enables anyone to issue tokens on top of Ethereum. As they are using a standard, those are interoperable. ERC-20 Tokens are critical to understanding the development of Ethereum as a business platform.

Decentralized Autonomous Organizations

A decentralized autonomous organization (DAO) operates autonomously on blockchain protocol under rules governed by smart contracts. DAO is among the most important innovations that Blockchain has brought to the business world, which can create “super entities” or large entities that do not have a central authority but are instead managed in a decentralized manner.

NFTs

Non-fungible tokens (NFTs) are cryptographic tokens that represent something unique. Non-fungible assets are those that are not mutually interchangeable. Non-fungible tokens contain identifying information that makes them unique. Unlike Bitcoin – which has a supply of 21 million identical coins – they cannot be exchanged like for like.

Read Next: Blockchain Business Models Framework Decentralized Finance, Blockchain Economics, Bitcoin.

Read Also: Proof-of-stake, Proof-of-work, Blockchain, ERC-20, DAO, NFT.

Connected Business Concepts

A free-to-play is a model that became particularly popular in gaming. Free-to-play is also commonly referred to as free-to-start. For instance, companies like Epic Games have launched popular games like Fortnite’s Battle Royale, which had ingrained a free-to-play model. This is a model that become extremely popular in the digital age of gaming.

According to Joel Monegro, a former analyst at USV (a venture capital firm) the blockchain implies value creation in its protocols. Where the web has allowed the value to be captured at the applications layer (take Facebook, Twitter, Google, and many others). In a Blockchain Economy, this value might be captured by the protocols at the base of the blockchain (for instance Bitcoin and Ethereum). However, according to blockchain investor Paivinen due to ease of forking, incentives to compete and improved interoperability and interchangeability also in a blockchain-based economy, protocols might get thinner. Although the marginal value of scale might be lower compared to a web-based economy, where massive scale created an economic advantage. The success of the Blockchain will depend on its commercial viability!

A Proof of Stake (PoS) is a form of consensus algorithm used to achieve agreement across a distributed network. As such it is, together with Proof of Work, among the key consensus algorithms for Blockchain protocols (like the Ethereum’s Casper protocol). Proof of Stake has the advantage of security, reduced risk of centralization, and energy efficiency.

A Proof of Work is a form of consensus algorithm used to achieve agreement across a distributed network. In a Proof of Work, miners compete to complete transactions on the network, by commuting hard mathematical problems (i.e. hashes functions) and as a result they get rewarded in coins.

A Blockchain Business Model according to the FourWeekMBA framework is made of four main components: Value Model (Core Philosophy, Core Values and Value Propositions for the key stakeholders), Blockchain Model (Protocol Rules, Network Shape and Applications Layer/Ecosystem), Distribution Model (the key channels amplifying the protocol and its communities), and the Economic Model (the dynamics/incentives through which protocol players make money). Those elements coming together can serve as the basis to build and analyze a solid Blockchain Business Model.

Ethereum was launched in 2015 with its cryptocurrency, Ether, as an open-source, blockchain-based, decentralized platform software. Smart contracts are enabled, and Distributed Applications (dApps) get built without downtime or third-party disturbance. It also helps developers build and publish applications as it is also a programming language running on a blockchain.

The Graph is an ERC20 Utility Token (built on top of Ethereum) to enable consumers to freely query the blockchain through a fully decentralized database kept by indexers, incentivized by the payment of tokens (called GRT). The network is also ministered by curators and delegators that help maintain a high-quality index.

BAT or Basic Attention Token is a utility token aiming to provide privacy-based web tools for advertisers and users to monetize attention on the web in a decentralized way via Blockchain-based technologies. Therefore, the BAT ecosystem moves around a browser (Brave), a privacy-based search engine (Brave Search), and a utility token (BAT). Users can opt-in to advertising, thus making money based on their attention to ads as they browse the web.

In 2012, co-founders Christian Larsen and Jed McCaleb created Ripple, a technology acting as both a pre-mined cryptocurrency called XRP and a digital payment platform enabling monetary transactions. Where Ripple is the tech company, XRP is the decentralized ledger.

In 2014, Jed McCaleb – which also played a key role in the development of Ripple – created a cryptocurrency to provide fast, reliable, and affordable money transactions. The same cryptocurrency has considerably grown seven years later. It is now one of the most stellar cryptocurrencies to provide a real-time platform that links banks, payment systems, and people. Meet, Stellar!

In early 2019, a joint project between TRON and BitTorrent Foundation called BitTorrent Token came to fruition. BitTorrent Token launched to tokenize in-demand file-sharing protocol and enhance content delivery and bandwidth accessibility with blockchain technology.

Chainlink is considered the most established decentralized oracle network. As an ecosystem housing several decentralized oracle networks running simultaneously. As a decentralized oracle service built on Ethereum, Chainlink has the power to support the development of blockchain solutions for both traditional businesses and enterprises.

Uniswap is a renowned decentralized crypto exchange created in 2018 and based on the Ethereum blockchain, to provide liquidity to the system. As a cryptocurrency exchange technology that operates on a decentralized basis. The Uniswap protocol inherited its namesake from the business that created it — Uniswap. Through smart contracts, the Uniswap protocol automates transactions between cryptocurrency tokens on the Ethereum blockchain.

In essence, Polkadot is a cryptocurrency project created as an effort to transform and power a decentralized internet, Web 3.0, in the future. Polkadot is a decentralized platform, which makes it interoperable with other blockchains.

Designed and created as an alternative to Ethereum, Cardano claims to be the first decentralized blockchain protocol to use a scientific approach and undergo a peer evaluation.

Solana is a blockchain network with a focus on high performance and rapid transactions. To boost speed, it employs a one-of-a-kind approach to transaction sequencing. Users can use SOL, the network’s native cryptocurrency, to cover transaction costs and engage with smart contracts.

Contents

• A glance at the Business Engineering world

• A discipline between business administration and technology

• What tasks a business engineer performs?

• What kind of background, education, and experience do you need to become a business engineer?

• How much does a business engineer make?

• Business Engineering as a foundational discipline of the FourWeekMBA Curriculum

  • Financial Modeling

  • Business Analysis

  • Business Modeling

  • Technological Modeling

  • Revenue Modeling

  • Intution, guts, wandering and customer obsession

  • Related

A glance at the Business Engineering world

At its core, a business engineer is a hybrid between a business person and an engineer. The business engineer is someone with the understanding of how the business world works ad macro level, combined with how organisms function at a micro level, that can architecture solutions based on several key elements.

As pointed out in Osterle, H. (1995), Business in the Information Age:

The business engineering concept enables the transformation of enterprises from the industrial age into the information age by means of procedure models, methods, and tools

Some of the key elements comprising business engineering require a deep understanding of several disciplines and areas:

• Business model

• Business processes

• Organizational structure

• Digitalization

• Information process and technologies

• The interaction between people and technologies within organizations

In one of its vacancies for Business Intelligence Engineer Amazon defines it as someone that can help “improve and define the best way of doing things throughout the company using the power of your analysis, technical skills, and business acumen.”

While this particular role is focused on improving internal processes to “identify opportunities to improve and optimize ship costs.”

As pointed out by Amazon “the successful candidate will be able to retrieve, integrate, visualize and present critical data in a format that is immediately useful to improve the business decision-making process.”

A discipline between business administration and technology

Business engineering is a discipline in between business administration and technology. As more and more organizations are innovated by combining technological product and processes with remixing old and new business model patterns, it becomes critical to understand and drive those processes.

A business engineer is a manager that can guide companies through hard decisions by looking at quantitative data, navigating ambiguity and reducing the noise where needed. Some of the disciplines part of business engineering are:

• Management science

• Business administration

• Law and economics

• Technology and engineering

A business engineer is a hybrid between a commercial and technical role. It can work as a liaison between commercial and technical teams to device complex solutions to its organizations or other companies for which the business engineer partners with.

What tasks a business engineer performs?

Some of the job descriptions from Indeed and LinkedIn say:

Developing sales and service with regional and global accounts, supporting Account Managers and business development. Driving sales-related activities, implementing customer projects such as product and prototype selections, costing, pricing, quotations, preparation for serial production, and logistics setups.

For instance, among the task required:

• Interacting with customers and consulting with Account Managers providing technical and commercial support

• Applying financial analysis to evaluate business opportunities

• Coordinating and driving customer-related and internal projects and activities

• Supporting and training the organization in technical, commercial and market-oriented tasks

• Handling claims with internal partners and managing quality control

On a position for Business Intelligence Engineer Amazon points out:

• Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc. that will support business needs

• Partner with operations/business teams to consult, develop and implement KPI’s, automated reporting/process solutions and data infrastructure improvements to meet business needs

• Apply deep analytic and business intelligence skill to extract meaningful insight and learning from large and complicated data sets

• Serve as liaison between the Business and technical teams to achieve the goal of providing actionable insights into current business performance, and ad hoc investigations into future improvements or innovations. This will require data gathering and manipulation, synthesis and modeling, problem-solving, and communication of insights and recommendations

What kind of background, education, and experience do you need to become a business engineer?

For some of the open vacancies for Business Engineer, the required background is:

• Bachelor’s degree in Mechanical or Chemical Engineering or comparable technical field.

• Preferably up to 3 years’ experience in technical sales and knowledge of heat transfer and thermodynamics

• Advanced Microsoft Office with an understanding of calculation tools.

• Experience of CRM/ERP systems is an advantage

Skills:

• Enjoy working in an international environment

• Proactive, positive, and target-oriented team player with a keen interest in technical and commercial matters

• Very strongly customer-oriented

• Strong networker with good interpersonal skills and the ability to cooperate and communicate with many different layers and cultures

Those, of course, are just some of the skills required. Those will widely vary from organization to organization.

How much does a business engineer make?

According to PayScale, the average yearly pay for a Business Engineer is $67,429. The total pay goes from $35,479 – $83,845 based on salary and bonus.

By running a search on Glassdoor for Business Engineer, the average salary can go from $64k per year for smaller organizations to senior Business Intelligence Engineer at eBay and Facebook, for $117k and $140k of yearly base salary respectively.

A new discipline?

Business Engineering as a foundational discipline of the FourWeekMBA Curriculum

I argue that the next step to the evolution of business innovation is that of Business Engineering, usually intended as a person using technology to build technical processes within the organization.

However, in the FourWeekMBA view, the Business Engineer is a hybrid between an entrepreneur, a customer-centered business designer, and a business analyst, able to prevent false patterns, thus growing the business with a mixture of intuition, business acumen, testing, and experimentation.

While for many, business engineering is something more technical connected to attaching technology to business processes.

To me, that is more conceptual, and it stands for an understanding of the business world that comes from various disciplines.

In fact, the business engineer borrows experimentation from business modeling:

Where scientists use labs to test their hypotheses through experimentation. Entrepreneurs build business model experiments to test their business ideas in the real world.

It borrows a customer-centered approach from design thinking:

Tim Brown, Executive Chair of IDEO, defined design thinking as “a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.” Therefore, desirability, feasibility, and viability are balanced to solve critical problems.

At the same time, it brings it to the next level with customer obsession:

Customer obsession goes beyond quantitative and qualitative data about customers, and it moves around customers’ feedback to gather valuable insights. Those insights start with the entrepreneur’s wandering process, driven by hunch, gut, intuition, curiosity, and a builder mindset. The product discovery moves around a building, reworking, experimenting, and iterating loop.

And all of that, while understanding the distribution model:

A distribution channel is the set of steps it takes for a product to get in the hands of the key customer or consumer. Distribution channels can be direct or indirect. Distribution can also be physical or digital, depending on the kind of business and industry.

And financial model:

Financial modeling involves the analysis of accounting, finance, and business data to predict future financial performance. Financial modeling is often used in valuation, which consists of estimating the value in dollar terms of a company based on several parameters. Some of the most common financial models comprise discounted cash flows, the M&A model, and the CCA model.

But most of all, the business engineer understands the difference between linear and non-linear thinking and knows when to apply one or the other:

Lateral thinking is a business strategy that involves approaching a problem from a different direction. The strategy attempts to remove traditionally formulaic and routine approaches to problem-solving by advocating creative thinking, therefore finding unconventional ways to solve a known problem. This sort of non-linear approach to problem-solving, can at times, create a big impact.

Indeed, the business engineer knows that in a context of continuous, linear improvement, linear thinking might work:

That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problems and not the technical solution of its founders.

But also how to drive breakthrough innovation:

The innovation loop is a methodology/framework derived from the Bell Labs, which produced innovation at scale throughout the 20th century. They learned how to leverage a hybrid innovation management model based on science, invention, engineering, and manufacturing at scale. By leveraging individual genius, creativity, and small/large groups.

In what I like to call technological modeling or barbelling:

Technological modeling is a discipline to provides the basis for companies to sustain innovation, thus developing incremental products. While also looking at breakthrough innovative products that can pave the way for long-term success. In a sort of Barbell Strategy, technological modeling suggests having a two-sided approach, on the one hand, to keep sustaining continuous innovation as a core part of the business model. On the other hand, it places bets on future developments that have the potential to break through and take a leap forward.

So that business innovation isn’t driven anymore in siloed departments, but the walls between product and marketing/distribution are wrecked, to create bottom-up growth.

Jeff Bezos explains the difference between e-commerce and a platform

Back in 2019, in Amazon’s shareholders’ letters, one of the last ones from Jeff Bezos, as CEO of Amazon, he highlighted:

The percentages represent the share of physical gross merchandise sales sold on Amazon by independent third-party sellers – mostly small- and medium-sized businesses – as opposed to Amazon retail’s own first-party sales.

Third-party sales have grown from 3% of the total to 58%.

To put it bluntly: Third-party sellers are kicking our first-party butt. Badly.

The statement above, explains the key difference between e-commerce and a platform!

E-commerce measures its success based on how many of its products it sells directly on its own stores.

A platform, by converse, measures the success of other stores, on top of the existing e-commerce infrastructure!

Imagine in the physical world, a retail shop, selling products (of his own) and a commercial shopping area, where there are shops of many kinds, selling their products.

In the former case, the retail shop will be concerned primarily about its revenues, and product sales. In the latter, the commercial center needs to make sure within it has a set of thriving shops, which attract as many people as possible. Only with that setup, it will be successful over time.

As Jeff Bezos further highlighted, back then:

And it’s a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%.

But in that same time, third-party sales have grown from $0.1 billion to $160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion.

He also analyzes the context, to understand what made up Amazon’s success in attracting third-party stores, and he posed a few questions:

Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization?

Jeff Bezos emphasized:

There isn’t one answer, but we do know one extremely important part of the answer:

We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year.

In short, a successful platform incentivizes third-party stores and e-commerce to compete against the first-party stores, and it offers them a set of key tools to manage inventory, payments, track shipments, and reporting.

As Jeff Bezos further highlighted:

But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers. With the success of these two programs now so well established, it’s difficult for most people to fully appreciate today just how radical those two offerings were at the time we launched them.

The combination of fulfilled by Amazon and prime membership, improved the customer experience, of buying from independent sellers, thus making it as good as buying from Amazon itself.

As Jeff Bezos, highlighted, those two programs (now widely successful) were not guaranteed to succeed:

We invested in both of these programs at significant financial risk and after much internal debate. We had to continue investing significantly over time as we experimented with different ideas and iterations.

In fact, while those make sense now, and seem obvious, in hindsight, it took a lot of mistakes, failures, and iterations, to get there:

We could not foresee with certainty what those programs would eventually look like, let alone whether they would succeed, but they were pushed forward with intuition and heart, and nourished with optimism.

This is the core of what customer obsession stands for:

Customer obsession goes beyond quantitative and qualitative data about customers, and it moves around customers’ feedback to gather valuable insights. Those insights start with the entrepreneur’s wandering process, driven by hunch, gut, intuition, curiosity, and a builder mindset. The product discovery moves around a building, reworking, experimenting, and iterating loop.

And what building a flywheel means:

The Amazon Flywheel or Amazon Virtuous Cycle is a strategy that leverages customer experience to drive traffic to the platform and third-party sellers. That improves the selections of goods, and Amazon further improves its cost structure so it can decrease prices which spins the flywheel.

Read Next: Amazon Business Model.

Currently, the predominant business model for commercial search engines is advertising. The goals of the advertising business model do not always correspond to providing quality search to users.

This is how, in 1998, in a paper entitled “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” Brin and Page, two Ph.D. students, at Stanford University, expressed their frustration, with the current landscape of search.

Just a couple of years before, in 1996, the two students, working on an algorithm – called “BackRub” – leveraging backlinks  (web links that looked like citations, where the site linked through a backlink gained authority over others, similarly to the citation mechanism in academia) managed to tame the exponentially growing web of pages.

By 1998, that project had now become a company, called Google.

Before we get to the story of what would later become Google, let’s dive a bit into the context of these years, and how the web (or the commercial Internet) looked like.

And how the various waves of the Internet were shaped by these companies.

The first internet wave and the first walled gardens

In the first wave of the commercial Internet (1994-1999) the first big tech players and tech giants were walled gardens. Those platforms enabled access to proprietary networks (this wasn’t really the Internet, as those were not open protocols). Instead, they were places where users could enjoy a set of controlled and closed online services (emails, news, forums, and later on search).

These first tech giants were companies like AOL, Prodigy, CompuServe, and GEnie. Their business model was straightforward, you would pay for a monthly subscription, and enjoy a few hours of access to their proprietary networks. For each additional hour, users spend on top of the subscription, they would be charged based on consumption.

The first Internet giant: AOL

AOL is a web portal and online service provider founded in 1983, by Marc Seriff, Steve Case, Jim Kimsey, and William von Meister.

AOL was one of the largest media companies of the early Internet, dominating email, internet connectivity, online news, and chat.

At its peak, in 1999, AOL had a market capitalization exceeding $200 billion. As we’ll see this milestone happened as AOL acquired Netscape, in its attempt to fully convert to the new rising wave, of Web 1.0 made of browsing first, then searching the commercial Internet.

Before closing this circle, let me give you some more context about these years.

AOL had mastered the art of attracting and then monetizing dial-up subscribers. By the mid-90s subscription business models, leveraging proprietary networks had started a fierce competition between each other.

Thus, eventually forcing, also AOL to adopt an unlimited subscription plan. Indeed, in October 1996, at the peak of its popularity, AOL announced a $19.95 flat-rate pricing plan for unlimited access to both the Internet and AOL’s private network.

As the legendary Steve Case announced at the time:

You’re seeing a much more aggressive America Online. AOL in one fell swoop is trying to meet the needs of the mainstream and also address the concerns of Wall Street. We really repriced the service to reach out to the heavy users who really want and need unlimited pricing [and] the light users who want the comfort of a relatively low monthly fee.

Yet AOL’s infrastructure was unprepared for the boom in popularity of broadband internet, and it barely handled that traffic, to the point that the platform started to crash more and more often.

By 1998, AOL was experiencing a set of outages, that made the service more and more unreliable.

This also triggered a set of class actions against the company, as users got angrier.

This showed that the Internet was becoming a critical utility to those users who subscribed to AOL and that AOL itself had become an important part of those users’ lives.

Yet, the company had to start to spike its subscriptions plans, as the infrastructure was collapsing under the weight of additional traffic.

As the company peaked in 1998, Steve Case announced: “we’re not going to get complacent, but we’ve created a service that’s fun and easy to use. Those factors and the general shift in spending to new media positions AOL as the best brand in the industry.”

By the year 2000, AOL had generated over $6.8 billion, comprising subscription services ($4.4 billion), advertising/commerce (almost $2 billion), and $500 million from enterprise solutions.

By June 2000, AOL counted 23.2 million members!

Take into account, that in the US, in the year 2000, there were over 120 million Internet users, thus still making AOL the primary avenue to the Internet.

In the same year, AOL sealed the largest merger in United States history – after the Vodafone-Mannesmann merger which reshaped the whole mobile telecom industry – which would play a key role in shaping the Internet, as we know it.

At the time, AOL acquired Time Warner for $111 billion in 2000. The result was a $360 billion multimedia conglomerate comprised of Time Warner’s vast media empire and AOL’s 30 million dial-up Internet subscribers.

As CNN Money highlighted back then, the deal was so big that it worried also Microsoft, which, as the merger was going through, started to engage with the Federal Trade Commission, to restrict the deal, and block it, because it claimed it would restrict competition on the Internet.

It’s critical – as we’ll see – to understand that AOL had been helping regulators in the preparation of the Microsoft antitrust case in the early 2000s, thus Microsoft was looking for revenge.

Yet, the deal went through, but it set a condition:

AOL Time Warner must offer its subscribers the option to sign up to at least one nonaffiliated cable, high-speed Internet service provider via Time Warner’s cable system before AOL itself begins offering such service.

In short, while AOL could merge with Time Warner, it still had to guarantee open access to the Internet, to prevent it to become only a proprietary network, controlled by the newly formed giant.

Unfortunately, the merger occurred just three months before the dot-com bubble burst and the economy fell into a recession.

The relationship between Time Warner and AOL was often acrimonious. This hindered AOL’s ability to make serious inroads into broadband, which was then largely controlled by cable companies. In the years following the merger, the dot-com recession and a lack of broadband integration lead to a serious decline in AOL subscribers.

AOL and Time Warner were two fundamentally different companies. AOL was primarily an online player, where Time Warner had tried but failed to enter the space.

The envisioned synergies between the two giants not only did not materialize. But these two companies never really managed to get along and create a unified culture. This also was a critical lesson in business history.

It doesn’t matter how much firepower you have, sometimes, in order to dominate a new industry, you need to completely change the business playbook. And AOL was soon to learn this lesson, which would cost it its leadership, while new startups, like Google, would take over.

In 2003, AOL Time Warner posted an almost $100 billion loss – at the time the largest in U.S. corporate history. The dot-com bubble had crashed the valuation of the newly formed company.

In the meantime, by 2003, Google had turned into a web giant. When it showed its financials, the whole tech industry was taken aback by its incredible success. Not only was Google profitable, but it was a rocket ship, generating almost a billion in revenue in 2003, with a net profit of over $106 million.

*

Before we get into the incredible rise of Google, we need to take another step back.

Indeed, you can hardly understand search if you don’t have a grasp of the “browser wars” of the 1990s!

The fall of proprietary networks, the browser wars, and the rise of Web 1.0

As AOL took over the Internet in the first wave of the mid-90s, it also opened up its platform to more and more people, by changing its revenue model. From the subscription and consumption model, AOL had to adapt to the unlimited subscription model where users could enjoy unlimited access to AOL’s proprietary network.

Founded in 1983, as we saw, AOL became the first web Internet giant, using a “walled-garden business strategy.” By early 2000, this strategy had become obsolete, since players like Google wrecked these walls off!

On paper, the merger of AOL and Time Warner formed a large and powerful company with the right mix of assets but AOL had already lost most of its value by the early 2000s.

With this new model, the AOL users base grew even further. But it also showed some of its weaknesses, as the platform became unstable, with a wide number of new members.

In this time period, the Internet also grew exponentially, favoring the birth of a few tech players. In this period, something very counterintuitive happened. Search, which seemed a feature to offer on top of the proprietary networks, became a killer commercial application!

How did search become a commercial killer application? The browser market had laid the foundation for the search market to thrive.

When Microsoft spent billions to bring TV online – the complete failure of the Information Superhighway

Grasping how new industries will evolve is one of the most difficult aspects of high-tech business. And even the smartest people that dominated an industry, can hardly imagine what the future will look like.

This is the reality of the business world. Indeed, back in the mid-90s, when the commercial Internet was finally taking over, most luminaries, gurus, and tech experts projected it as a sort of Information Superhigly (similarly to how today we talk about the Metaverse, and how Mark Zuckerberg’s vision for it might turn to be completely off).

As you can see, the vision at the time, was about an “interactive entertainment center.”

While, by 1995, Microsoft had tried to rewrite business history, as if Bill Gates and his company had grasped in full the Internet phenomenon. In reality, things looked quite different!

As explained by Jim Clark (co-founder of Netscape) in his book *“Netscape Time: The Making of the Billion-Dollar Start-Up That Took on Microsoft,“* in 1994, Netscape was launching the browser which would conquer the whole browser market share, thus, becoming, for a short period of time, the Internet!

In the same year, Microsoft was still trying to figure things out. Microsoft, a native player of the PC era, had risen during the 1970s when Intel had created a whole new industry. Thanks to Intel’s family of chips, with the development of the 8080 – led by Federico Faggin – going forward the computer industry was born.

As we saw, the turning point for Microsoft came when, IBM, in1980, was about to launch its IBM Personal Computer. The IBM Personal Computer, contrary to what IBM had done in its whole history, followed an open architecture.

In 1980, Microsoft partnered up with IBM to bundle Microsoft’s operating system with IBM computers. The deal was straightforward, IBM would pay Microsoft $430,000 for what would be called MS-DOS.

Microsoft on the other hand could license that same operating system to other PC makers, beyond IBM. The microcomputer space, which in the late 1970s was dominated by Tandy, Commodore, and Apple, was taken by surprise as the IBM Personal Computer became a huge success.

Yet, by the early 1990s, IBM lost its leadership and didn’t manage to capture the value of the PC market.

On the other hand, Microsoft became the de facto operating system of the PC industry and within a decade the company became a tech giant. In 1982, Microsoft recorded over $24 million in revenues, in 1985 over $140 million, and by 1990 Microsoft had passed a billion dollars in revenue, the first tech company to do so, and becoming the de facto operating system of the PC market.

Where IBM had created the PC standard in the early 1980s, Microsoft surfed it for decades!

Where IBM had lost its leadership, the PC had become a standard that would last for decades, spurring a market that gave rise to new players, competing on price. The hardware had been commoditized, where software, in the form of the operating system first, then applications would be monetized at a premium.

Microsoft followed a platform strategy, were on top of the operating system, it added applications (the first launch of Microsoft Office 1.0 happened in November 1990 and it comprised three applications: Word, Excel, and PowerPoint). Over the years Microsoft bundled everything up, creating de facto the dominant operating system and PC applications provider in the world.

Its distribution power got so strong, that by the year 2000, Microsoft had a 96% market share of all PCs! Microsoft had mastered this platform strategy, which would soon be used by the new Internet players.

IBM’s mistake would become one of the most studied in the history of high-tech business. As David Bradley, one of the teams of 12 who produced the PC at IBM highlighted:

At the time, we didn’t think it was going to be a revolutionary change, we knew we were working on an exciting project and we certainly hoped it was going to be successful, but we never imagined it was going to take over the world the way it did.

In short, IBM had grasped the importance of the project, but it missed how revolutionary it would be. And that is fine because, in foresight, it’s hard to determine which projects will become new industries.

However, IBM, which at the time, was still a big corporation (they called it “Big Blue“) had first approached a young Bill Gates, in July of 1980 (he was 24 at the time), to develop an operating system, to what became the IBM Personal Computer.

Why did they do it? First, IBM was in a rush. In fact, back then, typical product cycles lasted four years. Instead, IBM wanted to bring the PC to market, as quickly as possible. In addition, IBM was playing a different game. For IBM at the time, it wasn’t about the software, it was about the hardware. Indeed, back then, the software industry didn’t exist as the software was treated as a commodity to be given for free on top of the hardware.

It would be Microsoft that successfully commercialized software. This mindset and philosophy would stick in Microsoft’s culture for decades (the matra for Microsoft under Bill Gates was “we are a software company”), so much so, that when Microsoft tried to manufacture an alternative to the iPhone (its Windows Phone) in the 2010s, it failed miserably.

While on the one hand, IBM had a team of 12 technical people working on the project and a legal and procurement team. Bill Gates and Paul Allen were mostly doing things on their own.

As Bill Gates highlighted, remembering those days, “we had to be very clever, we actually did not get a royalty from IBM but we kept the rights so we were getting royalties from other people.”

By 1993, IBM shocked the business world by reporting quarterly losses of $8bn, primarily caused by increased competition and a changing market. IBM had created a whole new industry, and yet it had failed miserably in dominating, and profiting from it. Microsoft, on the other hand, had become the scariest tech giant of the 1990s.

Also, other players like Apple, which had dominated the computer industry in the late 1970s (though computers were still for niches), refused to license its operating system to others, thus making Microsoft the uncontested PC standard for decades!

Anyone, trying to enter the software space, was a threat to Microsoft, and therefore, was to be killed as quickly as possible, as any potential new sub-industry that would be created in software, which Bill Gates could not control, needed to be suppressed, or taken over by Microsoft.

And in 1994-95, the Internet was the industry that Microsoft needed to dominate if it wanted to keep its dominance, in the long run!

The interesting part was, that some of these Internet competitors, would use Microsoft’s platform strategy, to take over this new market.

#The commercial killer application of the early Internet: Browsing

Accessing the web in the early 1990s wasn’t an easy fit. If it wasn’t for proprietary networks, like AOL, accessing the Internet in the first place was very very hard.

Mosaic, the first web browser, changed that! For the first time, with a very simple and straightforward setup, users could access the Internet. The browser had been developed by a smart group of very young developers, at NCSA. NCSA or the National Center for Supercomputing Applications was a research project unit, set up at the University of Illinois Urbana-Champaign.

As the story goes, in 1992, Joseph Hardin and Dave Thompson, who worked at the NCSA, learned about Tim Berners-Lee’s work at CERN. In the fall of 1990, Tim Berners-Lee had developed the first browser on a NeXT machine (the company Steve Jobs had created after being ousted from Apple), together with an editor to create hypertext documents.

Text-based browsers started to spring up and by 1992, Joseph Hardin and Dave Thompson downloaded the ViolaWWW browser, which had some extended functionalities compared to the first browsers.

Two students at the University of Illinois Urbana-Champaign, Marc Andreessen and Eric Bina started to work on a new browser, for X-Windows on Unix computers, releasing the first version in 1993. This browser was called Mosaic, and it was the first browser to allow images embedded in the text, thus making for the first time, the Internet, way more interactive.

Yet, by August 1994, rather than enabling the development team to take over the project and commercialize it (as Stanford had been doing for decades) NCSA took over the Mosaic project, and it assigned its commercial rights to Spyglass, a corporation that was formed to profit from the Mosaic browser (in 1995 to kick off the launch of Internet Explorer and to kill Netscape dominance, Microsoft licensed Spyglass’ Mosaic technology).

In this context, in early 1994, Jim Clark, an entrepreneur, who had left his previous company,  called Silicon Graphics, was looking to create his next big thing, and he was also looking for revenge, as he, the founder of Silicon Graphics had become a marginal player within the company, and barely managed to make a tiny fortune, compared to the multi-billion dollar success he had built.

Jim Clark also looked at the Internet as the potential new business frontier. Yet, he, like Bill Gates, initially thought about bringing TV online. Little did he know, that shortly, he would have met Marc Andreessen, the young kid behind the development of Mosaic.

At the same time, Microsoft and its founder, Bill Gates, understood the importance of the internet. Back in January 1996, Bill Gates wrote one of the most quoted pieces, still nowadays “Content is King:”

One of the exciting things about the Internet is that anyone with a PC and a modem can publish whatever content they can create. In a sense, the Internet is the multimedia equivalent of the photocopier. It allows material to be duplicated at low cost, no matter the size of the audience.

Yet, still in 1996, Bill Gates had created a dedicated team with the sole purpose of bringing TV to the internet. However, that didn’t work.

The main problem of Gates’ vision at the time was the fact that Microsoft had tried to linearly apply TV to the Internet, as if, the two technologies would follow the same pattern of development.

Over the years, streaming took over the Internet (see Netflix), but in reality, it evolved in completely different ways, and formats (see Netflix binge-watching).

Yet, while Microsoft realized the potential of the Internet early on, it had executed badly on it. And by 1996, it was clear, that “browsing” was the killer commercial application of the Internet and it had a new king.

Time Magazine Archive

A featured in Time Magazine in February 1996, a shoeless Marc Andreessen (at the time 24) was featured as the new king of the Internet, an image that Bill Gates didn’t like at all.

The Browser wars

A young Marc Andreessen, co-founder of Netscape, together with Jim Clark, after months of tinkering, had come to the conclusion that the next big thing would be a “Mosaic killer.”

As the story went, back in 1994, as Clark had left Silicon Graphics, he had met, through a common friend, Marc Andreessen, which Clark recognized right on, as a person worth betting on.

Initially, the two brainstormed ideas about potential ventures to start. But suddenly things became clear. They could develop a Mosaic killer. In fact, the initial developers’ team (of which Andreessen was part) was now working on other projects (Andreessen had moved to California) as NCSA took credit for the development of Mosaic.

Andreessen, together with Clark, convinced the team of developers that had worked on Mosaic, to develop from scratch, a Mosaic killer. This would later become Netscape. The most successful Internet browser.

Netscape was a further improvement on Mosaic’s capabilities. For one thing, Marc Andreessen was a software guy by inclination, and he knew that on the Internet, fast development cycles were the rule. Things didn’t need to be perfect, as new software releases could fix bugs or things that didn’t work, while quickly gathering users’ feedback, and making the product way better, not in the matters of months, but weeks.

This was the new paradigm of the software industry, as the Internet playbook took over. While the first version of Netscape was slightly better than Mosaic, in its later releases, it improved many times over.

By 1997, the browser industry had become a pro game, where Netscape and Microsoft had brought large development teams together. In January 1997, NCSA stopped developing Mosaic.

On the other hand, in 1995 Netscape IPOed, creating the first multi-billion dollar Internet startup. After only sixteen months since the company’s inception. Netscape showed a skyrocketing revenue path, even though its losses kept mounting, and things didn’t look better, as Microsoft went all in!

Clark’s reasoning was that once Netscape had become the market leader, they could go on and monetize that leadership, in the long run, through enterprise deals, similarly to how Microsoft had done, thus creating a strong distribution advantage, that would last.

While Clark’s strategy proved to be correct, as Netscape ramped up its enterprise deals, it also showed Microsoft that they needed to act fast!

And by 1995, Microsoft finally launched its browser: Internet Explorer.

To be quick, and copy what had already worked for Netscape (a standard playbook of Bill Gates, which resembles a lot of the playbook of Mark Zuckerberg in the last decade), Microsoft had licensed the code of Internet Explorer from NCSA.

In short, the codebase Microsoft used to kick off its browser, Internet Explorer, was that of Mosaic, the same browser, that a few years before, Andressen and the core development team, had built at NCSA!

One of the famous quotes from Marc Andreessen was to “reduce Windows to a set of poorly debugged device drivers.”

That Netscape’s threat further created a sense of urgency for Microsoft’s top leadership, who started to invest massively in its browser. By 1995, Netscape had the most successful browser on the market and had developed it by bringing together the original team of Mosaic. Netscape truly became a Mosaic killer. From over 90% browser market shares of Mosaic, in 1994, by 1995-6 the situation had turned upside down.

Netscape had reached 80% of the market share, where Mosaic adoption had stalled (Netscape took a growing pie of the exponentially growing Internet users’ base). Netscape did that through fast releases and built-in network effects.

By 1996-98, Internet Explorer, thanks to the incredible distribution strength of Microsoft, was stealing market shares from Netscape, thus stealing its market leader position.

Indeed, Microsoft was simply bundling its Internet Explorer within its Office Package, thus making it the default choice for users to browse the Internet. Nothing new to Microsoft, which had used the “bundling strategy” for years now.

Yet things looked different in the late 1990s. Microsoft was now the undisputed dominant player in the PC industry, and it was trying to stiffen the competition through distribution in the newly formed Internet industry.

The Microsoft bundling strategy, would, later on, cost the company a famous antitrust case, in which, Bill Gates would be called, in 1998, for hours of deposition, that drained Gates, and might have determined his decision to step down as company’s CEO in 2000.

To be sure, we don’t know what really happened backstage in that antitrust case. And my assumption is that Gates was implicitly threatened to leave the reins of Microsoft if he wanted to avoid the whole company’s breakdown (this is pure speculation on my side).

This was the business context, in the late 1990s, when Google entered the picture.

If browsers wrecked down the walls of the proprietary networks, search engines completely shattered them

As the number of sites on the Internet grew exponentially (by the year 2000 more than 360 million users had joined it), this opened up the need for a tool that enabled one to surf the web to find the most relevant web pages. In parallel to the development of proprietary networks, like AOL, other tools had turned out to be congenial to the Internet.

The first was the browser, with a player like Mosaic, which is a short time span, became very popular.

Yet, as we saw, by 1994, a group of young people that had also worked at Mosaic (among which venture capitalist Marc Andreessen, founder of a16z), also built a browser called Netscape, which by 1995 became the market leader.

Netscape drew the attention of Microsoft’s Bill Gates, which understood how browsers could become the gatekeepers of the Internet. This spurred a war between Microsoft and Netscape, which culminated in Microsoft’s release of Internet Explorer, bundled in its Microsoft Office products.

Thus, Microsoft leveraged its position in the market, to quickly gain market shares, against Netscape. This drew the attention of the regulators who called Microsoft for abusing its dominating position. This led to the parallel development of another commercial killer application: search.

As the Browser wars went on, search became the most important application of the Internet, enabling users to surface the growing numbers of pages on the Web, which was growing at an untamable pace.

Search, therefore, was essential. However, the first search engines, while useful, they were still too much focused on paid placements, and also much easier to game, by webmasters who could easily have their pages show up as relevant, even if not. This paved the way for new players. One epitome of that was GoTo.com, created by the legendary Bill Gross. GoTo.com not only mixed paid results as if they were organic results.

It enabled everyone to bid and compete on its advertising platform. Thus, making the paid search a primary feature. While this model, called CPC was revolutionary, it was also skewed substantially toward paid vs organic results. In that period, toward the end of the 1990s, another player had developed a search engine able to index, and rank the growing mole of web pages.

This was first called Backrub, out of a P.h.d. project at Stanford. And later it was called Google! Google picked up quickly, becoming de facto the most popular search engine at the time. Its ability stood in enabling websites to rank organically without having to pay.

This opened up an industry of practitioners, called SEO (search engine optimization experts) which tried to understand the growing intricacies of search, to make their content distributed across the web. In fact, ranking a site organically had become way more intricate, through PageRank, than it was before, and SEO over the years would turn into a multi-billion dollar industry.

Initially, Google’s founders were quite skeptical of the advertising model for search engines, as they thought this would be intrinsically biased toward paid ads, thus not giving relevant results. Yet, over time they set to change that. They, therefore, started to build an advertising machine, able to also rank paid results based on various factors. Thus, Google borrowed from the GoTo.com CPC model and improved on it. This formula turned out to be extremely powerful.

Google’s deal that made it the tech giant we know today

While Google’s user base was scaling quickly in its early years. Its advertising machine pieces were assembled later on (between 2001-and 2004). Thus, in the early years, Google had to rely on business development deals to further scale up, strengthen its position, and become the market leader.

In the early days, Google’s destiny was all but determined. Indeed, in the early years (1998-2000) the company was not profitable, recording only $220K in revenue in 1999, and over $6 million in losses in the same year.

In 1999, Brin and Page were still thinking to go back to their PhDs at Stanford. Indeed, they approached various competing search engines and platforms, among which Excite, trying to sell Google for $1 million!

Yet, apparently, the Excite executive team eventually didn’t go for it, as the basic premise of Google was to invite users to click on the blue links the tool offered as search results, thus inviting users to leave their search page, and navigate the web.

While this is given for granted today, back then, most search engines were making money by keeping users on their search pages (more similar to what Google has evolved into today), thus, Google posed a threat to their business model.

The same deal was rejected by other players like AltaVista and Yahoo.

In 2000, Google had become very popular, yet it still recorded over $14 million in losses, on a $19 million turnover. Yet Google had been backed by Sequoia Capital, led by John Doerr. Indeed, in 1999 Google had received $25 million in equity funding, from Sequoia Capital and Kleiner Perkins.

As Larry Page announced at the time:

We are delighted to have venture capitalists of this caliber help us build the company, we plan to aggressively grow the company and the technology so we can continue to provide the best search experience on the web.

At the time, PageRank solved an equation of 500 million variables and two billion terms to serve proper search results. The market was still small (one hundred million web searches per day compared to the over eight billion web searches.) that today go through Google).

Venture capitalist, John Doerr explained in his book, “Measure What Matters” how in 1999, he had placed a bet on Google of $11.8 million, for 12% of the company.

While Google was not a first-mover (the search engine at the time was the 18th to enter the market, as Doerr explained), two months later, in the new Google’s offices Larry Page was lecturing Doerr on the poor quality of results of the existing search engines, and how Google would improve, at least of 10x, compared to existing players.

As a venture capitalist, Doerr’s main job was to guess the potential market size of a new industry (this is the obsession of venture capitalists).

And as the story goes, Doerr posed the question to Larry Page:

How big do you think this could be?

Larry Page responded:

Ten billion dollars.

This seemed a crazy market cap to Doerr, who in his mind, had considered a potential market size of Google of one billion dollars maximum.

So Doerr asked:

You mean market cap, right?”

And Page swiftly replied,

No, I don’t mean market cap, I mean revenues.

That seemed crazy enough to Doerr, as with ten billion in revenues, Google would be worth at least a hundred billion in market cap, which was the size of Microsoft, IBM, or Intel, at the time.

Six years later, to that conversation, by 2005, Google had reached a hundred billion market cap. By 2021, the Google advertising machine would generate twice that, in revenues alone, making Google (now called Alphabet) a 1.8 trillion dollar company!

Among the most important deals Google sealed in the early years, there was the deal with AOL. Indeed, AOL saw search as a feature within its proprietary network, thus featuring a search engine that enabled users to surf the web.

Initially, GoTo.com (later called Overture) had a deal with AOL to be featured as the main search engine. Yet as this contract expired by the late 90s, Google jumped on it, managing to get the deal with AOL, in place of Overture! This deal was a very important one, which put Google on a further growth trajectory.

Over the years and going into the early 2000s, proprietary networks had become less and less relevant, as more Internet/Web players had spurred up. From e-commerce to search, platforms like AOL had lost traction. In that scenario, Google became the new King in town.

From then on Google became the new dominant player on the Internet. From wrecking the walls of closed proprietary networks. Over the years (the 2010s – present) Google, then become Alphabet, turned into a sort of Walled Garden itself.Being a first-mover is no more the trick?

Technologies can give an important advantage in the very short term. However, those advantages can be lost pretty easily, if a technology is not leveraged fast. Yet implementing new, unproven technology is also risky, initially very expensive, and often requires the ability to develop a whole new market.

To make things worse, even when this new market has been developed, that doesn’t give you a long-term competitive advantage. In fact, new players that come in can do the same, by simply copying part of the strategy that turned out to be successful.

In short, the first player laid the foundation, for the latecomers to leverage the existing technology, and by improving on it to gain an advantage. But if being first is not giving a long-term advantage, what’s the key ingredient there?

The value of network effects

Many tech companies, from the rise of Microsoft going forward, understood the value of a platform strategy. A platform strategy consists in creating value for users by enabling an entrepreneurial ecosystem on top of it.

The essence of network effects stands in the fact that the service becomes exponentially more valuable for each additional user as more users join in. Of course, building network effects isn’t easy either. As many platforms like Uber and Airbnb figured out at the beginning when they needed to understand how to kick off these networks’ effects.

Thus, when it comes to creating a lasting competitive advantage in this digital landscape, even if you are a first-mover you got to think in terms of network effects.

The first-scaler advantage matters only if you can dominate a market in the long-term

When Netscape built the most valuable commercial browser, back in the mid-90s, the company gave up profits, to grow as quickly as possible. The bet was if Netscape grew large enough to have the most shares of the browsers market it could eventually enjoy also wide profit margins in the long term.

Yet, Netscape awoke Microsoft too early. And while Microsoft did leverage its dominating position to crush Netscape, it also managed to overtime destroy its market leadership. Indeed, while Netscape became a multi-billion dollar success, it never turned a profit, and it eventually sold to AOL, as the pressure from Microsoft was becoming unsustainable.

Thus, even when you do scale, and you do it first, you still need to make sure to stably control that market. Otherwise, like in the case of Netscape vs. Microsoft you might be taken over. Of course, in this particular case, Netscape was crashed by a tech monopoly that took advantage of its dominating position. And Microsoft would pay that many times over.

In fact, while the company survived the subsequent waves of the Internet, it was substantially slowed down by the antitrust case, which for years, would be a threat to Microsoft. Today, under the change in leadership, and under the direction of Satya Nadella, Microsoft has also become an over 2 trillion-dollar company.

Changing business playbooks

When browsing took over the early Internet, that was quite unexpected for many. Also, very smart people, like Bill Gates had envisioned a more linear evolution of the Internet, almost as if that was supposed to bring TV online. While this vision would be in part realized through the 2010s (see Netflix) in reality, it also shows that the model of entertainment on the Internet evolved in a whole different way than TV.

The same applied to search. When Google took over, existing giants like AOL, who had successfully dominated in the previous decade, were taken aback by the success of the latecomers in the Internet revolution.

First, players like AOL thought that search was not a commercial killer application, but rather a feature to be added on top of their services. Second, they didn’t necessarily envision, initially, how search engines would change the whole Internet playbook altogether. No more, based on conventional marketing, a tool like Google took over, as it combined product, marketing, and distribution as if they were a whole.

Third, even when consumers were quickly shifting to these new tools, it was very hard to acknowledge existing/dominating players.

In short, things might work the same for a long-time and then suddenly change. And when things do change, they do it so quickly that the dominating market position might be swept away pretty quickly.

Google: the King of the Web 1.0

Bach in the days, Brin and Page didn’t hide their resentment toward the advertising business model, which was the prevalent model for search. Indeed, in the paper “The Anatomy of a Large-Scale Hypertextual Web Search Engine” where Page and Brin presented their first prototype of Google.

With full text and hyperlink database of at least 24 million pages, in a paragraph dedicated to advertising, they explained: “We expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.“

The main issue they had toward advertising was the fact that it was biased and it caused a lot of spam in search results. Indeed, when they met Bill Gross, founder of GoTo, which would later become Overture, the encounter might not have been among the most cordial.

That’s because Bill Gross had figured the market for advertising had massive potential, as he introduced an auction-based system for bidding businesses, based on performance and clicks.

However, this was still back when Page and Brin were two academics completing their Ph.D. at Stanford University. The transition to becoming entrepreneurs would take soon to arrive. Indeed, as venture money was soon to be over a plan B was needed.

In addition, as Google managed to rank advertising based on relevance (for instance, by ranking higher those ads that got more clicks) advertising became a possible option. As Larry Page pointed out in the first Google letter to shareholders:

Advertising is our principal source of revenue, and the ads we provide are relevant and useful rather than intrusive and annoying.

Google revenues start to take off, yet the company would take a few years to become a “unicorn”

By 2000 Google was already a key player in the search industry. However, it wasn’t yet in the safe zone at a financial level. Indeed, in 2000 Google made $20 million in revenue. Even though it had launched its AdWords network, which would allow it to speed up its growth Google’s business model was still transitioning.

Some pieces of the puzzle were still missing. However, the first massive deal came into the door.

Overture was the father of pay-per-click advertising

By the end of the 1990s Bill Gross, founder of Idealab, an incubator where he could execute all his ideas, had also founded GoTo a search engine that for the first time used the pay-per-click business model.

In other words, in the past web portals, like AOL or Yahoo just sent undifferentiated traffic to websites. GoTo introduced a different logic. That of getting paid by the business advertising only when users clicked through it. Thus, only when there was relevant traffic.

The logic behind the GoTo business model might seem trivial today, but it was revolutionary at the time. In fact, with his pay-per-click Bill Gross would buy undifferentiated traffic from web portals at a low cost and sell that traffic for a much higher price.

GoTo soon changed its name to become Overture; while GoTo was both a search engine and an advertising network. Overture instead became merely an advertising network able to arbitrage the price difference between undifferentiated traffic and qualified traffic. Thus, Overture was the first to invent and prove the fact that the pay per click would be the business model of the internet.

At the time AOL was among the most prominent web portals, and among the most significant deals Overture had closed for its distribution strategy. At the time although Google was growing at a super-fast speed, it wasn’t any closer to being the market dominator it would become soon.

Google copied – part of – Overture’s business model and stole the AOL deal

By 2002 Google had finally launched its Google AdWords network that replicated that pay-per-click business model, and it improved on it. While it also figured out that if he wanted to scale up fast, it had to close large deals with web portals like AOL. Although nowadays AOL doesn’t sound to have any importance.

At the time it was among the most popular portals on the web. Known as America Online in 1998 it purchased Netscape, the dominant browser of that time. In short, there was a time when AOL was almost synonymous with the Internet.

In May 2002 the deal between AOL and Overture was expiring, and it was time for Google to take swift action. As reported in the book “Googled: The End of the World As We Know It” at the time Page said in relation to the AOL deal “I want us to bid to win,” while Kordestani in charge of business development and sales warned, “You’re betting the company if you do that.” According to Auletta’s account in the book Page replied to Kordestani “we should be able to monetize the pages, if not we deserve to go out of business.”

Whether or not those words are accurate that deal points out a critical aspect. At that point, Page and Brin were not only the engineers that had created PageRank but most of all shrewd entrepreneurs that understood the importance to close the right deals to kill competitors and dominate the market!

Overture sued for patent infringement then Yahoo settled the lawsuit with Google

Not long after the adoption of Google AdWord Overture sued it for patent infringement. The claim was that Google had copied the Overture model. However, after losing the AOL deal

Overture stock plunged 36 percent, with its stock at $21.99. Although the company would keep making high profits margins, it would never recover from that. In fact, in 2003 Yahoo bought Overture for $1.63 billion, valuing it at $24.63, roughly a 15 percent premium compared to its closing at the time of the deal.

Now part of Yahoo, in 2004, Google settled the Overture dispute. As reported in NY Times “Google agreed to give Yahoo 2.7 million shares, worth $291 million to $365 million if the shares sell within the range of $108 to $135 that Google has estimated for its initial offering price.”

It was the end of Overture and the rise of the most influential tech giant, today worth more than eight hundred billion dollars.

Google was primarily targeting technology from Applied Semantics called AdSense. It was the missing piece of the puzzle. In fact, with AdSense, Google could finally offer targeted ads on the websites of partners that joined the program. In short, Google would provide businesses with the chance to show their banners on the estate of those blogs which had become the heart of the web back in the 2000s.

It would also allow those blogs to jump from being amateurs to making some money via advertising. It was all tracked and based on the context of the page.

The AdSense value proposition was quite compelling. As pointed out in a 2004 financial report Google would “generate revenue by delivering relevant, cost-effective online advertising. Businesses use the AdWords program to promote their products and services with targeted advertising. Also, the thousands of third-party websites that comprise our Google Network use our Google AdSense program to deliver relevant ads that generate revenue and enhance the user experience.“

AdSense would become a critical part of the business.

Google embraced the whole web with its business model

At that stage, Google was ready to take off. Back in 2003 when Google had finally fine-tuned its business model, it had three primary constituencies:

• Users: Google provided users with products and services that enabled them to find any information, quickly.

• Advertisers: Google AdWords program, the auction-based advertising program allowed businesses to deliver ads both to customers on Google sites (for instance, the search page) and through the Google Network (any blog or site part of the AdSense program).

• Websites: Google free products, Google AdWords and Google AdSense embraced the whole web. While users get information for free and quickly. Businesses could make money by sponsoring their products on Google and via the Google network. Publishers could also quickly monetize their content.

Once the business model had all the pieces, needed growth became the norm. If at all, Page and Brin had to make sure not to have Google implode for hypergrowth. Thus, the hardest challenge might have been managing hypergrowth that would continue for over two decades.

In 2014 Google restructured the company as Alphabet, with Google as a subsidiary. Beyond Search, today Alphabet offers services like YouTube, Maps, Play, Gmail, Android, and Chrome to billion of people worldwide.

The Google business model is way more diversified today than it was back in 2000. By 2017 Advertising still represented 86% of its revenues. Google – now Alphabet – also devoted part of its revenues to investing in bets which might become its next cash cow. Today those bets only represent over 1% of the total Google turnover.

In 2017, in the founders’ letter, Google explained how it started to roll out AI for several aspects comprised of its products:

• understand images in Google Photos;

• enable Waymo cars to recognize and distinguish objects safely;

• significantly improve sound and camera quality in hardware;

• understand and produce speech for Google Home;

• translate over 100 languages in Google Translate;

• caption over a billion videos in 10 languages on YouTube;

• improve the efficiency of data centers;

• suggest short replies to emails;

• help doctors diagnose diseases, such as diabetic retinopathy;

• discover new planetary systems;

• create better neural networks (AutoML);

• … and much more.

By 2019, Google confirmed its “AI-first” strategy. Indeed, on a stage at the Google I/O conference, Pichai highlighted:

We are moving from a company that helps you find answers to a company that helps you get things done, we want our products to work harder for you in the context of your job, your home and your life.

This change was critical, as it moved the mission of the company from “organizing the world’s information and making it universally accessible and useful” to “helping you get things done.”

This is a critical move, from a business standpoint, as Google highlighted its focus on generating revenues based on its productivity tools. The segment that for decades had helped Microsoft remain among the largest tech players.

No wonder then, that Google free tools play a key role in that.

Today Google employs sophisticated language models, trained on billions of parameters, which in the future might be used to enable the search engine to generate more and more specific answers to users’ queries.

Let’s keep in mind, that after almost 25 years after the company’s inception, Google still has many challenges ahead.

Google’s business model today

As we saw, Google is a platform, and a tech media company running an attention-based business model. As of 2021, Alphabet’s Google generated over $257 billion in revenue.

Over $209 billion (more than 81% of the total revenues) came from Google Advertising products (Google Search, YouTube Ads, and Network Members sites).

They were followed by over $28 billion in other revenues (comprising Google Play, Pixel phones, and YouTube Premium), and by Google Cloud, which generated over $19 billion in 2021.

While Google, now Alphabet, has been diversifying its business model for more than a decade. Its main revenue stream is Google’s search engine, which generated about $149 billion in revenue in 2021.

Followed by the network members’ websites (the sites that adhere to Google AdSense for a revenue share on top of the advertising revenues generated on their properties).

And YouTube Ads, which generated about $29 billion (this excludes YouTube Prime Memberships, which are comprised of the other revenues).

Among the bets which Alphabet has placed over the years, there are ventures in the seld-driving industry, robotics, sustainable/renewable energies, and more.

Google’s Alphabet is one of the most successful tech players of our time. While Alphabet now is a vertically integrated company that goes beyond Google’s search engine. In reality, the Google search engine still plays a key role in the overall organization. In fact, Google is the main asset that provides resources to Alphabet to keep investing in new areas, keep integrating its supply chain, and also placing bets in completely new and unrelated areas.

Google in numbers today

Google’s profitability has slightly improved in 2021, thanks to the fact it managed to increase its revenue faster than it increased its operational costs, as traffic on its platforms increased substantially during 2020-2021.

For the first time in its history, Google generated over $257 billion in revenue. And the company almost reached a two trillion market capitalization.

For some context, when Google IPOed in 2004, it recorded almost a billion in revenues, and it was worth about $23 billion, as it popped at its IPO date to $85 per share (On April 7th, 2022, a Google stock is worth $2,743.52).

At the time, in 2004, Google had just managed to scale its advertising machine comprised mainly of Google AdWords (today Google Ads) and Google AdSense. At the time the advertising machine was primarily based on Internet traffic from desktop devices. That was a completely different world.

As we’ll see throughout this analysis, today most traffic comes from mobile. And Google’s mobile ads platforms (Google AdMob) play a key role. So let’s dive a bit into the main financial segments of Google.

Google’s main segments in 2021

In 2021, the Google advertising machine generated over $209 billion in revenue. This represented an over 42% growth, year over year! This is a massive improvement for a company worth almost two trillion. In a market landscape that is no anymore in favor of digital advertising.

How did Google pull this off?

We’ll see this shortly. But for now, let’s emphasize a few key points.

Today the Google advertising machine is comprised of three main products:

• Google Search/Properties: This represents the set of products that Google owns, from the search engines to all the other vertical platforms that the company operates (Google Discover, Google News, Google Travel, and more). In 2021, this segment generated over $148 billion!

• YouTube: This is of course one of the most successful business acquisitions ever done. It was acquired by Google for $1.65 billion in 2006. It’s important to notice that Google was able to integrate YouTube and scale it up. A feat that not every other company would have been able to achieve. At the time YouTube was getting sued for various copyright infringements (the platform is comprised of user-generated content, often posting copyrighted materials) that would have most probably bankrupted it if it had stayed a startup without Google’s backing. By 2021, YouTube has become an advertising machine generating over $28 billion (this doesn’t count the YouTube memberships, which are reported separately).

• And Google Network Members’ properties: this is the set of publishers that decide to opt into Google’s advertising network (either AdSense for desktop, or AdMob for in-app advertising). Here Google shows advertising on the network members’ properties, thus splitting the revenues with them. In 2021, Google’s network members generated over $31 billion of revenue.

As we’ll see understanding the difference among these segments helps us understand how Google manages its cost structure for each segment.

What determines the growth of each segment?

• Google’s search advertising has been driven by growth in search queries. In fact, since the pandemic hit, more and more users started to use Google’s products. This trend has continued. However, most of it was driven by mobile users’ growth. This is an important aspect, as it shows that Google’s main driver of growth is based on mobile traffic. This changes the way the company needs to prioritize its product developments efforts, its ad formats served to users, and also how it experiments.

• YouTube growth was driven primarily by improved ad formats. This means that Alphabet (as it’s evident to anyone going on YouTube) has ramped up the advertising operations on YouTube. In short, on YouTube now there are way more ads than before. This “improved ad formats” is the result of YouTube’s extreme stickiness with users, which enables Alphabet to play with its ad formats.

• Google’s network members’ properties were primarily driven by AdMob. In short, the mobile advertising platform, powered up by Android devices through the Google Play store, was the main driver of revenue growth in 2021. This shows how Google has shifted also its focus on the mobile advertising platform.

Let’s see how, a little bit more in detail, ad monetization changed for Google.

The Google advertising machine today

In 2021, three main factors determined the improvement in ad monetization by Google.

• First, Google recorded an increase in paid clicks (driven by an increase in user adoption and search queries primarily on mobile devices).

• Second, this also drove more paid clicks in AdMob through the Google Play store.

• Third, as we saw Google is testing various ad formats (we can argue it’s showing more ads) both on Google’s products and YouTube, which slightly improved monetization.

Among the other revenues, instead, Google Cloud also recorded an important growth thanks to the Google Cloud Platform.

Where instead, both the Google Cloud platform and the other Google Bets run at negative margins. Important to distinguish here.

The Google Cloud platform is critical for the future success of the Google AI platform.

At the end of it all, Google remains a machine transforming traffic into revenues, how?

The traffic acquisition cost represents the expenses incurred by an internet company, like Google, to gain qualified traffic – on its pages – for monetization.

Over the years Google has been able to reduce its traffic acquisition costs and in any case, keep it stable. In 2021 Google spent 21.75% of its total advertising revenues (over $45.56 billion) to guarantee its traffic on several desktop and mobile devices across the web.

When you look at a business model like that of Google, which is primarily a software/digital/tech company, it’s easy to fall into the trap of thinking it’s an asset-light business.

Indeed, a software company is asset-light compared to much more traditional industries (for instance manufacturing) but they do have massive expenses to guarantee their distribution strategy.

For instance, in 2021, Google spent over $45 billion in traffic acquisition costs, which comprise costs incurred to cut distribution deals with other companies (like the multi-billion deal Google has to be the default search engine on Apple’s Safari), and many other deals, together with the money paid to partners to bring traffic back to the Google’s properties.

Now, keeping this number stable over time, is critical, to assessing the health of the advertising machine. In fact, on top of the traffic that Google generates, the company is able to monetize it many times over.

For instance, in 2021, Google spent over $45 billion in traffic acquisition costs, but it generated over $209 billion in advertising revenues.

This means that Google was able to monetize its traffic 4.6 times its traffic acquisition costs.

Companies like Google have to cut distribution deals and split revenues with content partners to bring traffic back to their main properties online. For instance, in 2021, Google spent over $45 billion in traffic acquisition costs, but it generated over $209 billion in advertising revenues.

This means that Google could monetize its traffic 4.6 times its traffic acquisition costs. An increased monetization multiple over the years is a good sign. It means that Google was able to keep its advertising machine competitive. On the opposite side, a negative monetization multiple means the advertising machine is losing traction.

As you can notice from the above, this is a purely financial metric, which needs to be balanced out with a qualitative analysis of why the metric increased in the first place.

Indeed, it’s critical to keep into account these questions:

• Has monetization increased thanks to an improved UX? Or is monetization worsening the UX?

• Has monetization improved thanks to an increased customer base? Or has it increased due to higher prices per ad?

• Lastly, how is monetization balanced with legal risks posed by increased tracking?

All these questions are critical to answer, because, financially Google’s advertising machine seems as strong as ever. There are hidden risks underlying it, which might, all of a sudden threaten its overall business model.

In fact:

• On a positive note, Google has managed to further scale, as a consequence of the pandemic. Thus, bringing its products to hundreds of millions of new users. Yet. this further scale (especially on mobile devices) has created new challenges for the company. Which is finding it harder and harder to properly index a web made of billions and billions of pages, and growing. This poses a threat in the long term, as it might reduce the quality of organic search results.

• To monetize this expanded user base, Google is serving more ads. This might work in the short term to squeeze the advertising machine. But it might make the overall experience bad in the long term. So it’s critical to balance these things out.

• To further expand its revenues, the company has also increased the price per ad. While, in the short-term, the strategy works, in the long-term, this might substantially reduce the customer base.

Where is the next wave headed?

When Google wrecked apart the tech giants of the early Internet era, it built its competitive advantage by enabling users to find information around the exponentially growing number of web pages. This balance was broken when back in the 2015s Google started to roll out more and more features to keep users on its search results pages.

In February 2009, about twenty years from the first version of the Hypertext project, Tim Berners-Lee stood on a TED stage in Long Beach, California. As he opened the speech he remarked how 20 years had passed since the inception of the project that would lead to the web, and yet for 18 months that project, back in 1989 stood on a desk at the CERN, without anyone doing anything about it.

Until Tim Berners-Lee volunteered to do it as a side project!

In that time span, Tim Berners-Lee had laid the foundation for HTML, and the idea of URLs that stood behind HTTP. As he remarked in 2009, he felt compelled to take that side project, as he worked in a large research lab and felt extremely frustrated by the fragmentation that existed at the time.

There was no single protocol or framework that could connect all the various programs and make them talk. That is how the web was conceived, as a massive document that connected all other documents via hyperlinks. And yet by 2009, Tim Berners-Lee highlighted another frustration, that of connecting data. Up until that point, therefore, the web connected text and documents but failed to connect data.

Tim Berners-Lee explained that concept with these words:

So I want us now to think about not just two pieces of data being connected or six like he did, but I want to think about a world where everybody has put data on the web and so virtually everything you can imagine is on the web and then calling that linked data.

This would give the rise to the Semantic Web, which has already become a reality. Indeed, if we look at Google itself a good chunk of queries that it serves to users are served from its Knowledge Graph, a massive database made (as of 2020) of more than 500 billion facts about five billion entities (an entity is anything that exists on the web, it can be a person, a place, an event and so forth).

It’s important to note that already now, Google (with the Knowledge Graph), Facebook (with the Social Graph), and all the other tech giants, in a form, have already converted their “databases” into powerful Graphs.

Yet while these companies put together massive amounts of data about anything on the web, their algorithms are still siloed, walled, and managed as “proprietary data.”

Thus, while these semantic technologies did turn into advanced features for users at scale (think of how voice assistants can give answers to millions of questions) they do not talk to each other, and they might never talk to each other (why would Google, now Alphabet cooperate with Amazon? Or vice versa? when perhaps they are fighting against each other for advertising revenues? – which might also be relevant for the future digital marketing landscape – the only exception is they might come together only to fight regulation).

This is also where the Blockchain ecosystem becomes interesting. As the data that sits on the Blockchain protocols, this is usually open and accessible. In this sense, Web 3.0, as also intended by Ethereum’s co-founder Gavin Wood (who also built Solidity, which is the native language of the Ethereum Blockchain) would achieve its vision:

Web 3.0 is an inclusive set of protocols to provide building blocks for application makers. These building blocks take the place of traditional web technologies like HTTP, AJAX and MySQL, but present a whole new way of creating applications. These technologies give the user strong and verifiable guarantees about the information they are receiving, what information they are giving away, and what they are paying and what they are receiving in return. By empowering users to act for themselves within low-barrier markets, we can ensure censorship and monopolization have fewer places to hide. Consider Web 3.0 to be an executable Magna Carta — ‘the foundation of the freedom of the individual against the arbitrary authority of the despot.

This opened up a whole new chapter. But I’ll leave this story for next time 😉

They had known each other from their time at NuvoMedia, the company they had led to the development of the Rocket eBook. The first e-book was launched in 1996 when the commercial Internet was still at the embryonic stage (for some context, the Amazon Kindle would be launched in 2007).

Yet, even though Eberhard had founded and led NuvoMedia to a successful acquisition, which in the year 2000, was purchased for $187 million, by another media company, Eberhard was all but rich.

In fact, over the years his shares in the company had been diluted to the point, that, Eberhard’s exit from the sale only had not made him rich, but as he was divorcing his wife, most of that wealth went to her, and Eberhard had to start all over again.

Yet, along his journey Eberhard, had met Elon Musk, which, by 2003, was deep into his new venture: SpaceX.

Musk’s first ventures

Elon Musk had successfully exited the PayPal sale, by making $180 on a $1.5 billion acquisition in 2002. Yet, while SpaceX had been founded in 2002, Elon Musk had started to look into it, a couple of years before.

Musk was not new to entrepreneurship and the rollercoasters this “profession” was about. In fact, a few years back to PayPal, in 1995, together with his brother, Musk had founded Zip2.

The company built maps and business directories, which were very useful applications for media websites. Eventually, they sold the company to Compaq, for over $300 million, which made Elon Musk more than $20 million to start his next company. Zip2 would become a component of AltaVista, the search engine owned by Compaq.

With the new cash infusion, Musk started his next company, called X.com. Musk’s vision was to transform X.com into a financial behemoth, through the Internet. While his vision was unbounded, he also pushed his team to execute fast.

Yet, X.com had been founded in late 1999, when the commercial Internet was still young, and revolutionizing the financial system was not as simple as it seemed.

X.com’s team randomly met the team of Confinity (for a period they were neighbors sharing the same office building).

Another startup, created in late 1998, similarly to X.com was trying to build an Internet financial company. Yet, while X.com had an unbounded vision, Confinity, which had been founded by Pether Thiel, and Max Levchin, wanted to give people the ability to pay online, by beaming their money through a device, called PalmPilot.

For some context, in the late 1990s, the Palm Pilot was a successful device, especially in California, which is where Confinity was operating. Yet, the initial business plan of the company didn’t seem to work in the real world.

In fact, the beaming technology never took off as they had envisioned.

Instead, by late 1999, one thing was clear, a “side feature” became the killer commercial application for both companies. That was the ability to pay by using an email.

This, in fact, would become the primary feature for both X.com and Confinity, and both had stumbled upon it, as it got very popular on a platform: eBay.

While those two companies were very different, they had completely different visions, and leadership, in a strange turn of events, the companies that once were neighborhoods, eventually merged.

The new company was called PayPal, after Confinity’s email payment feature, which was already well known thourhg eBay. Thus, the company took the name of the side-feature, which unexpectedly became the commercial killer application.

Yet, by early 2000, the newly created PayPal, was all but safe.

In fact, the various near-death experiences in a year time frame turned PayPal into a drama machine. In the meantime, this drama machine had taken out various CEOs, until Elon Musk became – unwillingly – CEO of the company.

Yet, once CEO he pushed the company with his unrelenting management style, which pushed people beyond their limits. The management style of Musk, coupled with a complete divergence in vision between Musk and the other co-founders (in particular Thiel, Levchin, and Sacks) led to a final conflict.

Indeed, in 2000, Musk would be ousted as CEO, with a coup organized by PayPal’s other co-founders, Peter Thiel, Max Levchin, and David Sacks. As Musk was on his honeymoon, he was flying and he could not fight that back.

Musk was out from PayPal, and now he had time to think about what would come next!

SpaceX

As Musk got time to think about his next ventures. He had looked into something that he had been passionate about since childhood: space.

First, he tried to get involved by helping NASA get more funds and interest, in space exploration. He thought that was the main issue. Space exploration, a hot topic, during the 1960s-70s, had stalled, in the last decades.

Yet Musk realized it was not a matter of funding. The whole innovation system, related to space, was non-existent, so he needed to get involved.

As he got involved, he started to build SpaceX, from scratch. Indeed, initially, he had looked into various ways, to outsource parts of the rockets. But over time, SpaceX would have a different approach. SpaceX started to build all the components that would make up the rocket, in-house.

And yet, let’s remember, when SpaceX’s journey, crosses that of Tesla, we’re in 2003, when all SpaceX had was a prototype rocket on a computer. It would still take a few years for SpaceX to successfully perform its first launch.

In fact, on  September 28, 2008, SpaceX completed the Falcon 1 launch successfully!

In this context, Tesla entered the picture.

Back to Tesla

Musk had always been passionate about cars. In the footage, back in 1999, Musk was among the buyers of a rare supercar, which he showed off to the camera:

EVs were in the air. Indeed, in 1999, GM had launched its EV1, which turned out as a complete flop:

But it was also about performance and coolness.

In fact, most of the electric vehicles that were in production were bulky, ugly, and ineffective.

Tesla was set to change all that.

Telsa’s Roadster

Tesla’s initial plan was to manufacture a sports car that would be compelling to a very niche audience. Indeed, the target for the Tesla Roadster was to showcase the technology to a bunch of innovators, that liked the idea of an electric vehicle, which performance, could compete with other sports cars.

However, as Eberhard started to roll out Tesla’s business model (Musk had endowed Tesla with a few million, in 2004, to start the production of the Roadster) it became clear that building a performance electric car was not an easy fit.

While Eberhard had targeted the right audience (wealthy Californians, who would use the Tesla Roadster as a status quo), he had miscalculated the execution strategy.

Indeed, Eberhard thought Tesla could be built by outsourcing most of its parts (just like he had done years back with manufacturing the NuvoMedia ebook device). Yet, this turned out to be not the case.

Several challenges came up, right on:

• Batteries cathed fire.

• Components were way more expensive than they thought.

• Large suppliers didn’t want to deal with Tesla, at the time a small startup, when the legal liability of batteries was much bigger than the potential payoff for the supplier.

All the above didn’t help.

And Eberhard felt more and more pressure, as time goes by, and the Tesla Roadster is far from manufacturing, and it was way more expensive than the price point Musk had promised.

In this period, a person which played a key role at Tesla, and would be the main point of contact for Musk was JB Straubel. An engineer at the core, he was interested in battery technology.

He had worked in 1993 for Rosen Motors, and, just like Ford, in the late 1800s, Straubel was a racer.

Indeed, for him racing electric cars was a way to showcase their torque (with respect to gas-powered vehicles, electric cars produce an instant torque, which made the start of an EV more similar to a rocket launch than a car start).

Straubel’s ability to tinker with the electric engine would prove critical. In fact, one of the major issues with battery packs was that they caught fire.

Strauber invented a way to prevent batteries to catch fire, by enabling these cells to dissipate their energy. This was a major improvement.

While Eberhard was trying to progress with the Roadster, Musk was putting growing pressure on him. He wanted Tesla to execute faster, and he came up with continuous changes to the car.

Musk, therefore, had very close ties to the company. Indeed, when he had first invested in Tesla, of the total $6.5 million round, Musk had invested $6.35 million of his own money, while Eberhard had invested $75K (as a “skin in the game deposit”).

While the relationship between Musk and Eberhard, initially was a good one.

Over time, it deteriorated. And things only got worse, when Musk introduced a team within Tesla to audit its finance and see what was the real cost of producing the Roadster, at that moment.

From the analysis, it came up that expenses were out of control, and that the challenges to producing the Roadster were none near!

This triggered Musk, who added pressure on Eberhard and convinced him to start thinking about resigning as CEO and focus on the product instead.

While they both had agreed, eventually things precipitated, and the relationship between Musk and Eberhard quickly deteriorated.

To the point that Eberhard left Tesla, by signing a non-disparagement agreement, and after a quest to find Tesla’s new CEO, eventually, Musk appointed himself! It was 2008, and one of the greatest financial turmoils was to hit the US.

The Secret Tesla Master Plan

By 2006, Musk would lay out the foundation for Tesla’s plan for the next decade. It was a four points master plan, structured as below:

1. Build sports car

2. Use that money to build an affordable car

3. Use that money to build an even more affordable car

4. While doing above, also provide zero emission electric power generation options

These four points would take a decade to be executed. Musk showed how, even when it comes to an unbounded vision, like his, most of it is still about execution.

In the meantime, Musk had become the CEO of Tesla, which had also turned into a draining endeavor, consuming a lot of his time. And yet, as the 2008 financial crisis hit, Tesla managed to survive it, also thanks to a partnership with Daimler, which kept the company afloat.

As Wired explained back in 2009:

The deal provides Daimler with batteries and the know-how needed to bring an electric car to market “at the highest possible speed,” company officials said. In exchange, Tesla gets a big pile of cash and, perhaps more importantly, the parts and engineering expertise it needs to build the Model S sedan.

This deal would be critical for Tesla to get additional oxygen while having a strategic partner, and going toward the IPO.

In fact, Tesla would IPO the year after, at $17 per share, valuing the company at about $2 billion.

Tesla borrowing Apple’s retail strategy

As Tesla started to roll out its business plan, back in 2003, the company chose to keep control over the sales experience.

This choice was not an easy one. Indeed, the Tesla executive team liked the idea to go direct to consumers. But in the auto industry that was not an easy fit.

In fact, most auto companies sold through car dealers and franchises. Those franchises represented a huge, and powerful industry, which made most of its money, not necessarily on the sale of the vehicle, but rather on servicing the vehicle over time.

Yet, since the onset, Tesla had a feeling that going through car dealers wasn’t the right pick for it. And it started to build its retail capabilities.

In that respect, Tesla borrowed Apple’s retail strategy. For that matter, George Blankenship, a key player in the retail strategy of both GAP and Apple, played a key role in launching the Tesla store operations.

In 2008, Tesla opened up its first store, in LA, on Santa Monica Blvd.

The store would play a key role in both educating people about the Tesla brand, but also, later on, developing the service side of the business.

By controlling the customer experience, Tesla could, over time amortize the cost of the stores and build a valuable/differentiated brand. Even though Tesla’s cars were expensive.

Building up stores that sold wasn’t easy either.

By 2013, Tesla sales figures looked bleak, so much so that Musk looked into a potential sale of the company to his friends, Google’s co-founders’ Page and Brin, for $6 billion.

Indeed, after setting up the templates for the stores, Blankenship had left the company. And Tesla’s slowing sales were clear in 2015. McNeill revamped the sales force and trained it to close deals.

Where in the early days the store was only about education, by 2015, it had to become a sales machine, to make Tesla numbers add up!

By 2022, Tesla had hundreds of locations across the US.

To get to its sales numbers though, Tesla had to solve another critical issue,: making batteries for its cars available at scale!

The Gigafactory

As we go through the whole Tesla history, another key ingredient was the Gigafactory.

In fact, as Tesla had successfully launched, and dumped up production of the Roadster first, it had already started to invest in the Model S, which by 2012, had launched.

Yet, the real turning point, for Tesla’s scale would be represented by the Model 3.

Indeed, the Model 3 would have changed it all for Tesla, by expanding its market and by enabling it to “cross the chasm.”

The Roadster proved the viability of the technology to a small niche of the sports car industry, represented by innovators who were more interested in the technology.

The Model S had represented a further step. Moving from innovators to early adopters. People are interested also in the technology, but also in the performance, aesthetics, and in part, pricing.

As Tesla moved ahead, the Model 3, became the turning point. The car to move from early adopters to the early majority.

In fact, as the company highlighted “Tesla’s mission is to accelerate the world’s transition to sustainable energy through increasingly affordable electric vehicles and energy products. To ramp production to 500,000 cars per year, Tesla alone will require today’s entire worldwide supply of lithium-ion batteries.”

Therefore, where the Roadster was about prototyping, the Model S was about manufacturing, the Model 3 was all about mass manufacturing!

In order for Tesla to achieve mass scale, the Gigafactory played a pivotal role.

As the company explains:

Tesla broke ground on the Gigafactory in June 2014 outside Sparks, Nevada. The name Gigafactory comes from the word ‘Giga,’ the unit of measurement representing “billions.” The Gigafactory is being built in phases so that Tesla can begin manufacturing immediately inside the finished sections and continue to expand thereafter. Already, the current structure has a footprint of more than 1.9 million square feet, which houses approximately 5.3 million square feet of operational space across several floors. Still, the Gigafactory is about 30 percent done. Once complete, Tesla expects the Gigafactory to be the biggest building in the world – and entirely powered by renewable energy sources. Designed to be a net zero energy factory upon completion, the facility will be primarily powered by solar, and installation is already underway.

For Tesla to build its own batteries was another turning point.

Vertically integrating

As Tesla scaled, one thing was clear, Musk sought to control.

Tesla had kicked off its business plan by wanting to outsource almost everything.

Instead, it ended up manufacturing its own batteries, while going direct to consumers with its online and retail stores.

Another piece of the puzzle was lacking: energy production.

In that respect, a company called SolarCity, founded in 2006, would eventually become part of Tesla.

Musk had prompted his cousins, Lyndon Rive, and Peter Rive to start SolarCity.

The idea was to build this into an external arm, able to provide potentially clean energy for Tesla vehicles. In fact, Musk backed the company, while sitting on the boars of SolarCity and Tesla.

Yet, by 2016, the financial outlook for SolarCity looked bleak, and Tesla had to bail out the company by purchasing it for $2.6 billion.

Later on, Musk would be involved in a lawsuit from shareholders around this acquisition.

However as SolarCity looked like a bailout, Musk was able to reframe it as an expansion of Tesla’s mission.

In fact, in 2016, ten years after the Tesla Master Plan, Musk drafted the Master Plan, Part Deux (part two):

1. Create a low volume car, which would necessarily be expensive

2. Use that money to develop a medium volume car at a lower price

3. Use that money to create an affordable, high volume car And…

4. Provide solar power. No kidding, this has literally been on our website for 10 years.

As Musk justified at the time:

We can’t do this well if Tesla and SolarCity are different companies, which is why we need to combine and break down the barriers inherent to being separate companies. That they are separate at all, despite similar origins and pursuit of the same overarching goal of sustainable energy, is largely an accident of history. Now that Tesla is ready to scale Powerwall and SolarCity is ready to provide highly differentiated solar, the time has come to bring them together.

While this was a narrative Musk had built around, and to justify the acquisition of SolarCity, by 2021, the energy generating and storage segment (of which SolarCity was part) generated over $2.79 billion in revenues.

Subsidizing Tesla via its leasing arm

When Apple launched the iPhone, it combined hardware, operating system, and a marketplace to enable third-party to develop applications on top of its device.

The iPhone’s success was staggering, not just because it represented a device adopted, at mass, which would build the next consumer platform for decades to come.

Instead, Apple had managed to succeed nonetheless how expensive the iPhone was and is (the latest iPhone is more expensive than most computers out there).

How did Apple manage to succeed in distributing its iPhone?

Steve Jobs made mobile carriers subsidize the iPhone by amortizing its cost through the phone plans! (Apple deal explained here).

Still, as of today, most of the iPhone sales do not come from Apple direct stores. They come from third-party stores, which sell those iPhones via mobile carriers plans.

This is how you make a very expensive product, accessible, at scale.

At the same time, Tesla borrowed this strategy. But rather than enabling the subsidizing of Tesla through third-party, the company is doing it the way it has always done, through in-house leasing.

In fact, back in 2019, Tesla started to rump up its leasing operations of the Model 3 (the car which is supposed to go to the masses!) to enable the amplification of its distribution strategy, by subsidizing the product, and by building its own leasing arm.

In 2021, Tesla generated over $1.64 billion in revenues from its leasing arm (growing 56% year-on-year). And it’s not just about the revenues coming from the leasing arm.

It’s primarily about the additional distribution potential that this leasing arm would add to the company’s customer base (considering that Tesla is experimenting with a $0 down payment in various states in the US).

Tesla to the masses

Back in 2018, to Musk’s admission, Tesla was going through a very tough time again (the third near-death experience), and most expected Tesla to fail.

So much so that Musk was looking into selling Tesla to Apple, for $60 billion!

The deal didn’t land, Tesla kept pushing through executing its plan, and after avoiding the worst period since its inception (short sellers were betting against Tesla since 2015), the opening of the Shangai Gigafactory made things look great again!

The Gigafactory is instrumental to Tesla’s future ability to deliver cars at scale. In 2022, another key milestone was achieved. Tesla opened its Berlin Gigafactory, right in the heart of Europe’s automotive industry!

Master Plan, Part Three: An energy infrastructure platform?

While the challenges ahead for Tesla are still major, from mass production to the ability to deliver its new models, to a fully self-driving car, the ability to automate manufacturing through robotics, and to build its leasing/financing arm.

Yet Tesla seems to be building up what we can define as an energy infrastructure platform.

This platform might go well beyond cars, to embrace transportation, robotics, software, service, and finances.

The bet then is how big is this market in the future.

And to be sure, while this all makes sense in hindsight, Musk’s vision to get there has always been there. The pat was all but linear.

Slowly, then suddenly blowing competition off the water

The journey from the Tesla of the early days, to the Tesla of today, has gone through many near-death experiences, potential sales of the company, several mental breakdowns of Musk and the executive team around him, and many exciting achievements!

And still, in 2018, Tesla’s success was all but granted.

It took about 15 years for the company to build a viable business model at scale.

And while things progressed slowly for a long-time, they eventually and suddenly took off, blowing competition off the water.

It took two decades for Tesla to build the company we know today, and three years (between 2018-2021) from close to bankruptcy, to the trillion-dollar company!

If there is a lesson we can learn is innovation is expensive, unpredictable, first slow, then extremely fast, and only explainable in hindsight.

1989

1989 marks the very first form of anonymous transactions through cryptographic protocols with DigiCash. Founded by David Chaum, DigiCash used the cryptographic protocols Chaum created and described in his 1983 paper titled “Blind Signatures for Untraceable Payments.” These protocols closely resembled the cryptography still in use today with both public and private keys for transactions similar to the public and private keys Bitcoin uses.

Despite the impressive technology behind DigiCash that seemed ahead of its time, the company declared bankruptcy less than 10 years later in 1998. DigiCash failed to grow its user base at the rate required for sustainable revenue likely due to how early the technology entered the market. It was before eCommerce fully integrated into the internet, so the technology behind DigiCash did not have many use-cases.

1991

For the first time, Stuart Haber and W. Scott Stornetta described a “cryptographically secured chain of blocks” in 1991.

1998

In 1998, computer scientist Nick Szabo began working on a decentralized digital currency called “bit gold.” Later on, he coined the term “God Protocols” to refer to the concept of a set of computer protocols capable of arbitrating and facilitating private, seamless, and unbiased value exchanges involving two or more independent parties.

For this concept, “God Protocols” would act as a third party equally accessible to parties involved in exchange processes. Furthermore, as a neutral third party, “God Protocols” would uphold and execute stipulatory rules between parties reasonably and seamlessly, ensuring privacy by keeping all sensitive information from uninvolved entities.

2000

Stefan Konst made public his theorization of cryptographically secured chains. In addition to theorizing cryptographically secured chains, he also conceptualized its possible implementation.

2008

In 2008, a white paper containing a blockchain model was released and published by a developer, or developers going by Satoshi Nakamoto’s pseudonym.

2009

Satoshi Nakamoto developed Bitcoin as a currency that allows peer-to-peer transactions and eliminates the necessity for a central bank or other intermediaries in operating and maintaining the ledger.

Although not the first of its kind, Bitcoin is considered the most successful version of online currency as its technology solved long-standing problems in the crypto field.

Behind Bitcoin’s successful feat is the technology that Satoshi Nakamoto, themself, designed — the Blockchain. Blockchain is the record-keeping technology behind the Bitcoin network. Up to this day, the same, original, largest blockchain is still the one that runs and facilitates transactions in the Bitcoin network.

Aside from Satoshi Nakamoto, as we saw, another notable personality in the development of blockchain and cryptography is David Chaum. Apart from pioneering cryptography and privacy-preserving technologies, the invention of digital cash also gets attributed to David Chaum.

David Chaum’s 1982 dissertation is the first blockchain protocol proposal ever known. “Computer Systems Established, Maintained, and Trusted by Mutually Suspicious Groups” contained all but one vital element of the blockchain protocol, which received elaboration in Bitcoin’s whitepaper.

The year after the release of a white paper, Satoshi Nakamoto developed the first blockchain in the form of a public ledger for transactions using Bitcoin was implemented in 2009.

2014

Developers began searching for other applications of blockchain technology beyond currencies. Hence, the birth of Blockchain 2.0, an era of exploration for blockchain’s potential in other financial, inter-organizational transactions apart from currency.

In the same year, the Ethereum blockchain network introduced Smart Contracts, integrating computer programs that represent financial instruments like bonds into the blockchain technology.

Monero, the ultimate privacy coin, was also released in 2014 on April 18th.

2015

Shortly after introducing smart contracts, the Ethereum network released on July 30, 2015. Its initial release included 72 million coins with the first trade valuing a single coin at $2.77 USD. However, this value quickly fell the very next day to $0.81.

In 2015, Coinbase also became the first U.S. bitcoin exchange to open after receiving a $75 million investment. Since then, Coinbase has grown into the largest cryptocurrency exchange in the United States.

2017

With 2017 came some exciting altcoins looking to solve existing problems in the crypto space. First, there was Bitcoin Cash which was released in August. It aimed to reduce the volatility of transaction fees that were plaguing the Bitcoin network by increasing the maximum block size. This reduces the cost of a transaction by allowing larger blocks of data to transfer with a single transaction.

Next came the release of Cardano in September. Cardano differentiates itself through its heavily researched and peer-reviewed whitepaper helping to establish credibility for smart contracts built on the network. The creators of Cardano even established an organization dedicated to research related to blockchain and cryptocurrencies called IOHK. Cardano’s strong documentation and research-based approach make it a great solution for building decentralized apps and smart contracts.

2017 also saw the first hard fork of Ethereum with the Byzantium hard fork aimed to improve the privacy, security, and scalability of Ethereum as a whole.

At the same time as these impressive projects launched, bitcoin reached a major milestone. One bitcoin became worth more than one ounce of gold. While looking back this may not seem like a major feat, at the time it solidified that Bitcoin provided real value that could not be ignored.

2018

Based on a whitepaper created in 2017, EOS.io first released in June by Block.one. It aims to nearly eliminate transaction fees that still cause difficulties in the widespread adoption of cryptocurrencies. EOS.io also set out to make their platform extremely easy for other developers to work with. They created extensive documentation on working with their platform as well as training courses and certifications specific to their platform.

2020

Throughout 2020, most major cryptocurrencies continuously climbed in value with Bitcoin reaching over $20,000 USD and Ethereum reaching over $500 USD by the end of the year. This trend is continuing into 2021 with Bitcoin reaching over $60,000 USD in April and Ethereum reaching over $2,700 USD at the end of April marking a new all-time high for both cryptocurrencies.

Blockchain 2.0 and New Business Platforms

As Bitcoin successfully created a blockchain-based form of currency, developers began separating blockchain from currency and started exploring other use cases for such technology.

Although blockchain was not exhumed from currency as several other “altcoins” began building on the blockchain technology, there were genuinely different blockchain applications developed.

This is an extract from Blockchain Business Models

Read Next: Blockchain Flywheel, BAT Token, ERC-20 Token.

Read Also: Proof-of-stake, Proof-of-work, Bitcoin, Ethereum, Blockchain.

The beginnings of Ethereum

In a 2014 message from Vitalik Buterin that read “Welcome to the New Beginning,” Buterin explained “When the grand experiment that is bitcoin began, the anonymous wizard desired to test two parameters – a trustless, decentralized database enjoying security enforced by the austere relentlessness of cryptography and a robust transaction system capable of sending value across the world without intermediaries. Yet the past five years have painfully demonstrated a third missing feature: a sufficiently powerful Turing-complete scripting language.” 

And Vitalik Buterin continued listing the innovations that Bitcoin had brought but then got to the point of what Ethereum would be for “Ethereum is a modular, stateful, Turing-complete contract scripting system* married to a blockchain and developed with a philosophy of simplicity, universal accessibility, and generalization.”

Vitalik Buterin also highlighted the main goal of such a Blockchain model “to provide a platform for decentralized applications – an android of the cryptocurrency world, where all efforts can share a common set of APIs, trustless interactions and no compromises.”

This message alone well explains the whole foundation of Blockchain. A general-purpose Blockchain, working more like a programming language able to accommodate an infinite number of use cases on top of it. Indeed, as Vitalik Buterin has highlighted in many of his interviews, initially he had thought of a Blockchain that could be used for a few dozens of use cases. But then he realized that the strength of a modular, general-purpose Blockchain would have been unlimited. 

This apparently mad project turned into one of the most successful Blockchain protocols, that enabled various use cases (from decentralized applications and finance to decentralized autonomous organizations, non-fungible tokens, and more). 

The core developers behind the initial launch of Ethereum were Vitalik Buterin (who would become the leading person for the whole project), Gavin Wood (who later went on to found other successful protocols like Polkadot and Kusama), and Jeffrey Wilcke. 

Where did this name come from?

In a forum discussion in 2014, Vitalik Buterin explained the reasoning of Ethereum’s name “I was browsing a list of elements from science fiction on Wikipedia when I came across the name. I immediately realized that I liked it better than all of the other alternatives that I had seen; I suppose it was the fact that sounded nice and it had the word “ether”, referring to the hypothetical invisible medium that permeates the universe and allows light to travel.”

The name choice wasn’t that casual, as it stood for the mission that Ethereum had as a Blockchain protocol. Become the “gas” or the primary element that fueled transactions of any time on top of its modular, general-purpose Blockchain.

*In simple terms that means a general-purpose computer language.

The $18 million-dollar launch

As Ethereum got into the world as a project, it started its journey as a decentralized organization, busy in building up the key components of the protocol that would lay out the foundation of the work to do in the coming years. 

By January 2014, as Vitalik Buterin got ready to announce the “Ether Sale” which would officially mark the beginning of Ethereum as a cryptocurrency he reminded the cold day in San Francisco, back in November 2013, when he was drafting the White Paper, after months of reflection on what would determine the evolution of the blockchain. 

This phase would be called among the insiders “cryptocurrency 2.0” or the phase in which finally crypto would move beyond the application that Bitcoin had brought around money. In short, it wouldn’t be just about money, as a use case, but rather about applications, decentralized applications, that could potentially be built on top of this new infrastructure.

The journey to get through this realization wasn’t a simple one and as Vitalik Buterin highlighted that was quite frustrating. As Buterin explained in his own words:

“Eventually, I realized that the key to solving the problem once and for all was a simple insight that the field of computer science first conceived in 1935: there is no need to construct a separate infrastructure for each individual feature and implementation; rather, it is possible to create a Turing-complete programming language, and allow everyone to use that language to implement any feature that can be mathematically defined. This is how our computers work, and this is how our web browsers work; and, with Ethereum, this is how our cryptocurrencies can work.”

This would become his approach and strategy in developing the Ethereum protocol. Rather than thinking in simple use cases and potential applications, Vitalik Buterin started to think in terms of a programming language that could accommodate an unlimited number of use cases. 

From there lead code developers Gavin Wood (who would later depart to found two major Blockchain protocols like Polkadot and Kusama) and Jeffrey Wilcke (who later went on to found games development studio, Grid Games) but also other lead developers like Charles Hoskinson (who would, later on, support the hard fork of Ethereum, Ethereum Classic, and in 2016 he also found another successful protocol, Cardano), Anthony Di Iorio and Mihai Alisie (who would serve as vice-president of the Ethereum Foundation until 2015).

In short, the founding team that would bring the core Ethereum protocol to life (and that later on would be the protagonist of the first “Ethereum War”) was formed. 

Vitalik Buterin at the time described Ethereum as “a next-generation cryptographic ledger that intends to support numerous advanced features, including user-issued currencies, smart contracts, decentralized exchange and even what we think is the first proper implementation of decentralized autonomous organizations (DAOs) or companies (DACs)” (those would stick as some of the core use cases for Ethereum). 

Buterin also explained that even though decentralization was the great promise of Ethereum what made it special was “the way that it does this – referring to the various applications. Instead of attempting to specifically support each individual type of functionality as a feature, Ethereum includes a built-in Turing-complete scripting language, which allows you to code the features yourself through a mechanism known as “contracts”.

Indeed, contracts (or smart contracts) would become the killer application for Ethereum. Those contracts represented ‘agents’ running specific pieces of code every time a transaction is sent to it and even more interestingly more advanced versions of these agents would be even able to modify their own code (thus becoming autonomous agents). 

Over the course of the months as Ethereum moved from its White Paper to becoming a real-world project, more and more challenges came to be overcome. From the problems related to the proof of stake algorithm to mining and more. 

Yet the founding team was focused and capable.  

In a post to review the work done on the project just prior to the Ether sale, one of the leaders from the development team, Mihai Alisie, highlighted: 

“The project started as an idea in Vitalik’s mind. Ethereum has now expanded into thousands and thousands of other minds around the world, thanks to this interconnected digital mesh called the Internet. A sea of minds brought together by the idea of a Turing complete general-purpose blockchain is creating, as you’re reading these lines, the Minecraft of blockchain tech.”

One of the key discussions that went on in these months, and that indeed represented the foundation of Ethereum from an organizational point of view, was whether to be a for-profit or not-for-profit organization. And the latter was the conclusion, as Mihai Alisie explained: 

“After researching a number of models and organizations, we arrived at the conclusion that in order to keep the protocol and the software as pure as possible the only real option was to build a non-profit structure with a declared mission to develop, maintain, nurture and explore the potential of this new technology. Motivated not by money but radiant passion for this crazy idea of a free, open, and decentralized world. That’s what make us happy in the end and most importantly what makes us get up and work on this project, proudly saying today we’re building tomorrow.”

Finally, after months of intense work, the day of the sale came, and in a blog post on July 22, 2014, entitled “Launching the Ether Sale*” Vitalik Buterin announced the sale of what would become the major player in the Blockchain space, only behind Bitcoin (even though at the time very few people expected the success of such a project). 

As Vitalik Buterin explained in the same post “First of all, I would like to thank the community, and especially those close to the project who have in many cases abandoned their jobs to dedicate their time to it, for their extreme patience regarding the launch of the ether sale.”

In the blog post Vitalik Buterin laid down the work that had been done in the previous months to get to the sale (that included the development of the first version of the Ethereum protocol). The sale would fix the initial price at “2000 ETH per BTC”  until declining to a final rate of 1337 ETH per BTC and it concluded on September 2.

By the first two weeks from the sale over 50 million ETH had been sold pushing Ethereum among the top eight coins for a market cap for a value of the initial sale of $17.3M USD beating out also the initial sale of Dogecoin (at $15.5M). 

Keeping it open: The first year and the discussion around governance and vision

In a post highlighting the work done in the first year of the Ethereum project, Mihai Alisie, one of the co-founders who would stay on board as vice-president of the Ethereum Foundation until 2015 explained: 

“During the last couple of weeks, I started to think about how far we’ve come and how many things we have accomplished since this project started. From idea to implementation and everything in between, it was (and continues to be) the most intense ride of my life.”

Mihai remembered the early days of the Ethereum project when in the autumn of 2013, Vitalik Buterin had drafted the first version of the Ethereum White Paper, which he had addressed to a few selected ones, among these there was Mihai. 

As Mihai Alisie recalled “Ethereum felt different from anything else he’d sent me before. The same rush I felt when I first understood the implications of Bitcoin was returning, this time with thousands of new multi-dimensional rabbit holes to explore.”

In fact, Mihai together with Vitalik back in 2011, when Bitcoin was just gaining traction, started Bitcoin Magazine, a project that was meant to narrate all the aspects of the Bitcoin ecosystem. By May 2012 the first issue came out. 

From the magazine, Vitalik Buterin started to draft the vision for Ethereum. As the project got set up, along the way, in 2014, the Peter Thiel Foundation awarded $100K fo Vitalik Buterin for his Ehtereum’s project:

Image Source: blog.ethereum.org/2015/03/14/ethereum-the-first-year

This $100K would set the stage for a project worth billions of dollars only a couple of years later and potentially a trillion of dollars in a decade or two. 

The early years: $50 million Ether hack, the hard fork and the Web 3.0

In a blog post on January 2016 entitled “The last Blog Post,” Gavin Wood explained how his departure was going to mark the beginning of a few new projects. And in another article on his personal blog, he asked “So Ethereum is released. How come the dream of an open, transparent, jurisdiction-neutral techno-legal system hasn’t arrived?!”

Finally in an article entitled “Why We Need Web 3.0” of September 2018 (over two years from his departure from Ethereum) Gavin Wood emphasized his vision for the future by also announcing Polkadot: 

“From a user’s point of view, Web 3.0 will look barely different from Web 2.0, at least initially. We’ll see the same display technologies: HTML5, CSS, and so on. On the back-end, technologies like Polkadot — Parity’s inter-chain blockchain protocol — will connect different technological threads into a single economy and “movement.”

Polkadot and Kusama would all become blockchain protocols springing up from the “Ethereum’s war.”

But how did we get there? 

The years from 2014 to 2016 marked the beginning of Ethereum beyond its White Paper. Not just a paper project, but a real-world one, that had shown its capabilities. Yet, the question here still remained on the whole project’s viability. 

The development of the Ethereum Blockchain protocol had continued at full speed and the community grew exponentially. 

Until one of the greatest heists on the Blockchain took place, and that happened right on the Ethereum Blockchain. 

It all happened in the first part of June 2016, when the Ethereum community found a flaw in the DAO’s code. In an article entitled “More Ethereum Attacks: Race-To-Empty is the Real Deal” on June 9, 2016, Peter Vessenes opened by saying  “Chriseth at github casually pointed out a terrible, terrible attack on wallet contracts that I had not considered. If there were a responsible disclosure avenue for ethereum contract developers, I would use it, but there doesn’t seem to be. Not only that, this code has been out and published on github for long enough that I wanted to get the news out there quickly.”  

In short, a flaw in the smart contract’s code enabled potential hackers to exploit the fact that several withdrawals could be done, before the smart contract eventually records the final balance, thus enabling hackers to potentially steal millions of dollars from these smart contracts. This vulnerability not only was now visible for anyone, and up for grabs by hackers, but that posed a threat to the whole existence of Ethereum as a Blockchain. 

Indeed, if one of the core values of Ethereum was security and an “unhackable cryptographed blockchain” how could this be possible in the first place? 

The way the community would answer it would determine not only whether Ethereum survived but also if it could thrive going forward. 

Initially, the bug in the code was undervalued by the community, but as of June 17th, it became clear this was something serious. In a blog post entitled “CRITICAL UPDATE Re: DAO Vulnerability” Vitalik Buterin explained “An attack has been found and exploited in the DAO, and the attacker is currently in the process of draining the ether contained in the DAO into a child DAO. The attack is a recursive calling vulnerability, where an attacker called the “split” function, and then calls the split function recursively inside of the split, thereby collecting ether many times over in a single transaction.”

Therefore, this “split function” was used to withdraw ether out of the smart contract many times over in a single transaction. Similar to a broken cash machine where the robber is able to take the same amount of cash many times while the machine records it only once, the hackers started to take advantage of this vulnerability, thus draining millions of dollars worth of Ethereum’s from the DAO’s smart contracts. 

Indeed, imagine a cash machine that records only a transaction of $100 but while the drawer is closing the robber is able to take many times over banknotes of $100, while the cash machine only records one transaction of $100. This is the extent to which hackers were draining out money from smart contracts. 

From an analysis done by Phil Daian the next day revealed some of these flaws and explained: “this exploit in the DAO is clearly not trivial; the exact programming pattern that made the DAO vulnerable was not only known but fixed by the DAO creators themselves in an earlier intended update to the framework’s code. Ironically, as they were writing their blog posts and claiming victory, the hacker was preparing and deploying an exploit that targeted the same function they had just fixed to drain the DAO of all its funds.”

As it turned out the core bug was part of the language program developed to deal with DAO and smart contracts. In fact, within the language program, Solidity (which was invented by Gavin Wood). 

Gavin Wood, interviewed for the Dutch Blockchain Conference, on June 21, 2016, explained in his own words, what was going on and how to fix this next: 

“What happened so there are a few things to explain about this. The first thing is that the problem isn’t with the Ethereum itself but the problem is with one of these applications, with one of these smart contracts so the smart contracts are not built into Ethereum. Ethereum exists sort of on a lower level and these software run on the higher level so it’s like saying well these websites are broken and it’s not saying the same thing as the Internet’s broken right. So Ethereum is like the Internet it just sort of works but yes one of the websites as it were that the work that sits on if they’re on the on ethereum and broke this website was called the DAO. Now the Dow was envisioned as some sort of mechanism so that people could pay in ether and this either could be used to sponsor projects and if the project’s ended up becoming profitable people would be able to make some of the new profits back and what happened was due to a technical flaw in this the DAO in this piece of software, this website that sits on top of Ethereum someone was able to attack it and to drain about a third of the money that the DAO had managed to collect into a child DAO. So into a kind of an offspring of the same the same sort of thing but an offspring. Now the reality is that the mayor is still sitting there so we know precisely where as we can see in the system there’s a balance it’s big it’s bigger than it should be but there’s a different owner but a different owner and at the moment the owner is unable to withdraw it. So due to safeguards in the DAO it’s at about thirty nine days before the owner can withdraw it and so we have this time in order to determine whether we’re going to do something about it or whether we’re just going to let it go.”

Further asked by the interviewer, if that was terrible as an attack for the whole system’s trustability, Gavin Wood replied: 

“It’s an attack on the DAO. It’s an attack on the on the integrity of the DAO and it’s using the fact that the DAO is a smart contract that nobody can alter how it’s interpreted and if the interpretate if this software is wrong then the interpretation is wrong and people are understandably annoyed and the sound ugly concerned that you know yeah hold on where is this money being going now the question really is what can we do about it “

As the presenter asked “what to do” next, Gavin Wood, made clear to underline he had nothing to do with the DAO and as the interviewer asked Gavin Wood, whether Ethereum would survive that, Gavin Wood remarked an important point about the future of consensus and decision-making underlying Ethereum: 

“The community manages this problem hopefully of how to form governments consensus even in the face of a widespread concern that what happened wasn’t the expectation.”

This passage is critical, as would emphasize something the many people getting to know Blockchain protocols for the first time undervalue. The Blockchain protocol is not just a trustless entity that executes orders automatically. But, it’s also (and this is one of the main points of that) a distributed consensus platform, where important decisions can be taken as a group, rather than single individuals. This is a critical difference also between traditional governance (which is also how major tech players’ companies are run) and the new way of managing blockchain-based companies. 

Yet the Reddit user by the screen name of ydtm explained back at the time “Yes, I realize the OP is a bit harsh. I do think Vitalik is a smart guy. But I also think that tens of millions of dollars almost evaporated here, and I would like to provide a perspective based on language design – which might be somewhat different from what we’ve already heard from Emin Gün Sirer in his post mortem which also appeared recently.” 

Things got very bad when the flaw was found to be draining dozens of millions and it could get even worse. In the meantime, the developer’s community was frantically trying to find various solutions to the problem. Yet, whichever solution was potentially threatening for the network.

At this point, it’s critical to understand that Blockchain-based business models living on these protocols are made of rules expressed in the form of code that can’t be changed so easily. A change in the code could mean either a soft or hard fork. 

And none of these options was a simple one. Forking the blockchain is something that needs to be done carefully and only to reach critical decisions, and this indeed was a survival threat. However, that also opened up the discussion of how blockchain protocols were really immutable. They are not. Indeed, forking enables the underlying rules of a blockchain to be changed. Even though extremely difficult and still based on the consensus of the majority that could be done. 

Among the Ethereum community, the leader, Vitalik Buterin also was extremely preoccupied. In a chat between Vitalik Buterin and Exchanges, recorded on Steemit we can feel Vitalik’s concerns: 

[3:09:03 AM] George Hallam [ETH] : Ping

[3:09:19 AM] Bill Shihara: Pong

[3:09:57 AM] Bill Shihara: Is the reported issue with the DAO real?

[3:10:17 AM] Vitalik Buterin: as far as we can tell yes

[3:10:33 AM] Mike Li: Where can I find the report?

[3:10:54 AM] Vitalik Buterin: https://www.reddit.com/r/ethereum/comments/4oi2ta/i_think_thedao_is_getting_drained_right_now/

[3:10:55 AM] Vitalik Buterin: active thread

[3:11:06 AM] Alex Hanin: https://thedao.slack.com/messages/general/

[3:11:07 AM] Mike Li: Thank you VB

[3:11:19 AM] Vitalik Buterin: possible mitigation strategies are:

[3:11:21 AM] Bill Shihara: Thanks. There is a lot of panic so a clear statement from the DAO and ETH team’s would be extremely helpful. At this point, people are speculating that griff’s account was hacked.

[3:11:29 AM] Vitalik Buterin: 1. seizing any stolen either that goes through exchanges

[3:11:38 AM] Vitalik Buterin: 2. there is one person who will split within 2 hours

A few minutes later in the conversation, Vitalik Buterin said: 

[3:43:01 AM] Vitalik Buterin: ok can you guys stop trading

Asking exchanges to stop trading was a huge deal, as it also meant other legitimate people couldn’t freely trade Ethereum. Thus, this signals perfectly the concern Vitalik Buterin had at the time. 

To make things even worse, on June 18th 2016, on “An Open Letter” a guest claimed to be the attacker (this might have only been an attempt to distract the Ethereum’s community), and  explained: 

“I have carefully examined the code of The DAO and decided to participate after finding the feature where splitting is rewarded with additional ether. I have made use of this feature and have rightfully claimed 3,641,694 ether, and would like to thank the DAO for this reward. It is my understanding that the DAO code contains this feature to promote decentralization and encourage the creation of “child DAOs”.

And at the end of it he went on: 

“A soft or hard fork would amount to seizure of my legitimate and rightful ether, claimed legally through the terms of a smart contract. Such fork would permanently and irrevocably ruin all confidence in not only Ethereum but also the in the field of smart contracts and blockchain technology. Many large Ethereum holders will dump their ether, and developers, researchers, and companies will leave Ethereum. Make no mistake: any fork, soft or hard, will further damage Ethereum and destroy its reputation and appeal.

I reserve all rights to take any and all legal action against any accomplices of illegitimate theft, freezing, or seizure of my legitimate ether, and am actively working with my law firm. Those accomplices will be receiving Cease and Desist notices in the mail shortly.

I hope this event becomes an valuable learning experience for the Ethereum community and wish you all the best of luck.

Yours truly,

The Attacker”

Hard-forking the protocol to win the war

It had become clear by that point that this was a war, a “DAO War.” On June 24, 2016, on a blog post entitled “DAO Wars: Your voice on the soft-fork dilemma”  Péter Szilágyi, from Ethereum’s core development team (that had been frantically trying to solve this major flaw in the last weeks), explained: 

“The last week was quite hectic for all of us in the Ethereum ecosystem. The DAO has shown us that it takes much more effort to write smart contracts than we originally anticipated; but also that it takes a surprising amount of debate to reach a consensus on issues of this scale.”

One thing that strikes quickly from this event, is now going through this survival threat, there was no single person in charge. Sure, the community still relied a lot on Vitalik Buterin’s ability to respond to this. Yet the decision on how to end this over was in the hands of the developer’s community and even there, the developer’s community alone wasn’t the only stakeholder. In order to align the whole ecosystem, any decision needed to be debated over and made publicly available, to enable people using, exchanging, or building applications on top of Ethereum to understand what was happening there. 

This event is at the heart of what it means to do business on a Blockchain. 

As Vitalik Buterin went on aligning the community around the two courses of actions possible (soft-fork which would have been less invasive of the protocol, and hard-fork) as he emphasized in the same “as there is no clear, best course of action that will satisfy all community members equally, we’ve decided to give the power to the people running Ethereum to decide whether they support this decision or not.”

Vitalik Buterin also explained the consequences going forward, “miners who do not update by definition vote against the soft-fork as they will continue the current logic of keeping the gas limit above the vote threshold. If the soft-fork is accepted by the majority, non-updating miners will still accept blocked transactions. In that case, non-updating miners will either fork off their own Ethereum network, diverging from the majority, or will forfeit any blocks they mined (since it’s not accepted by the majority, overruling the minority blocks)” 

And as an epilogue “This release implements a soft-fork. A soft-fork is perfectly compatible with all protocol rules and requires only the consensus of the majority of miners to enact. It is temporary and can be removed/amended at any point in time upon miner consensus. It does not break protocol rules; it does not roll back any executed transactions/blocks; and it does change not any blockchain state outside of the original protocol capabilities.”

As time went by, the dilemma on how to permanently fix the issue was highlighted in the blog post “To fork or not to fork” on July 15, 2016, Ethereum’s core developer Jeffrey Wilcke explained “The DAO, though not a product developed by the Ethereum Foundation, has been a hot topic as of late, both internally in the organisation as well as within our community. The Hard Fork is a delicate topic and the way we see it, no decision is the right one. As this is not a decision that can be made by the foundation or any other single entity, we again turn towards the community to assess its wishes in order to provide the most appropriate protocol change.”

By July 20, 2016, the hard fork had been completed. This time Vitalik Buterin took the lead in explaining the process. As Ethereum’s blockchain moved toward block 1920000 (the one that would execute the hard fork) we can only imagine Buterin’s state of mind. As the process completed Buterin acclaimed “we would like to congratulate the Ethereum community on a successfully completed hard fork. Block 1920000 contained the execution of an irregular state change which transferred ~12 million ETH from the “Dark DAO” and “Whitehat DAO” contracts into the WithdrawDAO recovery contract. The fork itself took place smoothly, with roughly 85% of miners mining on the fork.”

This is what the hard fork looked like in practice. This simple move in codes determined hundreds of millions to move to the new fork in a few seconds. 

Image Credit: blog.ethereum.org/2016/07/20/hard-fork-completed

Vitalik Buterin closed the post by highlighting “we thank our developers and the community for working together to make the transition as smooth as it has been, and look forward to working together to continue to make the Ethereum ecosystem and protocol a success.”

In a final post “Onward from the Hard Fork” Vitalik Buterin explained “The foundation has committed to support the community consensus on the admittedly difficult hard fork decision. Seeing the results of various metrics, including carbonvote, dapp and ecosystem infrastructure adoption, this means that we will focus our resources and attention on the chain which is now called ETH (ie. the fork chain). That said, we recognize that the Ethereum code can be used to instantiate other blockchains with the same consensus rules, including testnets, consortium and private chains, clones and spinoffs, and have never been opposed to such instantiations.”

Therefore, going forward two Ethereum protocols would come out from this hard fork. The new ETH, which would be rebranded as the “official” Ethereum protocol, contained the altered history (by removing the hacked tokens) and the old Ethereum protocol, named now ETC, or Ethereum Classic that contained the unaltered history (together with the theft of millions of dollars). 

Thus, the hard-forked Ethereum protocol would continue its existence afresh, with a very hard-learned lesson, dozens of million dollars missing, and yet a community that had responded with maximum support. 

And all of this paradoxically highlighted one of blockchain’s most important promises, the unknowability of the holder. 

Everyone knows the address:

0xF35e2cC8E6523d683eD44870f5B7cC785051a77D 

Misplaced millions of ethers, and yet none knows who that is (having passed on the Ethereum Classic blockchain we don’t know for sure whether these tokens were eventually sold and to whom). Just like Satoshi Nakamoto remained a mystery after years from the Bitcoin’s White Paper (together with a pool of 1.1 million Bitcoins worth billions). So Ethereum’s stolen token was never traced back. 

Solving for Scale: Making Ethereum from 100x to 1000x more efficient

When Ethereum was first created as a project, the first question that popped to mind to investors was whether it would become a viable project. However, as it showed it was viable (and it survived the “DAO War”), the next question was about scalability. Indeed, as more and more applications (dApps) got built on top of the Ethereum blockchain, its fees to execute transactions got higher and higher. 

In part, these “gas fees” have helped as a disincentive to the system to execute transactions or applications that might be less relevant to the whole ecosystem. Yet, in the long run, the Ethereum ecosystem depends upon its ability to accommodate as many use cases as possible. 

This poses a major challenge, which is scalability. How does Ethereum tackle that? In two main ways. 

Layer 1 Scaling: Getting 100x Better

In layer 1 scaling the underneath Ethereum-based Blockchain, the protocol is made more efficient, thus enabling 10 to 100x growth of the ecosystem. 

Core examples of Layer 1 scaling comprise proof of stake and sharding. Indeed, as Ethereum rolls out what’s now called Eth2 (the upgrades that will make the whole protocol more scalable), eventually, as and if the roll-out comes out successfully, Eth2 will merge into Ethereum, thus becoming a more effective whole. 

It’s important to highlight that Ethereum started primarily as a proof of work-based protocol (like Bitcoin). While this delivered the project’s viability; as Ethereum grew to support new use cases like decentralized finance and decentralized applications a new consensus algorithm needed to be introduced. That is why Ethereum started to move toward proof of stake and sharding (these changes will be coordinated by the Beacon Chain). 

As Vitalik Buterin highlighted in “Why sharding is great: demystifying the technical properties” “sharding is the future of Ethereum scalability, and it will be key to helping the ecosystem support many thousands of transactions per second and allowing large portions of the world to regularly use the platform at an affordable cost. However, it is also one of the more misunderstood concepts in the Ethereum ecosystem and in blockchain ecosystems more broadly. It refers to a very specific set of ideas with very specific properties, but it often gets conflated with techniques that have very different and often much weaker security properties. The purpose of this post will be to explain exactly what specific properties sharding provides, how it differs from other technologies that are not sharding, and what sacrifices a sharded system has to make to achieve these properties.”

He also explained that when it comes to Blockchain protocols the Scalability Trilemma (or the ability to keep the public blockchain scalable, decentralized, and secure) can be achieved via more complex mechanisms like sharding*.   

As Vitalik Buterin highlighted “a sharded blockchain is:

• Scalable: it can process far more transactions than a single node

• Decentralized: it can survive entirely on consumer laptops, with no dependency on “supernodes” whatsoever

• Secure: an attacker can’t target a small part of the system with a small amount of resources; they can only try to dominate and attack the whole thing”

Blockchain companies use sharding to partition databases and increase scalability, allowing them to process more transactions per second. Sharding is a key mechanism underneath the Ethereum Blockchain and one of its critical components. Indeed, sharding enables Blockchain protocols to overcome the Scalability Trilemma (as a Blockchain grows, it stays scalable, secure, and decentralized).

The Scalability Trilemma (Image Credit: vitalik.ca). 

Layer 2 Scaling: Getting 1000x Better

When it comes to layer 2 scaling, this has the potential to make the whole ecosystem much more effective. This consists of enabling smarter protocols on top of the main Ethereum protocol. Thus expanding exponentially the capabilities and use cases available on the main protocol. A very basic example of layer 2 scaling are payment channels which “allow for practically unlimited, bidirectional transfers between two participants, as long as the net sum of their transfers does not exceed the deposited tokens.” 

As Vitalik Buterin explained “This technique – referring to payment channels – is powerful: it can be adjusted to handle bidirectional payments, smart contract relationships (eg. Alice and Bob making a financial contract inside the channel), and composition (if Alice and Bob have an open channel and so do Bob and Charlie, Alice can trustlessly interact with Charlie). But there are limits to what channels can do. Channels cannot be used to send funds off-chain to people who are not yet participants. Channels cannot be used to represent objects that do not have a clear logical owner (eg. Uniswap). And channels, especially if used to do things more complex than simple recurring payments, require a large amount of capital to be locked up.”

However, the main problem with these schemes is the fact that transactions are pushed off-chain (where the value is moved outside the blockchain), which can pose security risks, thus comprising the whole purpose of the blockchain. 

However, for Vitalik Buterin, one of the most exciting examples of layer 2 scaling are the so-called “roll-ups.” As an example, let’s consider the case of optimistic rollups, which “use a side chain that sits in parallel to the main Ethereum chain. They can offer improvements in scalability because they don’t do any computation by default. Instead, after a transaction they propose the new state to mainnet. Or “notarise” the transaction.” 

This is critical because roll-ups will reduce the congestion on top of the main blockchain, as they take place on a “sidechain” thus potentially reaching a transaction speed of 2,000-3000 per second.

Therefore, all these transactions would be processed through the rollups on the sidechain and the reports on top of layer 1, or the main Ethereum’s blockchain, de facto increasing speed, and reducing gas fees. 

And the key advantage is that these transactions would still be on-chain. This passage is critical to understand as Vitalik Buterin himself highlights: 

*“The fact that data is on-chain is key. Putting data on-chain and having consensus on that fact allows anyone to locally process all the operations in the rollup if they wish to, allowing them to detect fraud, initiate withdrawals, or personally start producing transaction batches. The lack of data availability issues means that a malicious or offline operator can do even less harm (eg. they cannot cause a 1 week delay), opening up a much larger design space for who has the right to publish batches and making rollups vastly easier to reason about. And most importantly, the lack of data availability issues means that there is no longer any need to map assets to owners, leading to the key reason why the Ethereum community is so much more excited about rollups than previous forms of layer 2 scaling: rollups are fully general-purpose, and one can even run an EVM inside a rollup, allowing existing Ethereum applications to migrate to rollups with almost no need to write any new code.”*

Toward Ethereum 2.0, Staking, Sharding, Proof of Stake* and Scaling

As a quick recap so far, Ethereum was born in 2014 out of Vitalik Buterin’s White Paper, and the core development team has been extremely successful since the start. By 2016 a critical flaw in the DAO smart contract made it possible for hackers to steal millions of dollars worth of Ethereum, thus posing a serious threat to its survival. The solution to it was a hard-fork, to which most of the Ethereum community joined in and that determined the split of the protocol. From there two protocols were formed, Ethereum Classic (ETC) Containing the unaltered history of the protocol (comprising the stolen tokens) and ETH, which would be rebranded as Ethereum, which contained the altered history (the protocol from which the stolen tokens had been removed). 

As Ethereum showed its viability, it started to scale quickly and by 2017 it also showed its potential. However, a problem of scalability arose, especially in light of massive “gas fees” (the fees to process transactions on top of Ethereum’s Blockchain). To solve this problem, Ethereum started to move toward Eth2 – scheduled between 2022-2024 – which once successfully rolled out would be rebranded as Ethereum. This upgraded protocol will primarily address scaling through two layers. With Layer 1 Scaling, the main protocol might get potentially 100x more efficient. 

This will consist of integrating new mechanisms such as proof of stake, and sharding. In the process, Ethereum holders can also stake their coins (those would be locked into the blockchain until the transition to Eth2 has been completed) and earn interest as a result of that. Layer 2 Scaling instead will consist of integrating mechanisms such as roll-ups that might make the whole blockchain 1000x more efficient, by enabling transactions to be processed at scale on sidechains, that can be reconducted back to the main protocol (thus still be on-chain and therefore secure). 

Read Also:

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Life is determined by a few key moments. That was the case when in 2016, Masa Son met Adam Neumann in the WeWork offices. Masa had only twelve minutes to decide whether to place a $4 billion bet on WeWork! With the usual coolness, Adam Neumann - a tall guy that felt ok in walking barefoot without a shirt in the middle of the street - played his cards at best. A few minutes later, Masa Son, among the wealthiest people in Japan, scribbled $4 billion on his iPad. That made Adam's company, WeWork, valued at $47 billion!

Masa and Adam would project WeWork to be valued at $10 trillion by 2028! Yet the wind was going to change very quickly. And just two years later, the whole thing was to implode.

From the height of a $47 billion valuation, the company risked losing it all!

This isn’t a movie by Oliver Stone, who wrote the legendary Wall Street, interpreted by Michael Douglas, in 1987, and which would paradoxically inspire generations of financiers. We’re, at this time, into WeWork’s offices, a real estate company claiming to be among the largest tech players, running what the company called a Space-As-A-Service Business Model. This story is so exciting that Apple TV+ is making a series about it, interpreted by Jared Leto.

When I interviewed Eliot Brown, a reporter at Wall Street journal since 2010, he had been following WeWork’s founder rise for a few years. Eventually, the story got so compelling that when WeWork crashed, Eliot wrote a book about it called “The Cult of We.” Founded in 2010, in SoHo, NYC, by Adam Neumann and Miguel McKelvey, WeWork quickly expanded. By 2012, WeWork was a successful and profitable company that was now worth over a hundred million in a very short time.

2016 would be a turning year for WeWork as it managed to get a $4 billion offer after a 12 minutes tour of the offices, Masa Son, founder of SoftBank. Masa Son would later promise to take over the company for $20 billion and make it into a $10 trillion behemoth by 2028!

Things didn't turn out as expected. Masa Son pulls back from its promised investment as liquidity drains out. WeWork, therefore, tries to IPO to getting the funding it needs to survive. Yet, as it submits its S-1 form to the SEC, the whole scandal comes out, as a conflict of interests, bad management, and extreme losses become public! WeWork would have to withdraw its IPO.

As the company restructured, it went public via a SPAC company BowX, valuing it at $9 billion (instead of the $47 billion of value at its peak). By March 2022, WeWork is valued at less than $4 billion.

What happened there? Let’s look at one of the craziest stories of the tech industry, which might well resemble the epitome of what can go wrong when markets are supplied with massive liquidity and private investors are looking for the next big thing!

As Eliot Brown explained to me, Adam Neumann's entrepreneurial story started when he moved back to Israel with his mother, where he lived most of his life, before adulthood. In Israel, he lived in a Kibbutz, a communal socialist experiment. There, he learned the value of community. He also learned how the place was a mess as it was hard to make the community keep going without the financial resources. After a short stint in the Navy in Israel, he moved to New York.

In the city, he found the perfect place for him to bloom. He just wanted to become rich, and with his sister already in New York, working as a supermodel, he was right on introduced to interesting people. Adam was quite energetic, a natural extrovert; he found it very easy to make friends and build communities just for having fun.

His first venture as an entrepreneur was a baby clothes company (mainly financed with his sister’s money), which tried to make clothing that had knee pads for babies when they were crawling. It was called “Krawlers.”

The idea was that babies’ knees must hurt, so here’s a way to make it, so they don’t and didn’t go very well. Yet Adam was a great salesman. However, his inability to understand the product and his lack of passion about it (he was a man in his 20s) made the business continuously struggle.

The real turn of events came when he met someone who ran an office space subleasing company, a little incubator-type environment called Sunshine Suites. It was the son of a classmate of his at college. Adam felt impressed by how much money Sunshine Suites was making. In the meantime, Adam had met an architect, which turned into a good friend named Miguel McKelvey. Adam Neumann pitched the idea to do something similar to Miguel McKelvey, who became the co-founder of something very similar to what would later become WeWork.

Back in Brooklyn, they convinced their landlord to give them a floor and put up the money to organize a first co-working space. The landlord put in the money, and real estate and Adam and McKelvey put in sweat equity. The deal worked pretty well! Soon enough, the company, which they called Green Desk, was a success. We’re in the 2010s.

When Adam Neumann saw the idea was working well, he figured to turn it into something way bigger. Yet the landlord didn’t seem to agree. Thus, he liquidated the two co-founders and gave them about $500K each.

Adam Neumann recommended McKelvey to keep his money as he would have spent it, so that they could use it for their next venture.

Finally, as the vision was shaping into Neumann’s mind, he wanted to build something big, a multi-billion dollar business.

He also understood that to do so; he had to play the venture capital game. And as it would later turn out, he was very good at it.

But before we get to that, Adam Neumann, in the meantime, had also met what would become later on his wife: Rebekah Paltrow, causing with the actress Gwyneth Paltrow.

At the first encounter, Rebekah Paltrow tried to inspire Neumann to think big, but also to do so with vision, and not to only think about money. While this might seem inspiring, as we would see throughout the story, it also turned into one of the paradoxes of the whole WeWork story, in what we can call “fake leadership.”

Fast forward, WeWork is indeed a good idea. That’s a sort of real estate arbitrage, where you leverage on a longer-term lease to rent the real estate locations at a much higher price to co-working companies by offering them ancillary services.

This model is well known today, yet pretty new in the 2010s. However, while this business model turned out to be profitable at the time (we’re right after one of the greatest real estate bubbles of our times), when commercial real estate was under pressure, it was still a business that was very hard to scale.

The primary reason was that WeWork had to anticipate the costs related to long-term leases and pay them out slowly as more members came in. While over time this model would make sense, in the short-term this form of arbitrage also carried negative cash flows.

Yet, we’re in a period when private markets were heating up, and venture capital was massively betting on tech companies. Adam Neumann, therefore, realized the importance of reframing WeWork as a tech company rather than a real estate player.

Indeed, over the years, WeWork called itself a Space-as-a-Service business model. This was done to mimic the successful and rising industry of software companies offering their technology for a monthly fee (the Software-as-a-Service).

The move was successful, as WeWork quickly convinced venture capitalists to invest. Among the first, there was Benchmark, a well-known name in Silicon Valley. They were the first big check into Uber.

This created an aura of success, it validated WeWork as a tech company, and it made it into a multi-million dollar success. And the road to billions wasn’t that far!

One of the most hilarious scenes of the series Silicon Valley (above) well explains in a hot market what makes a company successful. It’s not the revenues. It’s the hype you can create, but also how much you can shift your narrative around growth rather than profitability. That is what WeWork did. Adam Neumann, at that point (we’re around 2014-2015) had mastered the venture capital game. And he started to secure other financing deals.

The real breakthrough came when they managed to pull in a mutual fund, Fidelity. A growth fund part of the Fidelity family gave WeWork an over $200 million cheque, making the company valued over $10 billion for the first time.

Fidelity at the time was pulled into WeWork as it was trying to show it could invest in innovative companies, and for the mutual fund, a cheque of over $200 million was a small thing compared to the hundreds of billions it had under management.

While WeWork grew to become what is called a Decacorn, yet, as WeWork was growing by surfing venture capital investments, Adam Neumann was taking money off the table by selling some of his shares to finance his lifestyle.

At the same time, he was also opening personal loaning lines to keep the extravagant lifestyle the family was living. On the one hand, he preached to his team to work hard and do it for the mission; on the other hand, he was taking money off the table where he could to finance his lifestyle. To be sure, there is nothing bad about taking money off the table, especially if you’re letting some of your early employees, and the people that made the company successful do the same.

Instead, he was taking favorable deals for himself, and that’s it. And there is more to it.

As WeWork was growing, a plethora of conflicts of interest started to build up. In fact, Adam Neumann, on a growing number of deals, would, on the one side, invest in the property behind the commercial building. And on the other hand, manage the company as WeWork’s CEO. For a company that was now worth more than $10 billion this was a matter of concern. And yet, as the company scaled, things only got worse.

The money that Neumann would take from the various financing rounds, were also used to do acquisitions that didn’t make any sense. The epitome of it was the acquisition of a company called Wavegarden, which actually made artificial waves for surfing!

The real turning point for Neumann (or, if you wish, the beginning of the end) and WeWork came when he encountered Masa Son, the patron of SoftBank, a Japanese conglomerate, who had billions of dollars at its disposal. Masa Son’s career is quite interesting. In fact, he managed to become among the wealthiest person in the world, during the dot-com bubble, only to see his wealth to evaporate.

Even though he failed with the dot-com bubble he still managed to build an aura of success thanks to a huge winner. Indeed, Masa Son had invested $20 million in the early days of Alibaba, turning it into a multi-billion win!

The approach he used was gut instinct in spotting a visionary founder. Thus, it was this ability (as he later recalled) to spot a visionary like Jack Ma (founder of Alibaba) that made the investment so successful (according to Masa Son).

As Masa Son recounted, referring to Jack Ma (I edited the text for readability):

He had no business plan, and zero revenues, but his eyes were strong, strong eyes, shiny eyes, I could tell from the way he talked, he had charisma, leadership. So his business model was wrong, but the way he talked, and he could bring young Chinese people following him.

Masa Son, after the dot-com crash, had started to rebuild his business by investing in the communication industry, until he tried to merge Sprint and T-Mobile, and failed. Yet, when Masa Son's real mission was to find the next visionary. When he met Neumann he had successfully built one of the largest funds ever created, for tech companies. The Vision fund, in fact, had secured over $45 billion from Prince Salman (King of Saudi Arabia). With that money, Masa Son was ready to invest in the next tech messiah, able to change the world.

Here we go back to the day Masa Son had scribbled the $4 billion investment on his iPad. That made Adam's company, WeWork, valued at $47 billion!

Yet the story wasn’t over yet.

Masa Son became the main mentor of Adam Neumann, at the point that the two met to discuss the final vision for WeWork, making it into a multi-trillion-dollar success! Indeed, as Son and Neumann met, in 2018 Son had promised Neumann to buy out WeWork, make it a private company, and bring it to become a $10 trillion company by 2028.

That was the grandiose/mad vision!

Yet, as the deal was about to close, things changed pretty rapidly. As market liquidity started to drain up, pressure mounted on the Vision Fund, and Masa Son called the deal was off the table. This made Neumann go in the path of one of the most unsuccessful IPO attempts. As the window of opportunity to IPO was closing, WeWork tried to go public in 2019. Yet, as the WeWork S-1 was released the public was shocked to see a company bearing massive losses, and with no plan whatsoever to turn a profit any time soon. And to make things worse, all of Neumann’s conflicts of interests started to be made public, until the situation became unsustainable, and after various theatrical moves, Adam Neumann was ousted, yet he left the company with one of the most generous, severance packages of all time.

At the time of this writing, WeWork, which would later IPO through a SPAC, is now worth less than $4 billion. The once envisioned multi-trillion success turned into a nightmare.

The overall company survived all that, showing that overall, WeWork wasn’t a bad idea. But of course, neither is a tech company that could be worth more than Apple, Amazon, and Google combined.

Listen to the full Podcast Episode.