Posts

I used to have a clear answer to a founder’s question, “How do you value a company?” The question is just as important in conversations within a VC partnership as with founders. A valuation must have some justification to be compelling.

Reflecting on this question a founder posed this week, I remembered how we came to be here, the three eras of startup pricing: cash-flow, multiples, and discount-to-future-value.

Cash Flow
In the aftermath of the dotcom crash, a valuation depression kept valuations low. A few months before Lehman fell, I joined Redpoint. I was taught to ask founders how much capital they needed to attain milestones and circumspect the financial model. How much money did the company need to have 18-24 months of runway? The model says $4m? Great.

Imagine you’re a venture investor. You find a great company. You buy 16% of the company for $8m at $50m post-money valuation. Six months later, the company raises $100m at $500m. Things have gone very well.

Your 8m has 10xed. Naturally, you ride an imaginary horse around the room, galloping with glee.

Now you face an important strategic question: Do you invest your full pro-rata of $16m? Pro-rata is the right to invest more to maintain their percentage ownership. Venture firms reserve capital for these financings.

Defi lending protocols, distributed exchange protocols, cross-chain messaging protocols, communication protocols. All of them are in the process of being invented, debated, and adopted.

In a roundabout way, this post is about the emergence of web3 protocols. But it’s about how we got here.

For 20 years, from 1970 to 1990s, the first Protocol Wars raged over clacking IBM Model M mechanical keyboards.

At the time, computers were connected by local networks. Stanford operated a computer network. DARPA and University College London also. But these networks couldn’t talk to each other in a standardized way - paralleling the limited interoperability of blockchains today.

Revenue, Revenue_USD, Revenue_new, rev2, customer_revenue. Do you recognize these? They might be the column names you might find in your BI or analytics tool. Which is the one to use?

You pick Revenue_new (it’s new, after all!) and proceed with your analysis. A few minutes into the meeting with the sales team, the group startles: the data doesn’t match their expectations.

Something’s wrong.

What data are you using?! Revenue_new? Oh, Revenue_new is the old column. The company moved to customer_revenue last quarter when we hired a new VP of Finance and they updated the definition.

Traditional software was initially sold by perpetual license. Then in the mid-00s with the advent of SaaS, the market shifted to per seat per year pricing. And simultaneously, freemium marketing strategies blossomed. Freemium companies provide software for free temporarily to entice users to try and use the product. Eventually, these users cross a threshold and convert to a paid subscriber. This threshold can be based on number of people using the product (Expensify), number of documents signed in a month (HelloSign), or additional product features needed by users (Yammer).

As I’ve explored web3 I’ve been forming a mental model of the major innovations powering this enormous wave of innovation. At the moment, I see four clusters:

1. A permanent ownership record that exists beyond and outside a company. The photos I take, the movies I buy, the music I rent, the emails I write and receive, the messages I send - all of these are captive. They exist within a database controlled by Google, Netflix, Spotify, Gmail, WhatsApp. If these services disappear, so does my ownership/rentership record. In a future where digital assets are worth not $10 or $20, but hundreds or thousands of dollars, ownership that survives a company becomes an essential substrate of commerce.
2. Paying customers in “equity.” Internet hegemons have decimated entire spaces: social networks, advertising technology, video streaming and rental, paid email, infrastructure. Their economies of scale and network effects mount significant barriers to competition. What’s a startup to do? Compete on a different axis: reward users with tokens. A social network rewards its most valuable users in the coin of the realm. Same for music or file storage or graphics processing. As the network becomes more valuable, so does the user’s stake in the company. Web3 companies employ tokens to reward their customers for providing value. Because this technique is so new, startups have the upper hand: Innovator’s Dilemma redux.
3. Regulatory arbitrage. Twenty years ago, startups IPOed after 4 years. Today, it’s 12, driven by several factors but regulatory costs present the principal one. Crypto companies access pools of capital web2 companies cannot because the regulation doesn’t exist. Where nascent rules are present, the regulation isn’t yet a warren of legalese- yet. Within this freedom to maneuver, Defi protocols invent new financial instruments. The perp, a perpetual swap, has become the most traded crypto derivative). Perps don’t exist outside crypto.
4. DAO/Foundations: open-source software is arguably the most important motive force powering innovation in technology. Open-source software powers every server and most software. Crypto empowers open-source projects to monetize their innovation in a way web2 never achieved. DAOs bind the loose community of open-source software contributors through tokens. Tokens provide an ongoing financial link that aligns long-term incentives. Foundations endowed with significant token stakes fuel the ongoing protocol development, balancing the capitalism needed to fuel progress with the benevolence intrinsic to the open-source ethos.

But, wait. There’s one more!

There are roughly 27m software developers in the world. Only about 18k of them, or 0.07%, work on crypto or web3 every month.

Those 18,000 active engineers have created $2 trillion in market cap across the top 100 projects - $112m of value per person.

With such massive potential impact, why are there so few engineers working on web3?

Crypto is young. Crypto is volatile. Crypto requires learning new languages.

Every quarter, RedMonk publishes a chart of the most popular developer languages. The two most popular languages for authoring smart contracts are Solidity for Ethereum and Rust for Solana and Cosmos, circled in red.

Before a startup is founded, no stock exists. By the time it’s public, more than 100m shares exist across hundreds of shareholders (employees, institutional investors, retail investors). Through its life, the company might buy back some shares, destroying them and reducing share count.

The startup can inflate share count by creating shares. Conversely, the company can deflate share count by buying shares and destroying them. Over the life of a company, share count can vary significantly.

Could Instacart’s self-repricing become the first of many? It’s quite possible. The company announced it would mark its shares to a market price 40% less the last round.

In a fundraising environment awash with capital and term sheets lapping up on the front doors of many startups, why might we see more self-repricings?

Talent. Startups appeal to candidates span many dimensions: influence, category creation, smaller teams. But lottery-ticket upside remains one of the most important. Join the right company and it will change your economic life.

What’s the price of spice? If you’ve never seen a data app, that’s the question you should be asking yourself. Data apps are living documents that weave narratives around data and charts to explain, persuade, or empower.

Imagine your future self. You work for a large company selling spices and you’re tasked with exploring the impact of pricing changes. Most importantly, you’ll present the results to executives who will no doubt pepper you with questions about what-ifs.