While I did want to offer life lessons and every startup founder can be forgiven some level of humblebrag content marketing, there was definitely a voice in the back of my head at the time, persistently whispering: “How can we monetize this down the road?” and “This might go viral if we focus on the Quiet Quitting CEO angle”

Luckily, I came to my senses within a few newsletter editions, spurred by my innate fear of self-imposed publication deadlines. But it’s also because I am doing much better in my day job that I was at that time, so the need/desire to think about side hustles has gone away.

For the first time as a founder, I can say with confidence that we will succeed if things go as expected, rather than if they happen to break our way. The monetization voice, along with his cousin who’s always trying to get me to chase random startup ideas, are now mostly dormant. It’s actually weird feeling for me.

Therefore, my posts will hereby have no fucks given. Here are some cat memecoins:

Also, here’s a video that tries to explain how I finally found that balance in my day job:

Honestly, I wasn’t really sure, so I bought the biography of Elon by Walter Isaacson that recently came out.

700 pages later, I can confirm that he is indeed a gigantic asshole, but also a fascinating and complex one. The reaction video above provides a more nuanced take.

Watch on YouTube:

About this book

I picked up Billion Dollar Whale upon my friend Jesse’s recommendation, and also because I remembered going to the naked-girl sushi party mentioned in it.

The book turned out to be a minutely-researched tale and rollicking tale of a $5 billion bank heist using the machinery of modern-day finance. Basically, it answers the question: “What happens if you spent an ungodly amount of money that you don’t really have?”

Watch Review

Programming note

When I started this newsletter, I envisioned it turning into a proper side hustle, something that would generate income outside my day job.

A year of sporadic entries later, I’ve learned that:

1. I am very lazy.

2. I enjoy doing my day job more than any other job I’ve ever held.

Therefore, I decided if that I’m going to do something to make money, it should be doing more things related my day job. So if I’m going to spend time to create content, it should be purely for fun.

That’s why future entries will look more like the one above - off the cuff venting about random topics tangentially related to founder life. Thankfully, I think this is a topic that is filled with juicy nuggets of truth that I can unearth.

Plus, these videos will be a chance for me to play proud dad and showcase my daughter’s incredible video editing skills!

Watch on Youtube:

Content Mentioned

• The WEIRDest People in the World

• Indie Hackers Podcast

If there’s anything I’ve learned over the past two weeks, it’s to trust nothing and verify everything.

That’s why I was intrigued when I stumbled upon a tweet referencing a time when SBF described how Tether’s creation/redemption process worked.

Since I had just read about Tether’s associations with Celsius the day before, my spidey sense started tingling.

What is SBF’s Achilles heel?

The fat clown can’t shut up. He always says the quiet part out loud.

I knew there had to be some juicy nuggets in that interview, so I re-listened to it closely. I couldn’t believe what I found, so I felt like I had an obligation to share it publicly.

Watch the video here on Substack or on Youtube below:

If you want to dig deeper, Patrick McKenzie has an excellent article on Tether with a lot more detail and proper research.

References

Overcast.fm: Odd Lots Podcast with Sam Bankman-Fried

Tether: The Story So Far

Bitfinex April 2019 affidavit

Stablecoin Mechanics 2: Tether-Celsius

As for many of people in our industry, the FTX debacle has made me think about why I got into crypto in the first place, and why I’ll always be here.

Here’s the start of my answer.

I’ve started to formulate a theory called Digital Markets Theory. It’s still half-baked, but with your help, hopefully I can formulate it into a coherent explanation for crypto’s value proposition.

This will be the first video in a series. Watch here or on Youtube:

References

Tulips, Myths, and Cryptocurrencies

A Story of Two Crashes

It looks like Sam Bankman-Fried (SBF) co-opted FTX customer deposits and secretly lent them to rescue his market making firm Alameda Research in exchange for FTT collateral, sometime after the LUNA crash in May.

But why did Alameda Research need rescuing at all?

The market believed that Alameda was a money-printing machine that should have been able to weather the LUNA storm:

And more interestingly, why couldn’t SBF just Alameda Research die?

To a fawning Sequoia Capital, SBF said he wanted to make FTX the world’s dominant financial super-app:

“I want FTX to be a place where you can do anything you want with your next dollar. You can buy bitcoin. You can send money in whatever currency to any friend anywhere in the world. You can buy a banana. You can do anything you want with your money from inside FTX.”

The logical decision would have been to let Alameda perish and focus on building FTX.

Why did SBF risk everything to save Alameda?

Well, I think I might know.

I don’t have access to any confidential information, but CoinAlpha and Alameda Research both started in the Bay Area in 2017 amidst a close-knit community of nascent quant crypto funds, and I’ve chatted with Sam about how his firm is structured.

And since Hummingbot is the most widely used open source market making tool in crypto, many projects have asked me for advice around hiring market makers, so I’m quite familiar with Alameda and their business model. Also, FTX is one of Hummingbot’s most popular exchange connectors, so I’ve talked to both individual and professional users who run bots there.

Unfortunately, that didn’t prevent me from bamboozled by SBF’s engineering mindset, work ethic and all the social proofs around him. I’m a SRM bag-holder and was so confident that it was all just FUD that I bought even more SRM the morning of Tuesday November 8, right before it all went down.

But what pisses me off the most is that whenever my non-crypto friends and family asked me which crypto exchange they should use, I recommended FTX and FTX.us. They trusted me to help them navigate the dark, shadowy world of crypto, and I funneled them to a slaughterhouse.

I was too consumed with Hummingbot to pay attention, but in the last week, I finally looked at the facts which came out and triangulated them against what I know about Alameda Research’s business

In hindsight, the red flags should have been obvious. I think I finally understand how it all worked, so I put together a video to explain my theory.

Watch it here on Substack or via YouTube:

Let me know what you think in the comments below.

Links referenced

How Sam Bankman-Fried’s Crypto Empire Collapsed

Vampire Mining and the SushiSwap Saga

ChefNomi's Github page

The Man Who Saved SushiSwap

Alameda Research investments

Market Maker Models

FTX CEO leads $580m Series B round in Anthropic

FTX fee schedule

Sam Bankman-Fried Has a Savior Complex—And Maybe You Should Too

Sam Bankman-Fried Described Yield Farming and Left Matt Levine Stunned

Tweets referenced

A former economist with stints at CFTC and BLS (Bureau of Labor Statistics), Nicolas has a unique background and life story that led him to crypto. That's why I think Tellor is one of the most ambitious and hardcore-decentralized protocols in the industry. Furthermore, Nicolas explains how his work with Tellor informs his work with the Washington DC crypto lobby.

I interviewed Nicolas back in March 2022, so clearly a lot has changed in the markets since then. However, what remains the same are the tireless dedication and optimism of great crypto founders like Nicolas.

Watch this episode on YouTube:

Links:

• Tellor website: https://tellor.io

• Follow Tellor on Twitter: https://twitter.com/WeAreTellor

• Nicolas’s LinkedIn: https://www.linkedin.com/in/nicholas-fett/

PS. Three years ago, before Hummingbot was even born, Nicolas interviewed me on his podcast. Check it out to learn about Hummingbot's origin story!

To explain this dynamic, I gave the following talk at a couple of conferences (Avalanche Summit, ETHPortland) recently and will do an updated version at EthCC later this summer.

Below is a lightly-edited transcript.

When my startup pivoted to building an open source crypto trading bot 3 years ago, everyone (but especially our VCs) were like: What? Why? And most importantly, how will you make money?

At the time, to be honest, we didn’t really know either. But the idea seemed to resonate with exchanges, so after getting a small dev grant from 0x and striking a partnership with Binance, we decided to go for it.

Today, Hummingbot is the industry’s leading open source trading bot, used by tens of thousands of traders and developers all over the world. We are now a globally distributed team spanning 20+ countries, split between a for-profit company and open source foundation.

Along the way, we discovered that trading bots and exchanges have an interesting symbiotic relationship that not many people understand, so I want to explain that to you today.

First, a couple of definitions…

What is an Exchange?

I often use the analogy of a bazaar (a flea market to us uncultured Americans) to explain how a crypto exchange works.

A good bazaar has a diverse selection of products for sale, but what makes that happen are the individual merchants. If there are only a few merchants, shoppers wouldn’t come to the bazaar. And if there are only a few shoppers, merchants wouldn’t want to set up their stalls at that bazaar. A bazaar is a two-sided marketplace that needs both merchants and shoppers to function properly.

Crypto exchanges are similar. Traders arrive at the exchange to buy and sell tokens, but their ability to trade with low transaction costs depends on others who provide liquidity. Without these liquidity providers, traders wouldn’t want to come, and without traders, it doesn’t make sense for the liquidity providers to show up either.

In exchange jargon, we call the liquidity providers the market makers (or just makers) and the traders the takers.

This is a colorized photograph of Exchange Place in Manhattan, around 1900. Not too dissimilar from a bazaar, right?

The people standing on the street are market makers, who each ran individual businesses buying and selling stocks to passerby. Eventually, they decided to join forces and operate as a collective in a nearby building, which became the New York Stock Exchange.

Naturally, these makers didn’t like competitors, so they tightly restricted access to liquidity provision. Even to this day, you have to be a Designated Market Maker to provide liquidity to the NYSE, an exclusive role available only to the largest trading firms.

But then along came cryptocurrencies, and all of a sudden, anyone who could create a website or write a smart contract could launch a crypto exchange.

Because of that openness and the resulting competitive dynamics, the crypto exchange industry has evolved in a radically different way from what exists in traditional finance.

Just like bazaars, crypto exchanges are pure marketplaces, so they had to cater to both makers and takers by offering free, open API access to everyone. NYSE and other traditional exchanges charge millions of dollars per year for this direct market access.

It also enabled a lot of experimentation and creativity. Today, there are thousands of crypto exchanges of all stripes and styles, trading both spot and derivative markets, both centralized (database-based) venues as well as decentralized exchanges that live on myriad blockchains.

I hope that gives you a broad overview of exchanges, so let’s talk about bots.

Subscribe now

What is a Bot?

Many people think of trading bots as malicious, AI-driven agents, but having seen how users really run bots over the past 3 years, I use a much more basic, boring definition:

A bot is a process, a computer program that loops continuously. In each loop, a bot fetches data from one or more exchanges, performs some internal logic that tells it how to proceed, and then attempts to execute transactions on those exchanges. Like any computer process, a bot keeps running until it’s terminated, either by the bot-runner or by some external event.

In fact, a key bot metric is how long they can run before being terminated by some external event outside the runner’s control, bugs in either the bot code or the exchange code, WebSocket stream disconnection, memory or storage issues in the cloud instance where the bot is deployed, and even node infrastructure issues in the case of decentralized exchange bots.

Identifying and fixing these edge cases can be tricky, which is why a good QA testing process is important in building a good bot.

Bots are typically clients, not protocols. A client is software that you run on a machine where you have exclusive, secure access. That’s because in order to continually send transactions, the bot needs unencrypted access to your API keys for centralized exchanges like Binance, as well as wallet private keys in case of decentralized exchanges like Uniswap.

Therefore, most bots are deployed on cloud instances like AWS, ideally in the same geographic region as the exchange’s cloud servers to minimize latency. While there do exist web-based platforms where you can input your API keys and run bots, they are generally aimed at retail traders. As the saying goes, “Not your keys, not your crypto.”

Despite the popular misconception that bot-runners are evil hackers, the reality is that most bots are run by individual traders and developers just trying to make side income. 

Some traders make enough money to hire their friends, and that’s basically how all quant trading firms start off, even the largest firms like Jump and Citadel.

Subscribe now

How Bots Interact with Exchanges

Most exchanges in traditional finance, as well as most centralized crypto exchanges, use an order book model. Makers submit limit orders that specify how much of a specific token and  what price they are willing to buy or sell, and the order book aggregates all of those orders in one place. Makers can cancel or adjust their orders at any time, typically for free.

The aggregate order book provides the liquidity that is available for takers, the traders coming to the exchange looking to buy and sell tokens, to consume.

Because of market price volatility and competitive dynamics, makers need to rapidly create, adjust, and cancel orders in order to not lose money. While human-powered “click farms” still exist, most serious makers run market making bots to automate this activity.

Above is a diagram of a simple market making bot. Each loop, it fetches the state of the exchange order book and decides if it needs to refresh the orders it has placed.

Let’s say a market making bot has placed a buy order 1% below the current mid price, the current price in an order book, defined by the average of the best buy and sell orders. It has also placed a sell order 1% above the mid price (makers call this making a two-way market). 

If the bot fetches the order book and discovers that the mid price has moved substantially in either direction, the bot will likely need to refresh its orders in order to continue bracketing the mid price.

But order books aren’t the only exchange model in crypto. Automatic Market Maker (AMM) decentralized exchanges, popularized by Uniswap, exploded in popularity in 2020. Today, they account for billions in daily trading volume and are the fastest growing sector of the crypto exchange industry.

AMMs enable makers to provide liquidity simply by depositing two tokens into a pool. The smart contract has simple internal logic that sets a price for any given quantity that a taker want to buy or sell, with the condition that the product of the quantities of the two tokens in the pool must be the same before and after the trade (x*y=k). Because an AMM allow makers to provide liquidity in a single transaction whereas they would have to constantly refresh orders in the order book model, AMMs are a perfect fit for blockchains, where every transaction costs gas.

But there’s a catch. Since an AMM is just a pool of two tokens and all makers can do is to add or remove liquidity, the only way that AMM’s mid price can change is via trading. That means that whenever market prices shift, arbitrage opportunities are created. While some trades are done by retail traders coming to swap tokens, the bulk of AMM transactions are executed by arbitrage bots.

Above is a diagram of a simple arbitrage bot. Each loop, it fetches prices from two different exchanges that trade the same trading pair. 

If the two markets exhibit a meaningful price difference, the bot will execute a buy transaction on the lower-price exchange and a sell transaction on the higher-price exchange, locking in an arbitrage profit. If there’s no arbitrage opportunity available, nothing happens and the bot loops again.

So the status quo in the crypto exchange industry today is that retail traders are takers consuming liquidity, on order book exchanges, while they are makers providing liquidity on AMMs.

Conversely, market making bots are the makers on order book exchanges, while arbitrage bots are the takers on AMMs.

The industry has evolved this way because retail traders gravitate toward user-friendly, simpler styles of trading, like earning LP yields or taking from an order book, but to sustain that type of experience for them, the marketplace need some type of automated agent (bot) to provide the necessary liquidity or volume.

In trading parlance, a functioning market matches toxic flow (professional bots) with non-toxic flow (retail traders).

But since bots are programs that can do anything, they aren’t limited to just arbitrage and market making.

• Hedging bots allow you to protect against downside risk by hedging on another market. For example, our Cross-Exchange Market Making bot combines market making and arbitrage to provide liquidity to one exchange while hedging filled orders on another exchanges.

• Smart order routing bots improve the execution of a trade, by splitting up a large block into smaller chunks that are routed to different exchanges, or dripped onto an order book over time. One example is Hummingbot’s TWAP strategy.

• Technical indicator-based bots execute trades based on a technical indicator like RSI or MACD. For example, the Aroon Oscillator strategy in Hummingbot computes the Aroon indicator based on order book data and uses it to improve Hummingbot’s base market making strategy.

That’s why we designed Hummingbot as an open source framework. You can run the off-the-shelf strategies, or you can build your own custom bots.

The possibilities are endless.

The Hummingbot story

Let me tell you more about Hummingbot.

Before we launched the open source project 3 years ago, what sparked the idea was meeting lots of people trying to build trading bots: DEX startups, market makers, and even individual traders.

They were all spending weeks doing the exact same thing: building exchange integrations that let them do high-frequency trading. This entailed debugging low-level WebSocket connections, and wrestling with poorly-documented exchange APIs.

Even worse, they had to do all this drudgerous, mind-numbing work for every single exchange before they could run a single trading bot. When you are sending 10 orders a second, since any bug, however slight, could cost you a lot of money.

In hindsight, the answer seemed obvious: an open source project with integrations to every exchange, each built and maintained by community members, that everyone in the world could use.

Not only does Hummingbot maps different exchange APIs into a single, unified standard, but it also offers integrations to both centralized and decentralized exchanges.

Currently, the two worlds are highly fragmented for the simple reason that the two sides don’t speak the same language from a technical standpoint:

• Code: CEX traders are Python/C++ shops while interacting with DEXs requires familiarity with Solidity/Cargo and/or the ability to consume Typescript SDKs.

• Matching model: CEXs typically use the central limit order book (CLOB) model to match buyers and sellers, while DEXs are typically AMMs.

• Architecture: Connecting to CEX APIs requires familiarity with REST/WebSocket APIs while connecting to DEXs requires familiarity node/wallet/smart contract infrastructure across various blockchains.

With Hummingbot, quants can build cross-chain, cross-exchange bot that captures arbitrage and liquidity provisioning opportunities between any two exchanges in the network, say between Binance and Uniswap, or Coinbase and dYdX,

But Hummingbot isn’t just an open source codebase.

We have the largest and most active community of quant traders in the crypto industry. Thousands of people have learned market making through our YouTube videos and getting support on Discord.

Since Hummingbot is client software rather than a blockchain protocol, we happily welcome forks. Over 1500 developers have forked Hummingbot for their own use since we started.

Finally, we are starting to see significant institutional usage. Many token issuers and exchanges use Hummingbot as an alternative to hiring market makers, and new market makers now build their trading stack on top of Hummingbot to skip months of development work integrating to exchanges.

As the Hummingbot codebase matures and our community grows, I believe that it will eventually let users run any type of high-frequency trading strategy across any set of exchanges, anywhere in the world.

This is our mission: open source HFT.

Of course, this would be incredibly cool to build. But more importantly, this is the best way I can contribute to what I think crypto’s ultimate goal should be: giving people anywhere in the world the opportunity to achieve financial freedom for their families.

My favorite podcasts are interviews with other founders, especially those where the founder describes their ups and downs with unvarnished truth. Like a good book, I feel like I can empathize with the main character and the rationale behind their decisions, regardless of how it all turned out. On the other hand, I can’t stand the ones that are just content marketing for their startups.

Two of my favorite podcasts are The Quest with Justin Kan, where he gets other founders to share their stories with incredible openness and vulnerability, and Acquired, in which Ben and David, who are clearly lifelong friends from their warm radio-like banter, tell deeply researched stories of the world’s top startups.

So I decided to try to create a similar podcast, focused on crypto founders: people building companies, funds, protocols, DAOs, or just some random code on the blockchain. While I want to highlight people working on cool projects, my main motivation is to help them tell their founder stories. In particular, I’m interested in speaking to people who’ve made the leap from finance to crypto.

For the first episode, I’m excited to welcome Evgeny Gokhberg, managing partner of Re7 Capital, a quant hedge fund that pursues liquid high-yield stablecoin strategies. After I talked to Evgeny, I felt honored and lucky that he was my first podcast guest, because Evgeny shared an amazing story of how he grew up in the old USSR, studied finance in London and joined the elite ranks of UBS private banking, but gave it all up to join a tiny crypto startup, which somehow led to him managing a quant crypto hedge fund today.

Watch the video above or check out the Youtube video to hear Evgeny’s story:

• Growing up in Moscow and the differences between Communist finance and Western finance

• How he applied to 200 hedge funds to get 2 job offers

• Making his first angel investment

• Quitting a cushy private banking job to join a tiny crypto startup

• What unlocked the opportunity for him to launch a quant hedge fund

Unbeknownst to me, this entire conversation was accidentally live-streamed to Youtube. That could be either a feature or bug, so in the spirit of product-driven experimentation, I’m just making the raw, unedited video available!

Watch on Youtube

P.S. I apologize in advance for my extreme overuse of filler words (um, ah, like). I’m working on it.

P.P.S. If there’s someone in particular that you’d like me to interview, please leave a comment below, and I’ll try to make it happen!

That’s the core premise behind the Jobs To Be Done framework, popularized by the immortal Clayton Christensen. We “hire” products that perform “jobs” that ultimately help us achieve more of our fundamental desires: money, time, fun, status, meaning, etc. Over time, as technologies change and human societies adapt, new ways to fulfill these basic needs become viable, so we switch from old products to new products.

So what is the “job” of crypto?

What basic human need does it solve for in some new way?

Let me tell you about my first job.

As mentioned in this newsletter’s first post, I started my career on a Wall Street trading floor like this one.

Everyone in this room had the same basic job: creating new tradeable securities. It was our job to shepherd every type of company through the process of issuing a new security across every possible asset class.

We helped corporations issue new stocks and bonds. We helped banks securitize mortgage loans, credit card loans, and auto loans. We helped asset managers create ETFs, mutual funds, and other investment vehicles. Anything the market desired, we could securitize for it.

Basically, we helped issuers convert an intangible financial good with unknown value, held by insiders, into an asset trading on the secondary market with observable price movements and organic trading activity, held by the public.

We helped them get liquidity.

Liquidity is the difference between a paper stock certificate and a Fortune 500 company, between a JPEG and an exclusive NFT, between a public asset and a private asset.

But Citigroup did not sell access to liquidity cheaply.

From idea generation (assembling hundred-page Powerpoint decks to pitch to various companies) to roadshows (2 weeks flying business with one day in each major financial hub) to listing (getting blessed by a cadre of lawyers, regulators, and rating agencies), the entire process of turning an illiquid asset into a liquid one took at least six months, required hundreds of highly-priced humans working full-time, and often cost millions in travel costs alone.

The worse part was after these assets started trading. Every morning, I had to hustle and beg our traders, bored assholes fond of jokes with vague racial undertones, to give me indicative buy and sell prices for each bond we had issued. These marks were the price guideposts that helped our salespeople conduct daily client conversations and researchers write weekly reports. Of course, traders hated giving marks because they were giving away free information, so they took it out on junior analysts like me.

This long, painful process was necessary to make any asset liquid, so Citigroup couldn’t even entertain working on a deals less than $500 million in size. Otherwise, our fees simply wouldn’t cover the people, process, time, and compliance costs entailed.

In fact, I think creating liquidity is the only job that Wall Street really performs. Wall Street is just a gigantic vampire squid that manufactures and spits out financial assets, slicking off fee tendrils every time its tentacles juggle them.

But this one mammoth creature blocks access to liquidity for everyone else.

Until very recently, IPO markets were only available to a lucky few venture-backed companies, discouraging founders from starting new ventures.

What if liquidity were free?

What if anyone could make anything liquid?

Make Anything Liquid was the kind of slogan you heard at crypto conferences during 2017 and 2018, those heady days when many of the early Ethereum-based decentralized exchanges (DEX) raised their initial rounds of seed capital.

But now it was 2019, the bleak, black days of crypto winter. For two miserable years, we had all been desperately searching for product-market fit. You can see the pressure in our slumped shoulders and anxious huddles.

My startup Hummingbot was building an open source crypto trading bot, so our natural partners were the early Ethereum decentralized exchanges and protocols: 0x, Radar Relay, Airswap, DDEX, and IDEX.

Our success depended on their success, but none of the DEXs were even close to achieving their holy grail: a liquid, growing exchange that could challenge the large centralized exchanges. Quite the opposite, DEX volumes had actually fallen from 2018 to 2019 as the initial ICO buzz cooled off.

Skeptics doubted whether DEXs would ever become a reality:

If the long-run interest in DEXs continues to be for trading coins that aren’t available on centralized exchanges, the future is bleak. Anyone taking a sober look at the ICO landscape is likely to admit that the majority of offerings are little more than scams.

How successful have DEXs been and what can we expect going forward? Volume growth has stagnated for the few 0x relayers. EtherDelta seems to be running at lower volumes than it was earlier this year. Other DEXs are showing volume in the low millions with no major winners yet. This compares to USD billions in (daily) volume on centralized crypto exchanges.

— State of Decentralized Exchanges, June 2018

We didn’t realize it back then, but the problem was that all of those early DEXs used the order book model, copying Coinbase, Binance, and other centralized venues.

In hindsight, order books were a terrible match for the realities of L1 Ethereum, where block space is limited and each transaction is highly expensive. To accommodate, DEX order books had to be off-chain, just like centralized exchanges, so no one could atomically execute an Ethereum transaction to trade against a stale order or take advantage of an arbitrage opportunity.

Liquidity, the ability to buy and sell an asset for a specific price, was not yet available on the blockchain.

There did exist one exchange with on-chain liquidity, but I and many others pooh-poohed it as a simple toy after Uniswap launched in November 2018.

Uniswap was an Automatic Marker Maker (AMM) DEX. Conceptualized in a 2017 Reddit post by Vitalik Buterin, an AMM is just a pool of two assets locked in a smart contract that uses a constant product formula (x*y=k) to match buyers and sellers. According to the formula, any exchange between Asset A and Asset B must satisfy the constraint that the product of the asset quantities cannot change, both before and after the swap.

Effectively, an AMM creates a simple linear order book without requiring market makers to maintain and refresh orders.

AMMs provide the simplest possible experience for liquidity providers, since they just had to deposit two assets into the pool. No matter how market prices fluctuated afterwards, an AMM’s x*y=k constant product formula ensured that a price existed for any possible transaction. The catch, however, was that every liquidity provider in the pool had the exact same position and could only add/remove liquidity, which made professional market makers reluctant to participate.

But Uniswap’s programmatic nature meant that the existence of liquidity in any pool enabled potential arbitrage opportunities with any other market, and the first and only rule of markets remains that any and all arbitrage opportunities will eventually be closed.

Critically, one of Uniswap’s most impactful decisions was to tokenize Liquidity Provider (LP) positions, which enabled Yearn, Gelato, and other projects to apply leverage and boost yields for retail depositors.

Once degenerate yield famers could earn 100%+ annual yields, the DeFi flywheel started to accelerate in the summer of 2020, and began spinning faster and faster.

Today, DEXs are processing billions of dollars in trading volume every day. Access to liquidity has changed everything.1

Founders no longer have to hire an investment bank to take their company public. Instead, they can create a token and get instant liquidity for it on Uniswap.

Artists no longer have to hire an auction house to sell their artwork. Instead, they can create an NFT and get instant liquidity for it on OpenSea.

The trading floor is obsolete. Markets have replaced the need for middlemen.

Liquidity used to be the job of Wall Street, but now crypto can fulfill that basic human need 1000x cheaper, faster, and easier.

I am truly scared for what might come next, but I’m also excited for what’s possible.

I’ve been a struggling startup founder in Silicon Valley for the past 11 years, ever since I took a Stanford class and formed a team with a few Indonesian classmates to build a Blackberry app to solve Jakarta’s massive traffic problem.

Not surprisingly, that idea failed, but I had caught the founder bug. This began a long trek through the wilderness of startup failure.

There was the Wealthfront for family offices idea that went nowhere, the PDF table extraction tool for which my friend Max and I managed to raise a grand total of $240k from our friends and family, and mercifully, an acqui-hire that allowed us to pay them back, which I made sure to frame as a successful exit.

Rather than generational wealth or saving mankind, my reason for persevering was more basic: I couldn’t conceive of myself as a failure. Before coming to Silicon Valley, I had spent 9 years as a trader in the infamous subprime mortgage CDO industry and had grown accustomed to a steady rate of inflation in both title and all-in comp.

While I had left the finance industry because I wanted to create things that were actually valuable, my ego wouldn’t settle for being a product manager at someone else’s company. After every Techcrunch article about other founders raising huge rounds for ideas that seemed obvious in hindsight, I thought why couldn’t I have done that?

During those long years in the wilderness, raising a Series A round seemed like an impossible, magical threshold, after which I could finally look myself in the mirror without a low-level hum of castigation.

Incredibly, with a lot of luck and hard work, it finally happened.

Last year, my startup raised an $8 million Series A round led by Initialized Capital to build an ecosystem around Hummingbot, the open source market making software that we launched in 2019.

More importantly, over the past few years of building Hummingbot, seeing the myriad ways that our community used it, and understanding the value that it provided to them, I finally understood what genuine product-market fit felt like. Instead of chasing vanity success metrics, I discovered in myself a long-dormant, primal drive to invent something new, to build a product that provided people tangible value for the sake of it, to create a public good.

Liquidity is an essential need for anyone who issues a token, and before Hummingbot, their only option was hiring a hedge fund for market making services. By providing a free, open source bot, we had created the only software-powered solution in an industry dominated by human-powered, often dubious, market makers. In addition, we invented a new type of exchange for market makers instead of retail traders, where liquidity seekers could algorithmically distribute rewards to a decentralized community of liquidity providers, rather than just hiring a single one. Today, Hummingbot has become an indispensable DIY liquidity tool for many token issuers, exchanges, and trading firms, as well as thousands of individual traders and developers around the world.

Over the course of 2021, we tripled our team size and spun off the Hummingbot project into a new open source foundation governed by token holders. Entering 2022, I was the CEO of a rapidly growing crypto startup with 70 team members in 20 different countries.

That’s why it took a long time for me to process why I wanted to hand over the CEO job to my co-founder Carlo and embark on a new career as a Substack newsletter writer.

So for this first post, I wanted to tell you my origin story, why I decided to leave my job, and what I’ll be writing about.

I wanted to be a writer when I was young, because I spent most of my time reading books.

My parents worked weekends, so they would drop me off at the local public library, where I spent the entire day curating the set of books that I brought home to read during the ensuing week. Half of the books had to fit precise Dewey Decimal categories (biography, history, science, etc), while I could pick the other half myself, mostly Agatha Christie mysteries and YA fantasy epics that I devoured first.

When I wasn’t reading, I was playing computer games like Frogger and Return to Zork on the 386 PC that my parents had the incredible foresight to buy for me in 3rd grade, despite our limited finances back then.

I also spent many nights correcting the grammar in my parents’ cover letters as they looked for jobs. This was a matter of survival for my family. After the 1989 Tiananmen Square massacre, my dad organized demonstrations at the University of Florida in support of the Chinese student protestors. After getting their PhDs, if my parents couldn’t find employers willing to sponsor their green cards, we might have to go back to China, where, even today, people are disappeared.

Miraculously, after countless rejections, my dad finally landed an internship with a small Philadelphia options trading firm called Susquehanna Investment Group as their first-ever quant hire. SIG grew into one of the largest trading firms in the world, and my dad endured 20 years as one of the few Asians and non-native English speakers on a Wall Street trading floor.

Like many other first-generation immigrants, I learned that getting a good, proper job was the key to success in life. Despite my love for writing (I still treasure my Class of 97 Top English Student plaque), I never seriously considered it as a profession after learning that a journalist’s starting salary was a scant $19k a year.

Instead, I took the diametrically opposite route and went to Wharton undergraduate business school, the finishing school for junior investment bankers and management consultants. There, I met my future Hummingbot co-founder Carlo. We lived in the same freshman dorm and became lifelong friends after discovering a shared enthusiasm for drunken gymnastics.

During university, my favorite books were Liar’s Poker, Michael Lewis’s first book about starting his career on a mortgage trading desk at Salomon Brothers, and the lesser-known but equally-great FIASCO. Where others saw rogue traders who created complex, esoteric products that destabilized markets, I saw inventors who were creating experimental financial products that allocated risk and reward in radical, new ways.

After graduating in 2001, I joined a tiny trading desk at Salomon Smith Barney, the old Salomon Brothers remnants amalgamated with a retail brokerage into a corporate monstrosity sheltered under the drab Citigroup umbrella. My daily work environment was a cavernous Lower Manhattan trading floor, filled with a nonstop cacophony of ringing phones, barking Brooklyn accents, and random pushup contests. None of the mortgage traders, who still answered their phones Salomon Braawthers, knew what we did, only that it involved a lot of fancy computer models.

My desk structured and traded an obscure new product called a collateralized debt obligation (CDO).

As Anthony Bourdain explains above, manufacturing a CDO is similar to alchemy. We transformed a portfolio of high-yield bonds (rated BB and below) into a mix of AAA and other investment grade debt tranches that were sold to banks, pension funds, and insurance companies, along with a harder-to-sell equity tranche aimed at the degenerate investors of the time, family offices and hedge funds.

There was only one problem. CDO market growth was capped by the availability of high-yield bonds in the secondary market. We couldn’t find enough of them to package them into CDOs.

My desk had a potential solution. They wanted to recapture the old Salomon magic and package CDOs using mortgage-backed securities (MBS), especially the subprime variety which had substantially higher yields (ha!) than high-yield bonds. The MBS market was many times larger than the corporate bond market, plus the mortgage trading desk was holding a lot of illiquid inventory that they were eager to offload.

My job was to optimize the deal structure in Excel in order to maximize the yield of the CDO equity tranche, the hardest to sell, while maintaining the necessary ratings on the debt tranches. Tweaking these models (financial engineering) was my favorite part of the job. Each optimization - adjusting the asset composition, building new features into the cash flow waterfall - led to incremental jumps in the equity yield. It was like playing with math legos.

But first, we needed a model. Since a single CDO contained hundreds of MBS, and each MBS contained thousands of individual mortgage loans, using a regular Excel model would be cumbersome and impractically slow. So I built a model like this one that offloaded most of the calculations to VBA and used it to structure South Coast Funding, the first-ever CDO backed by subprime mortgages.

Over the next 7 years, subprime mortgage CDOs became Citigroup’s most lucrative and important fixed income product. The most aggressive buyers, mid-level managers at Asian and Middle Eastern banks and insurance companies, didn’t care what assets were in the portfolio. They were just doing their job, which appeared to be buying the highest yielding bonds of a certain credit rating. Some were so eager to lock in allocations that they would wire us the money before the deal was even officially announced.

Due to insatiable demand from CDOs, the supply of cash MBS in the secondary market ran dry, so we started to package CDOs with synthetic MBS created using credit default swaps, as depicted in The Big Short. Unlike in the Hollywood version, I and my Wall Street counterparts created the initial versions of these instruments. The hard part was convincing hedge funds to short the white-hot US housing market in 2004.

Bizarrely, what should have been the hard part - finding someone to bear the risk associated with a price decline in the US housing markets - was trivially easy, because Citigroup itself wanted to keep the largest tranches in each CDO, which contained embedded liquidity puts:

Citigroup almost went out of business in 2008 because it sold products with liquidity puts. That meant that if debt Citi sold to other investors became illiquid, those investors had the right to sell them back to Citi at face value. When debt markets froze, liquidity puts cost Citigroup $25 billion in losses in 90 days, at a time when it had less than $90 billion in equity.

Virtually all Citigroup’s liquidity put losses came from subprime mortgage CDOs that my desk created. Most of them used descendants of my original Excel model.

Believe it or not, this was an independent decision made by Citigroup’s treasury department. In fact, they were eager to hold the super-senior AAA bonds that contained these puts, which had juicy 20-40 bps spreads compared to standard corporate AAA bonds with thin 5-10 bps spreads.

Why? Because the decision makers, mid-level managers from Citigroup treasury, had the same basic job as the foreign CDO buyers: maximizing yield on a bond portfolio while maintaining certain credit rating and duration requirements. Performing too much due diligence might lead to a decision to pass, create more work for everyone on the team, and impact their year-end numbers, while staying silent was much more convenient. 

After the bottom fell out in 2008, everyone kept repeating the same stupid cliched phrase: we missed the forest for the trees.

In our continual competition to maximize yields, optimize transactions, and collect the next year-end bonus, we had all missed the perverse incentives that the CDO machine had created. 

Not only had this esoteric financial backwater actually warped the US housing market by fueling a bubble that would eventually have to pop, but I felt like I had personally contributed to millions of people losing their jobs and their homes.

Looking for a career reset, I applied to an engineering master’s program at Stanford and, luckily, got in. I had no aspirations to be a founder. I just wanted to leave finance behind.

Subscribe now

I’m a very different person today from the lost soul who came to Silicon Valley 11 years ago. Every failed startup idea and VC rejection letter taught me something new - how to build products that solve unmet needs, how to explain ideas to investors in ways they understand, how to manage people, how to understand myself better.

After raising our Series A last year, I spent much of the rest of the year interviewing candidates over Zoom, as we embarked on an ambitious hiring binge. Organizing my calendar became a more depressing version of Tetris as meetings stretched from early morning to late night.

Hummingbot’s core philosophy is that talent exists everywhere. We have built a 70-person team in 20 different countries, including Nigeria, Russia, Malaysia, and Iran. Coordination across time zones and cultures is still a huge ongoing challenge, but we make it work because of a bottoms-up, remote culture, powered by responsible, hard-working individuals who could reliably do their jobs while trusting their colleagues to do theirs.

In my opinion, Hummingbot’s most durable competitive advantage is our ability to scale a highly technical, globally distributed team.

The person responsible for running our organization efficiently is my co-founder and COO Carlo, who honed his finance and operational chops during a 13-year investment banking career at Goldman Sachs and other top Wall Street firms. But Carlo is much more than just an ex-banker; he is also a talented engineer who set up our initial devOps and blockchain infrastructure stack, and he has always done the small things that drive instill company culture, like organizing board game nights and decorating our Gather space.

Meanwhile, there were certain aspects of the CEO job that I enjoyed and excelled at, such as evangelizing Hummingbot and explaining how it compares to traditional market making. But there were other aspects of my job that I merely tolerated or even neglected, such as defining a clear organizational structure and building repeatable company processes.

Unlike my parents, who had to find employment or risk deportation, I have the opportunity to design and define my job, not just accept the one that society defines for me. Moreover, in order to legitimately espouse a culture of trusting your neighbors to do their jobs at Hummingbot, I have an obligation to set an example to my team.

That’s why I’m excited to announce that Carlo will take over as CEO of CoinAlpha, the company behind Hummingbot, effectively immediately.

This will enable Carlo to focus on growing CoinAlpha’s global team and our two lines of business: our Miner decentralized market making platform and the upcoming Hummingbot Prime product, a SaaS for institutional and advanced Hummingbot users that lets users rapidly backtest any Hummingbot strategy against full-resolution historical order book data.

Meanwhile, I will continue to work for CoinAlpha in a newly created job (working title: evangelizer/explainer/researcher). Using this newsletter, I plan to publish posts and host podcasts that explain how the Hummingbot ecosystem works, as well as explore new technical directions for the Hummingbot codebase.

My inspiration for this job is Vitalik Buterin, who plays a critical role in the Ethereum ecosystem without being involved in the day-to-day operations of the Ethereum Foundation. This frees Vitalik up to write two blog posts a month, attend Ethereum core dev meetings, contribute actively to ethereum/research, and evangelize Ethereum on the conference circuit.

More generally, I hope to bridge the prevailing disconnect between the finance and crypto industries by teaching people on both sides how the other side works.

The traditional finance world worries that crypto will be the next subprime crisis, a gigantic Ponzi scheme that makes a few people rich and many others poorer. True, there are many parallels between the insatiable chase for yield by DeFi token projects and investors today and the CDO excesses of yesteryear. But on the other hand, crypto people feel, justifiably, that regulators wield their power indiscriminately without fully understanding the underlying technology.

We’re talking past each other, not seeing the forest through the trees.

This newsletter will make the case that the crypto and finance industries will gradually fuse over the next few years, because they both solve the same core need: liquidity.

I’ll expand my past content related to market making and liquidity (articles, videos, whitepapers) to shed a bright light on that shadowy, opaque industry. I’ll expose the business model of market makers and how they can charge their customers millions per year. I’ll explain why the AMM (or more precisely, Uniswap’s working version of a decentralized one) is one of the most important inventions in the history of finance.

I will write about how everything in finance is about to change.

We now have all the tools we need to manufacture our own financial instruments, and more importantly, make them liquid and tradeable. These tools, all open source and publicly available, include blockchains like Ethereum, exchanges like Uniswap, and bot software like Hummingbot.

Before, we had to hire a middleman to do this job for us, with titles like venture capitalist, investment banker, and market maker.

Not anymore. Now, anyone can create a token, a digital representation of anything, that can be swapped for any other token on unblockable exchanges located anywhere in the world.

Essentially, we all have the power to invent new forms of money. 

Just like the Internet disrupted the media and commerce industries 20 years ago, crypto will change every aspect of finance, in ways both good and bad.

How it will all unfold, I frankly have no idea, but I’m excited to explore what the ramifications might be in this newsletter.

Finally, I want to teach founders what Silicon Valley calls product, the art of building something that people want, coupled with the science of getting someone to pay for it.

All those startup failures, interspersed with a few successes, have forced me to be honest with myself and taught me which product directions tend to work and which fail. I think I can use that experience to dispense hard but necessary product advice, not only to those actively building in the crypto or web3 space, but also to all the aspiring crypto founders out there trapped in traditional finance jobs.

Crypto is a technology that allows anyone to create liquid financial instruments, and like all new technologies, it will be used for both good and evil. While there are certainly scammers out there, most crypto founders are trying to do good by building projects that address the many hard problems that exist in the world.

I’m excited to help them succeed.