Information in DeFi and the wider crypto industry is widely accessible but scattered and often incoherent. It’s certainly not an understatement to say we’re dealing with information overload. To further complicate the situation, KOLs with crypto-cult-like behaviors endorse a project or shill tokens, and then casually throw in a DYOR (do your own research). It's suffocating and difficult to ascertain what’s true. Needless to say, access to reliable data and insights requires intensive research, careful analysis, and the ability to synthesize many sources of information. Instead of placing faith in individuals, well-informed decisions should be provable, backed with reliable on-chain data, and rooted in quantitative sciences. There’s a market for DeFi insights backed by clean data and 

It all started with the Risk Terminal which was launched last December as an MVP. We released a dashboard that was built on a few basic models we’d developed. Visualizing these models’ output was powerful. In the meantime, our community built more and more models. So we took a step back and wondered if we could coherently organize them. This effort led to the release of what we now call the Credmark Terminal. Behind the scenes, we do all the number crunching so users can see the outputs of validated financial models like 

. (Learn more about why we started with these models 

.) In a sense, the Credmark Terminal is a showcase for our models. All of the code is open source so anyone in the community can grab it to build their custom dashboards. Over time, we hope the Terminal becomes a primary source of risk data and financial data in DeFi for people who don’t require access to the raw data available via our API.

The first models we’re deploying in the Terminal cover lending protocols like Aave and Compound. Their source code can be viewed 

. All financial models are validated and verifiable, so users can verify how the models are built. Rest assured, all data is sourced from Credmark’s reliable on-chain state and ledger data.

Although risk continues to be our focus, our community has asked for other types of financial models. We’ve begun supporting those and, by necessity, had to rename the product. That’s how The Risk Terminal became the 

We’ve implemented lots of feedback from our users, added a ton of exciting features, and redesigned the entire terminal. This new interface enables us to easily scale and include more exciting features as our model repository grows. Selected models will be displayed on the terminal.

 will showcase established TradFi metrics like 

 but tweaked for DeFi. Other protocol metrics like VaR, TVL, and Trading Volume will be added subsequently in the coming weeks.

 will feature metrics like VaR and LCR for Aave and Compound. The new PowerBI Dashboard will also show data on Aave and Compound such as the flow of assets, top 10 transaction count, top 10 wallets, etc

 cover VaR, TVL, and Trading Volume metrics for the Top-10 pairs across Uniswap, Sushiswap, and Curve

 will show all relevant stats on Credmark’s native token $CMK and display the models that are most popular in terms of queries via our API.

All of the data in the Terminal will be available on 30-day, 60-day, or 90-day timeframes and can be downloaded in CSV format.

Sharpe Ratio is an established metric to compare risks and returns of assets. As we adjusted it to be compatible with DeFi, users are now able to compare the Sharpe Ratio for up to 5 different tokens across a time series.

While the lender's section only covers Aave and Compound at the moment, the purpose of these charts is to showcase the liquidity and solvency of lending protocols over time. These metrics are useful indicators to assess when the protocols may be undercollateralized or how much value may be at risk in a black swan event.


The Lending Pool Usage is a great tool to see the top lenders or borrowers of DAI, USDC, and USDT stable coins on Aave and Compound. Users can quickly visualize:

Users can also perform more in-depth analysis by right-clicking on a dataset and pressing drill through. All information is neatly presented up to the exact transaction hash and block timestamp.

Providing liquidity is a lucrative way to earn money, but it is risky. Our dashboard can provide insight into potential risks with the use of VaR or inform users of the imbalance within various Curve pools.

Take for example, the USDC / ETH pool on Uniswap V3 has a VaR of -30% which indicates the possibility of losing up to 30% of your total LP position in a worst-case scenario.

Now if we look at the Curve 3Pool, the balance ratio less than 1 which reflects an  imbalance towards USDT in the pool:

The Credmark Terminal is an application that demonstrates how powerful Credmark’s data is. As more sophisticated models are built, the more utility the Terminal will have. A full list of the current models can be found in the 

. A lot of the current models are built with the same parameters as traditional finance. At Credmark, we’ve been at work to develop crypto and DeFi native models. This is just the beginning. We will release some useful interactive dashboards very soon. 

 and let us know what you think or what you would like to see.


 is a financial modeling platform for DeFi, powered by verifiable on-chain data. It provides the infrastructure necessary to build models. An API allows anyone to consume the output of these models. 

Our modeling tools are the most flexible and robust available today. The 

 streamlines prototyping and deployment. 

 members are incentivized to build and improve models. As a result, users benefit from verifiable data and best-in-class analyses.

Credmark is a decentralized project. Our community participates in governance, provides research, and develops models. 

 to advance the next-generation financial system.

A DeFi Source of Truth

Introducing the Credmark Terminal

Simply access verifiable on-chain state and ledger data using 

Blockchain data is public and immutable. Smart contracts are also public, so everyone can see what they do. This transparency and immutability lead people to conclude that blockchain data can be trusted. It can and it can’t be. Almost nobody consumes the raw data, which is reliable. Instead, we consume interpreted data, and that interpretation is not reliable at all.

Web3 participants are unlikely to challenge the validity of the data they consume even though they know nothing about how it was produced. Data collection and interpretation methods are either obscure or unknown. Luckily, this will gradually change as the industry develops and the race to acquire higher quality data accelerates. More competition will inevitably lead to more stringent demands for reliable data.


On-chain data is raw when it is first extracted from the blockchain. It has to be interpreted and indexed before it can be used. In DeFi, this data is produced by smart contracts, so the interpretation of the data depends on the contract (program) that produced it. There are millions of smart contracts deployed on the Ethereum chain alone. These multiple data sources complicate things further. A closer look will present 

 like how on-chain data timestamps and real-time data like oracles and API timestamps present different ways of expressing time.

Deriving insights from data require careful analysis and data normalization as well as consistent methodologies. All of these must be transparent and verifiable so users can now rely on them.

Web3 and DeFi are touted as trustless because of their transparency, but to what extent is this true? Most providers of data or DeFi protocols do not fully disclose contextual details.

The truth is, it’s all a black box and the methodology isn’t transparent. Say you want to fetch the number of swaps that were conducted using the protocol’s API.

How do you assess the accuracy of the output?

These are all good questions and we can’t answer them without full transparency. In the absence of this transparency, we assume the data is correct.

To showcase how discrepancy exists across multiple reliable data sources, we conducted 

where we queried liquidity data across three sources for the lending protocol, Aave V2.

Smart contract (on-chain) data extraction

On-chain analysis is conducted by measuring the amount of aTokens issued by Aave to depositors. The difference is between assets' balance fetched from Aave Native API and total supply of corresponding aTokens. 

 From the comparison, a major difference is present in the total number of assets (totaling up to several million in value).

On-chain was point-of-time before block creation

Subgraph data can be collected at any time of the data with no clear transparency on how the node operates and the variables it takes into account.

Different sync times with variance across outputs can be troubling. Not to mention, the outputs will be difficult to verify and reproduce. Check out the 

Data availability is crucial when we consider the amount of value transacted every second in crypto. Imagine if a rebalancing application cannot rebalance swiftly because:

the source is slow or unresponsive, or worse,

Users of more reliable data can react better and faster to market conditions. Reliable data is worth money. Unfortunately, these are common issues that persist in DeFi. Luckily, they are being addressed by a new generation of independent data providers.

These are a few of the problems we’ve encountered. It’s not to suggest that these are the only problems.

At Credmark we work publicly and transparently. All of the data we produce can be traced back to the original, trustworthy on-chain data. This data drives our finance and risk models that in turn produce data. All of this is available via our API.

Our engineering and modeling teams are always available. They respond to queries and process community feedback as quickly as possible.

To accelerate the development of decentralized finance, access to data with verifiable integrity is essential. Together, we can do this.

 to advance the next-generation financial system

A Primer

Data Problems in DeFi

I met Wen-Chiao in May of 2019. Credmark was 5 months old. We’d just gone through an accelerator program in Hong Kong.

For some reason – I really can’t remember why – I was in Tokyo. The accelerator’s Program Manager sent a note telling me that a friend of his wanted to meet. I had no idea what to expect, but I agreed.

Wen-Chiao suggested a coffee shop deep in the bowels of one of Tokyo’s train stations, the kind of place foreigners leave their luggage in lockers they’ll never find again. After some trial and error, I found the coffee shop, and Wen-Chiao.


When we started talking I realized he was unusual.

His speech gets faster as he finishes his thoughts, as if needing to catch up with his brain. He frequently punctuates his sentences with a breathless ‘yea’, which sounds like a confirmation, or a victory cry. I’m not sure which, but I love it.

Wen-Chiao sounds American. I assumed he was. Then he ordered a drink, and I thought he might be Japanese. When I asked him which it was, he laughed, and said: “I’m Taiwanese, yea.”


After that unusual ice-breaker, I asked Wen-Chiao why he wanted to meet. He told me he loved crypto and wanted to work with us. When I asked him what he wanted to do, he said: “I’ll do anything. I know a lot of people in crypto in Japan and Taiwan.” That sounded great. We needed to find potential customers in Asia. Only problem was, we couldn’t pay him. The best I could offer him was a bonus on success. Wen-Chiao thought that was fine and soon disappeared into the station.

Wen-Chiao is tenacious, and creative. We talked every week, and every week he had something new to tell me. He came up with all sorts of leads and introduced me to many people. But commercially, we made no progress. We were too far ahead of the market.

Wen-Chiao busted his tail, but never earned a dime of commission.


A year ago I told my co-founder, Neil, that I couldn’t continue as CEO. We weren’t making any progress, and I wasn’t capable of restructuring the company to address a more immediate problem. Luckily, Neil was. He took over and turned Credmark into what it is today.

Leadership changed. Our mission changed. Our product was ditched in favor of something a lot more ambitious. Despite the turmoil, Wen-Chiao stuck with us. He saw what Neil was doing, and he thought it made sense.


One day Wen-Chiao called me and said: “I’m going to disappear for a few months. I never finished my military service, and my time’s running out.” Disappear he did, for 6 months. The only time I heard from him was during short home leaves. He stayed in the loop.

During this time, we raised money and started building a robust organization. Just as we started looking for someone to manage our growing community, Wen-Chiao was released from the Air Force – forever 🤞🏻– and I suggested to our then Head of Marketing that he should talk to him. He did, and a week later Wen-Chiao was a paid consultant.


Wen-Chiao took to his new job like duck to water. He learned all the DAO tooling, managed our English community, our Chinese community, and our Japanese community. As far as I could tell, he never slept. In a company of hard-working oddball polyglots, Wen-Chiao fit right in.

Six months later Neil decided that our Head of Marketing should be responsible for growth. I had to find his replacement. I wondered: could Wen-Chiao do it?

I hired a first-rate marketing consultant to help me solve the puzzle. She worked with Wen-Chiao for a few weeks before letting me know that he was definitely Head of Marketing material. He asked the right questions, thought about the right issues, and worked hard to fill in his lacunae. So we gave him the job.


People love to talk about the opportunities available in DAOs. “All you have to do is show up and contribute.” In some cases, it’s true. Wen-Chiao showed up. He believed in Credmark through two different iterations. He stuck with us, and now he’s a critical part of the core team.

I couldn’t be happier with this outcome. I’m a little bit proud of the role I played in this journey even though 99% of the credit goes to Wen-Chiao. I’m looking forward to supporting him in the coming years.

The message to anyone else interested in joining our community is clear. We welcome contributors. If your work is valuable, you’ll be rewarded. We’re paying attention.


From “I’ll do anything” to Head of Marketing

Meet Wen-Chiao

How to install and run the Model Framework

 as an open beta.
We’ve received a lot of positive feedback and comments from a wide range of users like:


 if you haven’t. It’s a game-changer and we’re setting on a mission to help users build robust models, deploy applications faster and access the most reliable data.

how the Model Framework can greatly reduce lines of codes 

 to give things a spin, provide feedback and help us iron out any issues.

You get rewarded to build models, propose improvements, find issues, and help spread the gospel.

Whenever a model is submitted and validated in the 

, the creator will receive an NFT once the NFT membership portal is available. 

The model will be tied to a specific wallet address. Every time the model is used, the owner of the NFT will receive a payout. Model owners can also sell the NFT to a willing buyer.

Once you've completed the task, please fill out 

Keep in mind this initiative will end on 

 to engage with our growing community of developers, data scientists and quants.

Anyone who has participated in any of the activities above will receive a beta tester role when they 

. With this role, users will be the first ones to test drive any product or solution in development whenever external feedback is needed and get rewarded.

A Community Program

Model Framework Open Beta Initiative

On Monday, April 18th we will be shutting down our private discord server and migrating all our activities to our 

Continue our path towards decentralization


Reduce the friction for community members to become contributors

Discord has proven to be the best platform for DAO’s to communicate and organize, however, when the core team and community exist on different servers, people tend to default to one or the other. By shutting down the private server and engaging solely on the public server, our team will be in direct communication with our community.

Additionally, we are on the verge of launching our full modeling platform. Once this is live, it is inevitable that users will have questions and feedback about our platform and having one centralized communication medium will help connect our team to users and ease the learning curve.


The public server will be divided into the following categories:

Members (for those who have signed up for API access)

Each category will be supervised by a department head, and our moderators will be available for assistance in all these categories. The full scope of each head’s responsibilities will be determined as we implement these changes.


Welcome channel, links channel, other relevant info channel and most importantly, the pick roles channel which will decide


Major protocol wide announcements, general chatter and a community call page



Our engineering team will provide updates about our modeling framework as they come. Regular tech standups will be held to communicate these updates. Additionally, any infrastructure changes will be communicated here .We have a lot of moving parts so this area will be crucial to monitor.



This will be where we want our community to contribute to our protocol’s growth. We encourage community members to suggest and connect our core team with other projects that either want to leverage our protocol for themselves or who provide services that could be beneficial to our project.

This will be the most active area of our community. As the Risk and Research team continues to update our Credmark Wiki with new topics, they will be engaging the community in these channels to validate theories and discover new protocols. Additionally, we will hold workshops to guide devs through any trouble areas and to educate our community on how to build with our framework. Our existing Defi Alpha channel will live here.



Anything pertaining to UI/UX, product design, or graphics for our website, social media or copywriting for blogs and technical documents will live here. From our past competitions, we know that our community is capable of producing high quality content. We think this could be a great way for community members who are not technical or financial to participate.



This channel will most likely be limited to core members. This segment of the project is responsible for payroll, accounting, hiring and other administrative tasks that don’t necessitate community involvement, although community involvement is appreciated!



 
Owning CMK, or owning membership access will give users access to these channels. This will be where governance is discussed among other topics that pertain to the inner workings of the protocol.



There will still be a need for private channels. Certain team members will have the ability to create private channels within the server. Certain information deemed sensitive will have to be communicated this way. While our goal is to achieve complete transparency and decentralization, we are still a work in progress and have to proceed as such.


This post is purposefully vague as there will be many adjustments made to the server as we move forward, so we don’t want to commit to anything too specific. Expect some bumps and hiccups as we make this transition, but also expect a significant increase in activity and communication from our team. We think this change will spark increased involvement from our community and spur adoption of our product amongst other projects.

 is a financial modeling platform for DeFi, powered by verifiable on-chain data. It provides the infrastructure necessary to build models. An API allows anyone to consume the output of these models.

 to advance the next-generation financial system. 

Merging Internal & Community Discord Servers

Taking The Next Step Towards Decentralization

How to install and run the Model Framework


 makes rapid prototyping and deployment of crypto financial models simple. It enables builders to:

easily access current and historical blockchain data,


use existing validated models (composability FTW!),


Web 3 developers, quants, data scientists, or modelers can immediately get started after forking the 

. The framework enables the users to access the list of models in the local repository and run local models. Public models are also accessible with API calls. With over 

, builders can significantly reduce the amount of time to begin building useful Web3 software without the complexity of most Web3 development tools.

The web3.py library is complex. The Credmark Model Framework is simple and even more powerful. It reduces the line of code to fetch the same data compared to the web3.py library. In addition, it provides real-time and historical on-chain data of numerous protocols such as Aave, Compound, Uniswap, and Sushiswap. Any builder can use this framework and build applications on top of it. It provides builders with a toolkit and verifiable data all in one place.


To fetch data for each protocol or token can be a repetitive and redundant process. To illustrate the difference between web3.py python library and the Credmark Model Framework, we compare the two methods:

Fetch the total supply of the Credmark ($CMK) token and,


Fetch the pool address of two tokens on Sushiswap.


Fetching the pool address of two tokens on Sushiswap

The Model Framework abstracts a lot of the complexity involved in the web3.py library. Not only is deploying models easy and fast, the actual inputs to build the models are greatly simplified. Users no longer have to search for the individual token addresses — simply insert the token symbol. Variable declarations are also no longer necessary for the ABIs. We’ve reduced the complexity in the background to offer a better experience to the end-user.


A Model Framework Example

Develop in DeFi & Web3 Simply 

The process of fetching reliable DeFi and crypto data isn’t clear-cut. Say you want to know the historical price of a token, you’ll probably look to centralized services like CoinGecko or decentralized alternatives like SubGraphs or others like Dune Analytics. That’s all fine until the validity of the data is brought into question:

How would you know when or how the data was collected?


How would you know the exact block of the transaction?

The truth is, it’s all a black box and the methodology isn’t transparent. Reliable models require reliable data, precise context, and verifiable sources. 

This is where the Credmark Model Framework comes in.

, users can make use of existing and verified on-chain data, but it abstracts away the complexity of web3 coding. 

Input the block number or the time-stamp to output the transaction data. If there’s no data for the exact time-stamp, it’ll provide the closest data to the input time-stamp and corresponding block number. 


Don’t have the bandwidth to look for all the individual smart contract addresses? Input the smart contract address of the protocol, and it will output all the contract’s ABIs. 

It simplifies the coding process, to let modelers do what they do best without compromising transparency and verifiability.

Initially, the model infrastructure was used as the underlying framework to develop 

, an analytics dashboard that displays historical and live data powered by financial risk models. 

It was met with great enthusiasm as users can visualize and immediately assess the health of lending protocols such as Aave & Compound; an example application that was built using our model infrastructure and our data ETL. It served as a primer as we built out our framework and continues to output new metrics as new models are built with the framework.


The Credmark Model Framework is a set of tools that enable developers to rapidly prototype and deploy models that use blockchain data via Credmark’s Ethereum data ETL. In the next few months, we will provide API access to this data.


The Model Framework is designed with modeling best practices in mind. We chose Python for the purpose of rapid model development and flexibility. Financial modelers familiar with the Web3.py library understand the difficulty of building models that need access to large amounts of blockchain data. Our toolkit eliminates much of the complexity thanks to:

intuitive interfaces to define models, including their input and output data so that they are readily composable,


model context to ensure deterministic behavior 


a model search engine so that users can find and use local and remote models,


common data objects such as Address, Contract, Token, Position, Portfolio that encapsulate data and smart behavior.

These are a few examples of the components that we’ve developed to streamline the process. Check out our 

 in Github, you’ll find scripts and sample models to get you started immediately. We’ve also provided basic algorithmic, protocol, and series models that will make your model building easier. For a complete list, look at the 

When the Framework moves into general availability, model authors will be rewarded for their work. Every time a model is built, the creator will receive an NFT which represents ownership of the model. The NFT holder can hold onto the NFT to receive a payout every time the model is used, or sell it off to a willing purchaser. 

Until the model NFT is ready, we suggest modelers include a wallet address in the bio section of GitHub so we can provide the NFT once the system is ready.

The Model Framework is in open beta. We have a long list of improvements and additions and expect that list to get longer as our community experiments and provides feedback. 

introduction of Membership NFTs which grants access to the financial modeling and analytics tools

An Introduction

Model Framework Open Beta Release

A few months ago I wrote about the difficulties of DeFi treasury management from a planning perspective. It was called “

DeFi Treasury Management - A Halloween Special

” because managing money in DeFi is a horror show. Normal DeFi risks, like losing all of your money when you type a single incorrect number in a 42 character Eth address, become really scary when you’re moving around tens (if not hundreds) of thousands of dollars. Add in a half dozen protocols, 3 chains, a series of incompatible tools and you can start to see why I had a horror show on my hands.

, who is responsible for Credmark’s treasury management strategy, had put together a very clear asset allocation plan. He’s an experienced asset manager and crypto trader. He knows what he’s doing.

You can find the plan for our first cycle 

It was published in mid-December. We planned to execute it by January 1st.


Asan’s treasury management strategy is relatively traditional, but on the aggressive side. We decided to keep the execution dead-simple:

We analyze the plan's performance at the end of the month.


Getting this done was my problem, so I was stuck executing. Because all of Credmark’s treasury is managed through multi-sigs, I also needed a volunteer. It was getting close to Christmas and everyone had something better to do, but my colleague 

 felt sorry for me and offered to help. It’s possible he’ll never forgive me.

We read through the plan together and said: “Two hours, max.” We scheduled a two and a half hour meeting, just in case.


We thought the first phase of our asset allocation was dead simple: diversify our stablecoin holdings. Our treasury was primarily USDC, with some USDT. Asan wanted a more diverse portfolio: more USDT, some TUSD, some DAI, and some PAX.

We store our treasury assets in a Gnosis safe, and we use CoinShift to make our lives easier. We executed our first swap on Gnosis: USDC for DAI. Collier set it up and I confirmed it.

20 minutes later, it failed. We tried again. Same result.
So we tried using CoinShift. Same problem, over and over.

Two and a half hours after starting, we still had 0 (ZERO!) DAI in our treasury. And that was only the first of many transactions.

At that point we called one of our in-house Ethereum experts and asked him what he thought was happening. After some digging, he reported that swaps from Gnosis (or tools built on Gnosis) requires the price for the swap to remain the same between multiple signers. If the price changes in between initiation and confirmation of the second signer, the transaction fails.

Even though the swap is initiated, the order put in may no longer be valid based on the new market price.

Further complicating things, if a swap isn’t executed within ~5 minutes of initiation, it fails. When you’re dealing with crazy gas fluctuations and coordinating across multiple continents, this time window is more constraining than you’d think.

Of course, all of this is configurable, but the usability isn’t even close to what we needed to get through our strategy during this decade. Collier and I settled on transferring the USDC to a Trezor, executing the swap, and then sending the DAI back to the treasury safe.

The next day I had to fly from Texas to Italy, so Collier and I couldn’t continue working together. We decided to clone a Trezor so that we could check each other. Not exactly multisig, but safer than putting all the responsibility on a single person.

When I got home, we scheduled our next meeting. Three hours, just to be safe.

If you’ve ever seen the movie “Home Alone” you probably remember the hapless robbers being foiled at every turn by the imaginative kid. Well, that’s exactly what my next few sessions with Collier felt like.

Every session we were sure we’d reach our goal. Session after session, we failed. In the end we spent 44 hours executing Asan’s plan.

Once we moved the USDC to our Trezors, swapping them for other stablecoins was easy. We used Uniswap and Sushiswap. We would have used 1inch, but Collier couldn’t get to the site because he was in the US. Thank you SEC.

But then Asan wanted us to buy some ADA, some SOL, some MATIC, and some BTC. 😱

One thing I forgot to mention earlier was that our core team members didn’t want us to use a central exchange. “Keep it DeFi” he said. We tried.

We had a bunch of ERC-20 tokens. How were we going to get our hands on tokens from other chains without an exchange? And once we had them, where were we going to put them? Even though Gnosis is on multiple chains, it isn’t really multichain yet. If you are on a non-Eth chain and try to send assets to your Eth Gnosis safe, POOF, you’ve just lit those assets on fire with no chance of recovery.

We started with SOL and came up with a cunning plan.

Use Wormhole Bridge to wrap ETH to move it to Solana.

Use a Solana DEX to Swap wrapped ETH for SOL.

Use Wormhole Bridge to wrap SOL to move it to Ethereum.

Unfortunately, everything that could go wrong went wrong.

Wormhole Bridge didn’t work with a Trezor connected to Metamask, so we had to move tokens to Metamask.

Solflare no longer allowed my Ledger to sign transactions. No idea why that stopped working. So I had to move SOL directly to a Solflare native wallet.

Later I had to destroy the Solflare native wallet to re-attach my ledger. No problem, I had the seed phrase. But when I recreated the wallet using the seed phrase, I got different addresses. An address that held USD 30K of SOL was inaccessible to me.

I spent two hours trying to come up with a story that explained how I’d lost thirty thousand dollars without making me sound like a complete idiot. My dog was puzzled by my pacing until I asked myself if maybe this was a wallet bug. Time for a Hail Mary 🙏🏻. I created a Solet wallet with the seed phrase and lo, it worked! The wallet contained the original address, and I could access our SOL.


As one of my colleagues likes to say: “We’re so early.”

. Very elegant. As I type, the service seems to have disappeared, so now I wonder if we’ll ever be able to unwrap our ADA! Sigh.

Next, Asan wanted us to lend some tokens and borrow others. He showed us a lot of math to justify all this activity, but Collier and I didn’t care by that point. We were the executioners, the brawn of the operation. Whatever the brain wanted, we were going to deliver, even if it killed us.

Luckily all of the borrowing and lending only involved ERC-20 tokens. That’s not quite true. Some BTC was required, but by that point we knew he really meant wBTC 😉

So we headed over to Aave and got to work. Incredibly, (almost) nothing went wrong. Everything worked as planned, at least on my computer. On Collier's, nothing worked. We don’t know why. Having a cloned Trezor saved the day.


We left a few token buys for last: QRDO and BLOK. We looked for them on every DEX we knew, but couldn’t find them. Time to break the rules.

We found a centralized exchange in Asia that allowed us to signup with only an email address. Lack of KYC made it feel almost DEXish. After a few tests we decided it wasn’t a scam, and bought some QRDO and BLOK. BLOK lives on the Polygon network. Using a centralized exchange insulated us from the pain of moving things on and off of Polygon.

The very last thing on our list was staking the BLOK. We found the app to do that, but it had taken so long for us to get through our treasury management plan we found that all the BLOK staking pools were closed. Our BLOK remains unstaked.


Our treasury management strategy has two very specific goals:

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