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OnChain Wizard

OnChain Wizard

3 years ago

How to make a >800 million dollars in crypto attacking the once 3rd largest stablecoin, Soros style

Everyone is talking about the $UST attack right now, including Janet Yellen. But no one is talking about how much money the attacker made (or how brilliant it was). Lets dig in.

Our story starts in late March, when the Luna Foundation Guard (or LFG) starts buying BTC to help back $UST. LFG started accumulating BTC on 3/22, and by March 26th had a $1bn+ BTC position. This is leg #1 that made this trade (or attack) brilliant.

The second leg comes in the form of the 4pool Frax announcement for $UST on April 1st. This added the second leg needed to help execute the strategy in a capital efficient way (liquidity will be lower and then the attack is on).

We don't know when the attacker borrowed 100k BTC to start the position, other than that it was sold into Kwon's buying (still speculation). LFG bought 15k BTC between March 27th and April 11th, so lets just take the average price between these dates ($42k).


So you have a ~$4.2bn short position built. Over the same time, the attacker builds a $1bn OTC position in $UST. The stage is now set to create a run on the bank and get paid on your BTC short. In anticipation of the 4pool, LFG initially removes $150mm from 3pool liquidity.

The liquidity was pulled on 5/8 and then the attacker uses $350mm of UST to drain curve liquidity (and LFG pulls another $100mm of liquidity).

But this only starts the de-pegging (down to 0.972 at the lows). LFG begins selling $BTC to defend the peg, causing downward pressure on BTC while the run on $UST was just getting started.

With the Curve liquidity drained, the attacker used the remainder of their $1b OTC $UST position ($650mm or so) to start offloading on Binance. As withdrawals from Anchor turned from concern into panic, this caused a real de-peg as people fled for the exits

So LFG is selling $BTC to restore the peg while the attacker is selling $UST on Binance. Eventually the chain gets congested and the CEXs suspend withdrawals of $UST, fueling the bank run panic. $UST de-pegs to 60c at the bottom, while $BTC bleeds out.


The crypto community panics as they wonder how much $BTC will be sold to keep the peg. There are liquidations across the board and LUNA pukes because of its redemption mechanism (the attacker very well could have shorted LUNA as well). BTC fell 25% from $42k on 4/11 to $31.3k

So how much did our attacker make? There aren't details on where they covered obviously, but if they are able to cover (or buy back) the entire position at ~$32k, that means they made $952mm on the short.

On the $350mm of $UST curve dumps I don't think they took much of a loss, lets assume 3% or just $11m. And lets assume that all the Binance dumps were done at 80c, thats another $125mm cost of doing business. For a grand total profit of $815mm (bf borrow cost).

BTC was the perfect playground for the trade, as the liquidity was there to pull it off. While having LFG involved in BTC, and foreseeing they would sell to keep the peg (and prevent LUNA from dying) was the kicker.

Lastly, the liquidity being low on 3pool in advance of 4pool allowed the attacker to drain it with only $350mm, causing the broader panic in both BTC and $UST. Any shorts on LUNA would've added a lot of P&L here as well, with it falling -65% since 5/7.

And for the reply guys, yes I know a lot of this involves some speculation & assumptions. But a lot of money was made here either way, and I thought it would be cool to dive into how they did it.

More on Web3 & Crypto

Vitalik

Vitalik

3 years ago

Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)

When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.

Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.

However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?

Selling at below market-clearing prices has large inefficiencies and negative externalities

An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.

There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.

So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.

The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.

Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.

ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?

That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.

High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.

So why do sellers sometimes sell below market price?

Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.

Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.

Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.

But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.

This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?

Interesting solutions

It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?

Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.

1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.

2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).

3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.

4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.

5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:

Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.

With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?

Make the per-person allocation amount dynamic.

Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.

Here's another idea if you like clever game mechanics with fancy quadratic formulas.

Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.

The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.

One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.

The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!

Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.

Answers to possible questions

Q: Won't people who don't care about your project buy the item and immediately resell it?

A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.

Q: What if I want to make my item available to a specific community?

A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.

Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.

A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.

Jonathan Vanian

Jonathan Vanian

3 years ago

What is Terra? Your guide to the hot cryptocurrency

With cryptocurrencies like Bitcoin, Ether, and Dogecoin gyrating in value over the past few months, many people are looking at so-called stablecoins like Terra to invest in because of their more predictable prices.

Terraform Labs, which oversees the Terra cryptocurrency project, has benefited from its rising popularity. The company said recently that investors like Arrington Capital, Lightspeed Venture Partners, and Pantera Capital have pledged $150 million to help it incubate various crypto projects that are connected to Terra.

Terraform Labs and its partners have built apps that operate on the company’s blockchain technology that helps keep a permanent and shared record of the firm’s crypto-related financial transactions.

Here’s what you need to know about Terra and the company behind it.

What is Terra?

Terra is a blockchain project developed by Terraform Labs that powers the startup’s cryptocurrencies and financial apps. These cryptocurrencies include the Terra U.S. Dollar, or UST, that is pegged to the U.S. dollar through an algorithm.

Terra is a stablecoin that is intended to reduce the volatility endemic to cryptocurrencies like Bitcoin. Some stablecoins, like Tether, are pegged to more conventional currencies, like the U.S. dollar, through cash and cash equivalents as opposed to an algorithm and associated reserve token.

To mint new UST tokens, a percentage of another digital token and reserve asset, Luna, is “burned.” If the demand for UST rises with more people using the currency, more Luna will be automatically burned and diverted to a community pool. That balancing act is supposed to help stabilize the price, to a degree.

“Luna directly benefits from the economic growth of the Terra economy, and it suffers from contractions of the Terra coin,” Terraform Labs CEO Do Kwon said.

Each time someone buys something—like an ice cream—using UST, that transaction generates a fee, similar to a credit card transaction. That fee is then distributed to people who own Luna tokens, similar to a stock dividend.

Who leads Terra?

The South Korean firm Terraform Labs was founded in 2018 by Daniel Shin and Kwon, who is now the company’s CEO. Kwon is a 29-year-old former Microsoft employee; Shin now heads the Chai online payment service, a Terra partner. Kwon said many Koreans have used the Chai service to buy goods like movie tickets using Terra cryptocurrency.

Terraform Labs does not make money from transactions using its crypto and instead relies on outside funding to operate, Kwon said. It has raised $57 million in funding from investors like HashKey Digital Asset Group, Divergence Digital Currency Fund, and Huobi Capital, according to deal-tracking service PitchBook. The amount raised is in addition to the latest $150 million funding commitment announced on July 16.

What are Terra’s plans?

Terraform Labs plans to use Terra’s blockchain and its associated cryptocurrencies—including one pegged to the Korean won—to create a digital financial system independent of major banks and fintech-app makers. So far, its main source of growth has been in Korea, where people have bought goods at stores, like coffee, using the Chai payment app that’s built on Terra’s blockchain. Kwon said the company’s associated Mirror trading app is experiencing growth in China and Thailand.

Meanwhile, Kwon said Terraform Labs would use its latest $150 million in funding to invest in groups that build financial apps on Terra’s blockchain. He likened the scouting and investing in other groups as akin to a “Y Combinator demo day type of situation,” a reference to the popular startup pitch event organized by early-stage investor Y Combinator.

The combination of all these Terra-specific financial apps shows that Terraform Labs is “almost creating a kind of bank,” said Ryan Watkins, a senior research analyst at cryptocurrency consultancy Messari.

In addition to cryptocurrencies, Terraform Labs has a number of other projects including the Anchor app, a high-yield savings account for holders of the group’s digital coins. Meanwhile, people can use the firm’s associated Mirror app to create synthetic financial assets that mimic more conventional ones, like “tokenized” representations of corporate stocks. These synthetic assets are supposed to be helpful to people like “a small retail trader in Thailand” who can more easily buy shares and “get some exposure to the upside” of stocks that they otherwise wouldn’t have been able to obtain, Kwon said. But some critics have said the U.S. Securities and Exchange Commission may eventually crack down on synthetic stocks, which are currently unregulated.

What do critics say?

Terra still has a long way to go to catch up to bigger cryptocurrency projects like Ethereum.

Most financial transactions involving Terra-related cryptocurrencies have originated in Korea, where its founders are based. Although Terra is becoming more popular in Korea thanks to rising interest in its partner Chai, it’s too early to say whether Terra-related currencies will gain traction in other countries.

Terra’s blockchain runs on a “limited number of nodes,” said Messari’s Watkins, referring to the computers that help keep the system running. That helps reduce latency that may otherwise slow processing of financial transactions, he said.

But the tradeoff is that Terra is less “decentralized” than other blockchain platforms like Ethereum, which is powered by thousands of interconnected computing nodes worldwide. That could make Terra less appealing to some blockchain purists.

Vivek Singh

Vivek Singh

3 years ago

A Warm Welcome to Web3 and the Future of the Internet

Let's take a look back at the internet's history and see where we're going — and why.

Tim Berners Lee had a problem. He was at CERN, the world's largest particle physics factory, at the time. The institute's stated goal was to study the simplest particles with the most sophisticated scientific instruments. The institute completed the LEP Tunnel in 1988, a 27 kilometer ring. This was Europe's largest civil engineering project (to study smaller particles — electrons).

The problem Tim Berners Lee found was information loss, not particle physics. CERN employed a thousand people in 1989. Due to team size and complexity, people often struggled to recall past project information. While these obstacles could be overcome, high turnover was nearly impossible. Berners Lee addressed the issue in a proposal titled ‘Information Management'.

When a typical stay is two years, data is constantly lost. The introduction of new people takes a lot of time from them and others before they understand what is going on. An emergency situation may require a detective investigation to recover technical details of past projects. Often, the data is recorded but cannot be found. — Information Management: A Proposal

He had an idea. Create an information management system that allowed users to access data in a decentralized manner using a new technology called ‘hypertext'.
To quote Berners Lee, his proposal was “vague but exciting...”. The paper eventually evolved into the internet we know today. Here are three popular W3C standards used by billions of people today:


(credit: CERN)

HTML (Hypertext Markup)

A web formatting language.

URI (Unique Resource Identifier)

Each web resource has its own “address”. Known as ‘a URL'.

HTTP (Hypertext Transfer Protocol)

Retrieves linked resources from across the web.

These technologies underpin all computer work. They were the seeds of our quest to reorganize information, a task as fruitful as particle physics.

Tim Berners-Lee would probably think the three decades from 1989 to 2018 were eventful. He'd be amazed by the billions, the inspiring, the novel. Unlocking innovation at CERN through ‘Information Management'.
The fictional character would probably need a drink, walk, and a few deep breaths to fully grasp the internet's impact. He'd be surprised to see a few big names in the mix.

Then he'd say, "Something's wrong here."

We should review the web's history before going there. Was it a success after Berners Lee made it public? Web1 and Web2: What is it about what we are doing now that so many believe we need a new one, web3?

Per Outlier Ventures' Jamie Burke:

Web 1.0 was read-only.
Web 2.0 was the writable
Web 3.0 is a direct-write web.

Let's explore.

Web1: The Read-Only Web

Web1 was the digital age. We put our books, research, and lives ‘online'. The web made information retrieval easier than any filing cabinet ever. Massive amounts of data were stored online. Encyclopedias, medical records, and entire libraries were put away into floppy disks and hard drives.

In 2015, the web had around 305,500,000,000 pages of content (280 million copies of Atlas Shrugged).

Initially, one didn't expect to contribute much to this database. Web1 was an online version of the real world, but not yet a new way of using the invention.

One gets the impression that the web has been underutilized by historians if all we can say about it is that it has become a giant global fax machine. — Daniel Cohen, The Web's Second Decade (2004)

That doesn't mean developers weren't building. The web was being advanced by great minds. Web2 was born as technology advanced.

Web2: Read-Write Web

Remember when you clicked something on a website and the whole page refreshed? Is it too early to call the mid-2000s ‘the good old days'?
Browsers improved gradually, then suddenly. AJAX calls augmented CGI scripts, and applications began sending data back and forth without disrupting the entire web page. One button to ‘digg' a post (see below). Web experiences blossomed.

In 2006, Digg was the most active ‘Web 2.0' site. (Photo: Ethereum Foundation Taylor Gerring)

Interaction was the focus of new applications. Posting, upvoting, hearting, pinning, tweeting, liking, commenting, and clapping became a lexicon of their own. It exploded in 2004. Easy ways to ‘write' on the internet grew, and continue to grow.

Facebook became a Web2 icon, where users created trillions of rows of data. Google and Amazon moved from Web1 to Web2 by better understanding users and building products and services that met their needs.

Business models based on Software-as-a-Service and then managing consumer data within them for a fee have exploded.

Web2 Emerging Issues

Unbelievably, an intriguing dilemma arose. When creating this read-write web, a non-trivial question skirted underneath the covers. Who owns it all?

You have no control over [Web 2] online SaaS. People didn't realize this because SaaS was so new. People have realized this is the real issue in recent years.

Even if these organizations have good intentions, their incentive is not on the users' side.
“You are not their customer, therefore you are their product,” they say. With Laura Shin, Vitalik Buterin, Unchained

A good plot line emerges. Many amazing, world-changing software products quietly lost users' data control.
For example: Facebook owns much of your social graph data. Even if you hate Facebook, you can't leave without giving up that data. There is no ‘export' or ‘exit'. The platform owns ownership.

While many companies can pull data on you, you cannot do so.

On the surface, this isn't an issue. These companies use my data better than I do! A complex group of stakeholders, each with their own goals. One is maximizing shareholder value for public companies. Tim Berners-Lee (and others) dislike the incentives created.

“Show me the incentive and I will show you the outcome.” — Berkshire Hathaway's CEO

It's easy to see what the read-write web has allowed in retrospect. We've been given the keys to create content instead of just consume it. On Facebook and Twitter, anyone with a laptop and internet can participate. But the engagement isn't ours. Platforms own themselves.

Web3: The ‘Unmediated’ Read-Write Web

Tim Berners Lee proposed a decade ago that ‘linked data' could solve the internet's data problem.

However, until recently, the same principles that allowed the Web of documents to thrive were not applied to data...

The Web of Data also allows for new domain-specific applications. Unlike Web 2.0 mashups, Linked Data applications work with an unbound global data space. As new data sources appear on the Web, they can provide more complete answers.

At around the same time as linked data research began, Satoshi Nakamoto created Bitcoin. After ten years, it appears that Berners Lee's ideas ‘link' spiritually with cryptocurrencies.

What should Web 3 do?

Here are some quick predictions for the web's future.

Users' data:
Users own information and provide it to corporations, businesses, or services that will benefit them.

Defying censorship:

No government, company, or institution should control your access to information (1, 2, 3)

Connect users and platforms:

Create symbiotic rather than competitive relationships between users and platform creators.

Open networks:

“First, the cryptonetwork-participant contract is enforced in open source code. Their voices and exits are used to keep them in check.” Dixon, Chris (4)

Global interactivity:

Transacting value, information, or assets with anyone with internet access, anywhere, at low cost

Self-determination:

Giving you the ability to own, see, and understand your entire digital identity.

Not pull, push:

‘Push' your data to trusted sources instead of ‘pulling' it from others.

Where Does This Leave Us?

Change incentives, change the world. Nick Babalola

People believe web3 can help build a better, fairer system. This is not the same as equal pay or outcomes, but more equal opportunity.

It should be noted that some of these advantages have been discussed previously. Will the changes work? Will they make a difference? These unanswered questions are technical, economic, political, and philosophical. Unintended consequences are likely.

We hope Web3 is a more democratic web. And we think incentives help the user. If there’s one thing that’s on our side, it’s that open has always beaten closed, given a long enough timescale.

We are at the start. 

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Jano le Roux

Jano le Roux

3 years ago

Never Heard Of: The Apple Of Email Marketing Tools

Unlimited everything for $19 monthly!?

Flodesk

Even with pretty words, no one wants to read an ugly email.

  • Not Gen Z

  • Not Millennials

  • Not Gen X

  • Not Boomers

I am a minimalist.

I like Mozart. I like avos. I love Apple.

When I hear seamlessly, effortlessly, or Apple's new adverb fluidly, my toes curl.

No email marketing tool gave me that feeling.

As a marketing consultant helping high-growth brands create marketing that doesn't feel like marketing, I've worked with every email marketing platform imaginable, including that naughty monkey and the expensive platform whose sales teams don't stop calling.

Most email marketing platforms are flawed.

  1. They are overpriced.

  2. They use dreadful templates.

  3. They employ a poor visual designer.

  4. The user experience there is awful.

  5. Too many useless buttons are present. (Similar to the TV remote!)

I may have finally found the perfect email marketing tool. It creates strong flows. It helps me focus on storytelling.

It’s called Flodesk.

It’s effortless. It’s seamless. It’s fluid.

Here’s why it excites me.

Unlimited everything for $19 per month

Sends unlimited. Emails unlimited. Signups unlimited.

Most email platforms penalize success.

Pay for performance?

  • $87 for 10k contacts

  • $605 for 100K contacts

  • $1,300+ for 200K contacts

In the 1990s, this made sense, but not now. It reminds me of when ISPs capped internet usage at 5 GB per month.

Flodesk made unlimited email for a low price a reality. Affordable, attractive email marketing isn't just for big companies.

Flodesk doesn't penalize you for growing your list. Price stays the same as lists grow.

Flodesk plans cost $38 per month, but I'll give you a 30-day trial for $19.

Amazingly strong flows

Foster different people's flows.

Email marketing isn't one-size-fits-all.

Different times require different emails.

People don't open emails because they're irrelevant, in my experience. A colder audience needs a nurturing sequence.

Flodesk automates your email funnels so top-funnel prospects fall in love with your brand and values before mid- and bottom-funnel email flows nudge them to take action.

I wish I could save more custom audience fields to further customize the experience.

Dynamic editor

Easy. Effortless.

Flodesk's editor is Apple-like.

You understand how it works almost instantly.

Like many Apple products, it's intentionally limited. No distractions. You can focus on emotional email writing.

Flodesk

Flodesk's inability to add inline HTML to emails is my biggest issue with larger projects. I wish I could upload HTML emails.

Simple sign-up procedures

Dream up joining.

I like how easy it is to create conversion-focused landing pages. Linkly lets you easily create 5 landing pages and A/B test messaging.

Flodesk

I like that you can use signup forms to ask people what they're interested in so they get relevant emails instead of mindless mass emails nobody opens.

Flodesk

I love how easy it is to embed in-line on a website.

Wonderful designer templates

Beautiful, connecting emails.

Flodesk has calm email templates. My designer's eye felt at rest when I received plain text emails with big impacts.

Flodesk

As a typography nerd, I love Flodesk's handpicked designer fonts. It gives emails a designer feel that is hard to replicate on other platforms without coding and custom font licenses.

Small adjustments can have a big impact

Details matter.

Flodesk remembers your brand colors. Flodesk automatically adds your logo and social handles to emails after signup.

Flodesk uses Zapier. This lets you send emails based on a user's action.

A bad live chat can trigger a series of emails to win back a customer.

Flodesk isn't for everyone.

Flodesk is great for Apple users like me.

Mike Tarullo

Mike Tarullo

3 years ago

Even In a Crazy Market, Hire the Best People: The "First Ten" Rules

The Pareto Principle is a way of life for First Ten people.

Hiring is difficult, but you shouldn't compromise on team members. Or it may suggest you need to look beyond years in a similar role/function.

Every hire should be someone we'd want as one of our first ten employees.

If you hire such people, your team will adapt, initiate, and problem-solve, and your company will grow. You'll stay nimble even as you scale, and you'll learn from your colleagues.

If you only hire for a specific role or someone who can execute the job, you'll become a cluster of optimizers, and talent will depart for a more fascinating company. A startup is continually changing, therefore you want individuals that embrace it.

As a leader, establishing ideal conditions for talent and having a real ideology should be high on your agenda. You can't eliminate attrition, nor would you want to, but you can hire people who will become your company's leaders.

In my last four jobs I was employee 2, 5, 3, and 5. So while this is all a bit self serving, you’re the one reading my writing — and I have some experience with who works out in the first ten!

First, we'll examine what they do well (and why they're beneficial for startups), then what they don't, and how to hire them.

First 10 are:

  • Business partners: Because it's their company, they take care of whatever has to be done and have ideas about how to do it. You can rely on them to always put the success of the firm first because it is their top priority (company success is strongly connected with success for early workers). This approach will eventually take someone to leadership positions.

  • High Speed Learners: They process knowledge quickly and can reach 80%+ competency in a new subject matter rather quickly. A growing business that is successful tries new things frequently. We have all lost a lot of money and time on employees who follow the wrong playbook or who wait for someone else within the company to take care of them.

  • Autodidacts learn by trial and error, osmosis, networking with others, applying first principles, and reading voraciously (articles, newsletters, books, and even social media). Although teaching is wonderful, you won't have time.

  • Self-scaling: They figure out a means to deal with issues and avoid doing the grunt labor over the long haul, increasing their leverage. Great people don't keep doing the same thing forever; as they expand, they use automation and delegation to fill in their lower branches. This is a crucial one; even though you'll still adore them, you'll have to manage their scope or help them learn how to scale on their own.

  • Free Range: You can direct them toward objectives rather than specific chores. Check-ins can be used to keep them generally on course without stifling invention instead of giving them precise instructions because doing so will obscure their light.

  • When people are inspired, they bring their own ideas about what a firm can be and become animated during discussions about how to get there.

  • Novelty Seeking: They look for business and personal growth chances. Give them fresh assignments and new directions to follow around once every three months.


Here’s what the First Ten types may not be:

  • Domain specialists. When you look at their resumes, you'll almost certainly think they're unqualified. Fortunately, a few strategically positioned experts may empower a number of First Ten types by serving on a leadership team or in advising capacities.

  • Balanced. These people become very invested, and they may be vulnerable to many types of stress. You may need to assist them in managing their own stress and coaching them through obstacles. If you are reading this and work at Banza, I apologize for not doing a better job of supporting this. I need to be better at it.

  • Able to handle micromanagement with ease. People who like to be in charge will suppress these people. Good decision-making should be delegated to competent individuals. Generally speaking, if you wish to scale.

Great startup team members have versatility, learning, innovation, and energy. When we hire for the function, not the person, we become dull and staid. Could this person go to another department if needed? Could they expand two levels in a few years?

First Ten qualities and experience level may have a weak inverse association. People with 20+ years of experience who had worked at larger organizations wanted to try something new and had a growth mentality. College graduates may want to be told what to do and how to accomplish it so they can stay in their lane and do what their management asks.

Does the First Ten archetype sound right for your org? Cool, let’s go hiring. How will you know when you’ve found one?

  • They exhibit adaptive excellence, excelling at a variety of unrelated tasks. It could be hobbies or professional talents. This suggests that they will succeed in the next several endeavors they pursue.

  • Successful risk-taking is doing something that wasn't certain to succeed, sometimes more than once, and making it do so. It's an attitude.

  • Rapid Rise: They regularly change roles and get promoted. However, they don't leave companies when the going gets tough. Look for promotions at every stop and at least one position with three or more years of experience.

You can ask them:

  • Tell me about a time when you started from scratch or achieved success. What occurred en route? You might request a variety of tales from various occupations or even aspects of life. They ought to be energized by this.

  • What new skills have you just acquired? It is not required to be work-related. They must be able to describe it and unintentionally become enthusiastic about it.

  • Tell me about a moment when you encountered a challenge and had to alter your strategy. The core of a startup is reinventing itself when faced with obstacles.

  • Tell me about a moment when you eliminated yourself from a position at work. They've demonstrated they can permanently solve one issue and develop into a new one, as stated above.

  • Why do you want to leave X position or Y duty? These people ought to be moving forward, not backward, all the time. Instead, they will discuss what they are looking forward to visiting your location.

  • Any questions? Due to their inherent curiosity and desire to learn new things, they should practically never run out of questions. You can really tell if they are sufficiently curious at this point.

People who see their success as being the same as the success of the organization are the best-case team members, in any market. They’ll grow and change with the company, and always try to prioritize what matters. You’ll find yourself more energized by your work because you’re surrounded by others who are as well. Happy teambuilding!

Pat Vieljeux

Pat Vieljeux

3 years ago

In 5 minutes, you can tell if a startup will succeed.

Or the “lie to me” method.

I can predict a startup's success in minutes.

Just interview its founder.

Ask "why?"

I question "why" till I sense him.

I need to feel the person I have in front of me. I need to know if he or she can deliver. Startups aren't easy. Without abilities, a brilliant idea will fail.

Good entrepreneurs have these qualities: He's a leader, determined, and resilient.

For me, they can be split in two categories.

The first entrepreneur aspires to live meaningfully. The second wants to get rich. The second is communicative. He wants to wow the crowd. He's motivated by the thought of one day sailing a boat past palm trees and sunny beaches.

What drives the first entrepreneur is evident in his speech, face, and voice. He will not speak about his product. He's (nearly) uninterested. He's not selling anything. He's not a salesman. He wants to succeed. The product is his fuel.

He'll explain his decision. He'll share his motivations. His desire. And he'll use meaningful words.

Paul Ekman has shown that face expressions aren't cultural. His study influenced the American TV series "lie to me" about body language and speech.

Passionate entrepreneurs are obvious. It's palpable. Faking passion is tough. Someone who wants your favor and money will expose his actual motives through his expressions and language.

The good liar will be able to fool you for a while, but not for long if you pay attention to his body language and how he expresses himself.

And also, if you look at his business plan.

His business plan reveals his goals. Read between the lines.

Entrepreneur 1 will focus on his "why", whereas Entrepreneur 2 will focus on the "how".

Entrepreneur 1 will develop a vision-driven culture.

The second, on the other hand, will focus on his EBITDA.

Why is the culture so critical? Because it will allow entrepreneur 1 to develop a solid team that can tackle his problems and trials. His team's "why" will keep them together in tough times.

"Give me a terrific start-up team with a mediocre idea over a weak one any day." Because a great team knows when to pivot and trusts each other. Weak teams fail.” — Bernhard Schroeder

Closings thoughts

Every VC must ask Why. Entrepreneur's motivations. This "why" will create the team's culture. This culture will help the team adjust to any setback.