Sam Bankman Fried (SDBF) is a legendary con man. But the NYT might not tell you that...

Since SBF's empire was revealed to be a lie, mainstream news organizations and commentators have failed to give readers a straightforward assessment. The New York Times and Wall Street Journal have uncovered many key facts about the scandal, but they have also soft-peddled Bankman-Fried's intent and culpability.

It's clear that the FTX crypto exchange and Alameda Research committed fraud to steal money from users and investors. That’s why a recent New York Times interview was widely derided for seeming to frame FTX’s collapse as the result of mismanagement rather than malfeasance. A Wall Street Journal article lamented FTX's loss of charitable donations, bolstering Bankman's philanthropic pose. Matthew Yglesias, court chronicler of the neoliberal status quo, seemed to whitewash his own entanglements by crediting SBF's money with helping Democrats in 2020 – sidestepping the likelihood that the money was embezzled.

Many outlets have called what happened to FTX a "bank run" or a "run on deposits," but Bankman-Fried insists the company was overleveraged and disorganized. Both attempts to frame the fallout obscure the core issue: customer funds misused.

Because banks lend customer funds to generate returns, they can experience "bank runs." If everyone withdraws at once, they can experience a short-term cash crunch but there won't be a long-term problem.

Crypto exchanges like FTX aren't banks. They don't do bank-style lending, so a withdrawal surge shouldn't strain liquidity. FTX promised customers it wouldn't lend or use their crypto.

Alameda's balance sheet blurs SBF's crypto empire.

The funds were sent to Alameda Research, where they were apparently gambled away. This is massive theft. According to a bankruptcy document, up to 1 million customers could be affected.

In less than a month, reporting and the bankruptcy process have uncovered a laundry list of decisions and practices that would constitute financial fraud if FTX had been a U.S.-regulated entity, even without crypto-specific rules. These ploys may be litigated in U.S. courts if they enabled the theft of American property.

The list is very, very long.

The many crimes of Sam Bankman-Fried and FTX

At the heart of SBF's fraud are the deep and (literally) intimate ties between FTX and Alameda Research, a hedge fund he co-founded. An exchange makes money from transaction fees on user assets, but Alameda trades and invests its own funds.

Bankman-Fried called FTX and Alameda "wholly separate" and resigned as Alameda's CEO in 2019. The two operations were closely linked. Bankman-Fried and Alameda CEO Caroline Ellison were romantically linked.

These circumstances enabled SBF's sin.  Within days of FTX's first signs of weakness, it was clear the exchange was funneling customer assets to Alameda for trading, lending, and investing. Reuters reported on Nov. 12 that FTX sent $10 billion to Alameda. As much as $2 billion was believed to have disappeared after being sent to Alameda. Now the losses look worse.

It's unclear why those funds were sent to Alameda or when Bankman-Fried betrayed his depositors. On-chain analysis shows most FTX to Alameda transfers occurred in late 2021, and bankruptcy filings show both lost $3.7 billion in 2021.

SBF's companies lost millions before the 2022 crypto bear market. They may have stolen funds before Terra and Three Arrows Capital, which killed many leveraged crypto players.

FTT loans and prints

CoinDesk's report on Alameda's FTT holdings ignited FTX and Alameda Research. FTX created this instrument, but only a small portion was traded publicly; FTX and Alameda held the rest. These holdings were illiquid, meaning they couldn't be sold at market price. Bankman-Fried valued its stock at the fictitious price.

FTT tokens were reportedly used as collateral for loans, including FTX loans to Alameda. Close ties between FTX and Alameda made the FTT token harder or more expensive to use as collateral, reducing the risk to customer funds.

This use of an internal asset as collateral for loans between clandestinely related entities is similar to Enron's 1990s accounting fraud. These executives served 12 years in prison.

Alameda's margin liquidation exemption

Alameda Research had a "secret exemption" from FTX's liquidation and margin trading rules, according to legal filings by FTX's new CEO.

FTX, like other crypto platforms and some equity or commodity services, offered "margin" or loans for trades. These loans are usually collateralized, meaning borrowers put up other funds or assets. If a margin trade loses enough money, the exchange will sell the user's collateral to pay off the initial loan.

Keeping asset markets solvent requires liquidating bad margin positions. Exempting Alameda would give it huge advantages while exposing other FTX users to hidden risks. Alameda could have kept losing positions open while closing out competitors. Alameda could lose more on FTX than it could pay back, leaving a hole in customer funds.

The exemption is criminal in multiple ways. FTX was fraudulently marketed overall. Instead of a level playing field, there were many customers.

Above them all, with shotgun poised, was Alameda Research.

Alameda front-running FTX listings

Argus says there's circumstantial evidence that Alameda Research had insider knowledge of FTX's token listing plans. Alameda was able to buy large amounts of tokens before the listing and sell them after the price bump.

If true, these claims would be the most brazenly illegal of Alameda and FTX's alleged shenanigans. Even if the tokens aren't formally classified as securities, insider trading laws may apply.

In a similar case this year, an OpenSea employee was charged with wire fraud for allegedly insider trading. This employee faces 20 years in prison for front-running monkey JPEGs.

Huge loans to executives

Alameda Research reportedly lent FTX executives $4.1 billion, including massive personal loans. Bankman-Fried received $1 billion in personal loans and $2.3 billion for an entity he controlled, Paper Bird. Nishad Singh, director of engineering, was given $543 million, and FTX Digital Markets co-CEO Ryan Salame received $55 million.

FTX has more smoking guns than a Texas shooting range, but this one is the smoking bazooka – a sign of criminal intent. It's unclear how most of the personal loans were used, but liquidators will have to recoup the money.

The loans to Paper Bird were even more worrisome because they created another related third party to shuffle assets. Forbes speculates that some Paper Bird funds went to buy Binance's FTX stake, and Paper Bird committed hundreds of millions to outside investments.

FTX Inner Circle: Who's Who

That included many FTX-backed VC funds. Time will tell if this financial incest was criminal fraud. It fits Bankman-pattern Fried's of using secret flows, leverage, and funny money to inflate asset prices.

FTT or loan 'bailouts'

Also. As the crypto bear market continued in 2022, Bankman-Fried proposed bailouts for bankrupt crypto lenders BlockFi and Voyager Digital. CoinDesk was among those deceived, welcoming SBF as a J.P. Morgan-style sector backstop.

In a now-infamous interview with CNBC's "Squawk Box," Bankman-Fried referred to these decisions as bets that may or may not pay off.

But maybe not. Bloomberg's Matt Levine speculated that FTX backed BlockFi with FTT money. This Monopoly bailout may have been intended to hide FTX and Alameda liabilities that would have been exposed if BlockFi went bankrupt sooner. This ploy has no name, but it echoes other corporate frauds.

Secret bank purchase

Alameda Research invested $11.5 million in the tiny Farmington State Bank, doubling its net worth. As a non-U.S. entity and an investment firm, Alameda should have cleared regulatory hurdles before acquiring a U.S. bank.

In the context of FTX, the bank's stake becomes "ominous." Alameda and FTX could have done more shenanigans with bank control. Compare this to the Bank for Credit and Commerce International's failed attempts to buy U.S. banks. BCCI was even nefarious than FTX and wanted to buy U.S. banks to expand its money-laundering empire.

The mainstream's mistakes

These are complex and nuanced forms of fraud that echo traditional finance models. This obscurity helped Bankman-Fried masquerade as an honest player and likely kept coverage soft after the collapse.

Bankman-Fried had a scruffy, nerdy image, like Mark Zuckerberg and Adam Neumann. In interviews, he spoke nonsense about an industry full of jargon and complicated tech. Strategic donations and insincere ideological statements helped him gain political and social influence.

SBF' s'Effective' Altruism Blew Up FTX

Bankman-Fried has continued to muddy the waters with disingenuous letters, statements, interviews, and tweets since his con collapsed. He's tried to portray himself as a well-intentioned but naive kid who made some mistakes. This is a softer, more pernicious version of what Trump learned from mob lawyer Roy Cohn. Bankman-Fried doesn't "deny, deny, deny" but "confuse, evade, distort."

It's mostly worked. Kevin O'Leary, who plays an investor on "Shark Tank," repeats Bankman-SBF's counterfactuals.  O'Leary called Bankman-Fried a "savant" and "probably one of the most accomplished crypto traders in the world" in a Nov. 27 interview with Business Insider, despite recent data indicating immense trading losses even when times were good.

O'Leary's status as an FTX investor and former paid spokesperson explains his continued affection for Bankman-Fried despite contradictory evidence. He's not the only one promoting Bankman-Fried. The disgraced son of two Stanford law professors will defend himself at Wednesday's DealBook Summit.

SBF's fraud and theft rival those of Bernie Madoff and Jho Low. Whether intentionally or through malign ineptitude, the fraud echoes Worldcom and Enron.

The Perverse Impacts of Anti-Money-Laundering

The principals in all of those scandals wound up either sentenced to prison or on the run from the law. Sam Bankman-Fried clearly deserves to share their fate.

Read the full article here.

Blockchain validates transactions with consensus algorithms. Bitcoin and Ethereum use Proof-of-Work, while Polkadot and Cardano use Proof-of-Stake.

Other consensus protocols are used to verify transactions besides these two. This post focuses on Proof-of-Time (PoT), used by Analog, and Proof-of-History (PoH), used by Solana as a hybrid consensus protocol.

PoT and PoH may seem similar to users, but they are actually very different protocols.

Proof-of-Time (PoT)

Analog developed Proof-of-Time (PoT) based on Delegated Proof-of-Stake (DPoS). Users select "delegates" to validate the next block in DPoS. PoT uses a ranking system, and validators stake an equal amount of tokens. Validators also "self-select" themselves via a verifiable random function."

The ranking system gives network validators a performance score, with trustworthy validators with a long history getting higher scores. System also considers validator's fixed stake. PoT's ledger is called "Timechain."

Voting on delegates borrows from DPoS, but there are changes. PoT's first voting stage has validators (or "time electors" putting forward a block to be included in the ledger).

Validators are chosen randomly based on their ranking score and fixed stake. One validator is chosen at a time using a Verifiable Delay Function (VDF).

Validators use a verifiable delay function to determine if they'll propose a Timechain block. If chosen, they validate the transaction and generate a VDF proof before submitting both to other Timechain nodes.

This leads to the second process, where the transaction is passed through 1,000 validators selected using the same method. Each validator checks the transaction to ensure it's valid.

If the transaction passes, validators accept the block, and if over 2/3 accept it, it's added to the Timechain.

Proof-of-History (PoH)

Proof-of-History is a consensus algorithm that proves when a transaction occurred. PoH uses a VDF to verify transactions, like Proof-of-Time. Similar to Proof-of-Work, VDFs use a lot of computing power to calculate but little to verify transactions, similar to (PoW).

This shows users and validators how long a transaction took to verify.

PoH uses VDFs to verify event intervals. This process uses cryptography to prevent determining output from input.

The outputs of one transaction are used as inputs for the next. Timestamps record the inputs' order. This checks if data was created before an event.

PoT vs. PoH

PoT and PoH differ in that:

• PoT uses VDFs to select validators (or time electors), while PoH measures time between events.

• PoH uses a VDF to validate transactions, while PoT uses a ranking system.

• PoT's VDF-elected validators verify transactions proposed by a previous validator. PoH uses a VDF to validate transactions and data.

Conclusion

Both Proof-of-Time (PoT) and Proof-of-History (PoH) validate blockchain transactions differently. PoT uses a ranking system to randomly select validators to verify transactions.

PoH uses a Verifiable Delay Function to validate transactions, verify how much time has passed between two events, and allow validators to quickly verify a transaction without malicious actors knowing the input.

Unexpected Success

Shopify CEO and co-founder Tobias Lutke. Shopify is worth $48 billion.

World-renowned entrepreneur Tobi

Tobi never expected his first online snowboard business to become a multimillion-dollar software corporation.

Tobi founded Shopify to establish a 20-person company.

The publicly traded corporation employs over 10,000 people.

Here's Tobi Lutke's incredible story.

Elon Musk tweeted his admiration for the Shopify creator.

30-October-2019.

Musk praised Shopify founder Tobi Lutke on Twitter.

Happened:

Explore this programmer's journey.

What difficulties did Tobi experience as a young child?

Germany raised Tobi.

Tobi's parents realized he was smart but had trouble learning as a toddler.

Tobi was learning disabled.

Tobi struggled with school tests.

Tobi's learning impairments were undiagnosed.

Tobi struggled to read as a dyslexic.

Tobi also found school boring.

Germany's curriculum didn't inspire Tobi's curiosity.

“The curriculum in Germany was taught like here are all the solutions you might find useful later in life, spending very little time talking about the problem…If I don’t understand the problem I’m trying to solve, it’s very hard for me to learn about a solution to a problem.”

Studying computer programming

After tenth grade, Tobi decided school wasn't for him and joined a German apprenticeship program.

This curriculum taught Tobi software engineering.

He was an apprentice in a small Siemens subsidiary team.

Tobi worked with rebellious Siemens employees.

Team members impressed Tobi.

Tobi joined the team for this reason.

Tobi was pleased to get paid to write programming all day.

His life could not have been better.

Devoted to snowboarding

Tobi loved snowboarding.

He drove 5 hours to ski at his folks' house.

His friends traveled to the US to snowboard when he was older.

However, the cheap dollar conversion rate led them to Canada.

2000.

Tobi originally decided to snowboard instead than ski.

Snowboarding captivated him in Canada.

On the trip to Canada, Tobi encounters his wife.

Tobi meets his wife Fiona McKean on his first Canadian ski trip.

They maintained in touch after the trip.

Fiona moved to Germany after graduating.

Tobi was a startup coder.

Fiona found work in Germany.

Her work included editing, writing, and academics.

“We lived together for 10 months and then she told me that she need to go back for the master's program.”

With Fiona, Tobi immigrated to Canada.

Fiona invites Tobi.

Tobi agreed to move to Canada.

Programming helped Tobi move in with his girlfriend.

Tobi was an excellent programmer, therefore what he did in Germany could be done anywhere.

He worked remotely for his German employer in Canada.

Tobi struggled with remote work.

Due to poor communication.

No slack, so he used email.

Programmers had trouble emailing.

Tobi's startup was developing a browser.

After the dot-com crash, individuals left that startup.

It ended.

Tobi didn't intend to work for any major corporations.

Tobi left his startup.

He believed he had important skills for any huge corporation.

He refused to join a huge corporation.

Because of Siemens.

Tobi learned to write professional code and about himself while working at Siemens in Germany.

Siemens culture was odd.

Employees were distrustful.

Siemens' rigorous dress code implies that the corporation doesn't trust employees' attire.

It wasn't Tobi's place.

“There was so much bad with it that it just felt wrong…20-year-old Tobi would not have a career there.”

Focused only on snowboarding

Tobi lived in Ottawa with his girlfriend.

Canada is frigid in winter.

Ottawa's winters last.

Almost half a year.

Tobi wanted to do something worthwhile now.

So he snowboarded.

Tobi began snowboarding seriously.

He sought every snowboarding knowledge.

He researched the greatest snowboarding gear first.

He created big spreadsheets for snowboard-making technologies.

Tobi grew interested in selling snowboards while researching.

He intended to sell snowboards online.

He had no choice but to start his own company.

A small local company offered Tobi a job.

Interested.

He must sign papers to join the local company.

He needed a work permit when he signed the documents.

Tobi had no work permit.

He was allowed to stay in Canada while applying for permanent residency.

“I wasn’t illegal in the country, but my state didn’t give me a work permit. I talked to a lawyer and he told me it’s going to take a while until I get a permanent residency.”

Tobi's lawyer told him he cannot get a work visa without permanent residence.

His lawyer said something else intriguing.

Tobis lawyer advised him to start a business.

Tobi declined this local company's job offer because of this.

Tobi considered opening an internet store with his technical skills.

He sold snowboards online.

“I was thinking of setting up an online store software because I figured that would exist and use it as a way to sell snowboards…make money while snowboarding and hopefully have a good life.”

What brought Tobi and his co-founder together, and how did he support Tobi?

Tobi lived with his girlfriend's parents.

In Ottawa, Tobi encounters Scott Lake.

Scott was Tobis girlfriend's family friend and worked for Tobi's future employer.

Scott and Tobi snowboarded.

Tobi pitched Scott his snowboard sales software idea.

Scott liked the idea.

They planned a business together.

“I was looking after the technology and Scott was dealing with the business side…It was Scott who ended up developing relationships with vendors and doing all the business set-up.”

Issues they ran into when attempting to launch their business online

Neither could afford a long-term lease.

That prompted their online business idea.

They would open a store.

Tobi anticipated opening an internet store in a week.

Tobi seeks open-source software.

Most existing software was pricey.

Tobi and Scott couldn't afford pricey software.

“In 2004, I was sitting in front of my computer absolutely stunned realising that we hadn’t figured out how to create software for online stores.”

They required software to:

• to upload snowboard images to the website.

• people to look up the types of snowboards that were offered on the website. There must be a search feature in the software.

• Online users transmit payments, and the merchant must receive them.

• notifying vendors of the recently received order.

No online selling software existed at the time.

Online credit card payments were difficult.

How did they advance the software while keeping expenses down?

Tobi and Scott needed money to start selling snowboards.

Tobi and Scott funded their firm with savings.

“We both put money into the company…I think the capital we had was around CAD 20,000(Canadian Dollars).”

Despite investing their savings.

They minimized costs.

They tried to conserve.

No office rental.

They worked in several coffee shops.

Tobi lived rent-free at his girlfriend's parents.

He installed software in coffee cafes.

How were the software issues handled?

Tobi found no online snowboard sales software.

Two choices remained:

1. Change your mind and try something else.

2. Use his programming expertise to produce something that will aid in the expansion of this company.

Tobi knew he was the sole programmer working on such a project from the start.

“I had this realisation that I’m going to be the only programmer who has ever worked on this, so I don’t have to choose something that lots of people know. I can choose just the best tool for the job…There is been this programming language called Ruby which I just absolutely loved ”

Ruby was open-source and only had Japanese documentation.

Latin is the source code.

Tobi used Ruby twice.

He assumed he could pick the tool this time.

Why not build with Ruby?

How did they find their first time operating a business?

Tobi writes applications in Ruby.

He wrote the initial software version in 2.5 months.

Tobi and Scott founded Snowdevil to sell snowboards.

Tobi coded for 16 hours a day.

His lifestyle was unhealthy.

He enjoyed pizza and coke.

“I would never recommend this to anyone, but at the time there was nothing more interesting to me in the world.”

Their initial purchase and encounter with it

Tobi worked in cafes then.

“I was working in a coffee shop at this time and I remember everything about that day…At some time, while I was writing the software, I had to type the email that the software would send to tell me about the order.”

Tobi recalls everything.

He checked the order on his laptop at the coffee shop.

Pennsylvanian ordered snowboard.

Tobi walked home and called Scott. Tobi told Scott their first order.

They loved the order.

How were people made aware about Snowdevil?

2004 was very different.

Tobi and Scott attempted simple website advertising.

Google AdWords was new.

Ad clicks cost 20 cents.

Online snowboard stores were scarce at the time.

Google ads propelled the snowdevil brand.

Snowdevil prospered.

They swiftly recouped their original investment in the snowboard business because to its high profit margin.

Tobi and Scott struggled with inventories.

“Snowboards had really good profit margins…Our biggest problem was keeping inventory and getting it back…We were out of stock all the time.”

Selling snowboards returned their investment and saved them money.

They did not appoint a business manager.

They accomplished everything alone.

Sales dipped in the spring, but something magical happened.

Spring sales plummeted.

They considered stocking different boards.

They naturally wanted to add boards and grow the business.

However, magic occurred.

Tobi coded and improved software while running Snowdevil.

He modified software constantly. He wanted speedier software.

He experimented to make the software more resilient.

Tobi received emails requesting the Snowdevil license.

They intended to create something similar.

“I didn’t stop programming, I was just like Ok now let me try things, let me make it faster and try different approaches…Increasingly I got people sending me emails and asking me If I would like to licence snowdevil to them. People wanted to start something similar.”

Software or skateboards, your choice

Scott and Tobi had to choose a hobby in 2005.

They might sell alternative boards or use software.

The software was a no-brainer from demand.

Daniel Weinand is invited to join Tobi's business.

Tobis German best friend is Daniel.

Tobi and Scott chose to use the software.

Tobi and Scott kept the software service.

Tobi called Daniel to invite him to Canada to collaborate.

Scott and Tobi had quit snowboarding until then.

How was Shopify launched, and whence did the name come from?

The three chose Shopify.

Named from two words.

First:

• Shop

Final part:

• Simplify

Shopify

Shopify's crew has always had one goal:

• creating software that would make it simple and easy for people to launch online storefronts.

Launched Shopify after raising money for the first time.

Shopify began fundraising in 2005.

First, they borrowed from family and friends.

They needed roughly $200k to run the company efficiently.

$200k was a lot then.

When questioned why they require so much money. Tobi told them to trust him with their goals. The team raised seed money from family and friends.

Shopify.com has a landing page. A demo of their goal was on the landing page.

In 2006, Shopify had about 4,000 emails.

Shopify rented an Ottawa office.

“We sent a blast of emails…Some people signed up just to try it out, which was exciting.”

How things developed after Scott left the company

Shopify co-founder Scott Lake left in 2008.

Scott was CEO.

“He(Scott) realized at some point that where the software industry was going, most of the people who were the CEOs were actually the highly technical person on the founding team.”

Scott leaving the company worried Tobi.

Tobis worried about finding a new CEO.

To Tobi:

A great VC will have the network to identify the perfect CEO for your firm.

Tobi started visiting Silicon Valley to meet with venture capitalists to recruit a CEO.

Initially visiting Silicon Valley

Tobi came to Silicon Valley to start a 20-person company.

This company creates eCommerce store software.

Tobi never wanted a big corporation. He desired a fulfilling existence.

“I stayed in a hostel in the Bay Area. I had one roommate who was also a computer programmer. I bought a bicycle on Craiglist. I was there for a week, but ended up staying two and a half weeks.”

Tobi arrived unprepared.

When venture capitalists asked him business questions.

He answered few queries.

Tobi didn't comprehend VC meetings' terminology.

He wrote the terms down and looked them up.

Some were fascinated after he couldn't answer all these queries.

“I ended up getting the kind of term sheets people dream about…All the offers were conditional on moving our company to Silicon Valley.”

Canada received Tobi.

He wanted to consult his team before deciding. Shopify had five employees at the time.

2008.

A global recession greeted Tobi in Canada. The recession hurt the market.

His term sheets were useless.

The economic downturn in the world provided Shopify with a fantastic opportunity.

The global recession caused significant job losses.

Fired employees had several ideas.

They wanted online stores.

Entrepreneurship was desired. They wanted to quit work.

People took risks and tried new things during the global slump.

Shopify subscribers skyrocketed during the recession.

“In 2009, the company reached neutral cash flow for the first time…We were in a position to think about long-term investments, such as infrastructure projects.”

Then, Tobi Lutke became CEO.

How did Tobi perform as the company's CEO?

“I wasn’t good. My team was very patient with me, but I had a lot to learn…It’s a very subtle job.”

2009–2010.

Tobi limited the company's potential.

He deliberately restrained company growth.

Tobi had one costly problem:

• Whether Shopify is a venture or a lifestyle business.

The company's annual revenue approached $1 million.

Tobi battled with the firm and himself despite good revenue.

His wife was supportive, but the responsibility was crushing him.

“It’s a crushing responsibility…People had families and kids…I just couldn’t believe what was going on…My father-in-law gave me money to cover the payroll and it was his life-saving.”

Throughout this trip, everyone supported Tobi.

They believed it.

$7 million in donations received

Tobi couldn't decide if this was a lifestyle or a business.

Shopify struggled with marketing then.

Later, Tobi tried 5 marketing methods.

He told himself that if any marketing method greatly increased their growth, he would call it a venture, otherwise a lifestyle.

The Shopify crew brainstormed and voted on marketing concepts.

Tested.

“Every single idea worked…We did Adwords, published a book on the concept, sponsored a podcast and all the ones we tracked worked.”

To Silicon Valley once more

Shopify marketing concepts worked once.

Tobi returned to Silicon Valley to pitch investors.

He raised $7 million, valuing Shopify at $25 million.

All investors had board seats.

“I find it very helpful…I always had a fantastic relationship with everyone who’s invested in my company…I told them straight that I am not going to pretend I know things, I want you to help me.”

Tobi developed skills via running Shopify.

Shopify had 20 employees.

Leaving his wife's parents' home

Tobi left his wife's parents in 2014.

Tobi had a child.

Shopify has 80,000 customers and 300 staff in 2013.

Public offering in 2015

Shopify investors went public in 2015.

Shopify powers 4.1 million e-Commerce sites.

Shopify stores are 65% US-based.

It is currently valued at $48 billion.

Are MVPs outdated and have no place in modern product culture?

Frank Robinson coined "MVP" in 2001. In the same year as the Agile Manifesto, the first Scrum experiment began. MVPs are old.

The concept was created to solve the waterfall problem at the time.

The market was still sour from the .com bubble. The tech industry needed a new approach. Product and Agile gained popularity because they weren't waterfall.

More than 20 years later, waterfall is dead as dead can be, but we are still talking about MVPs. Does that make sense?

What is an MVP?

Minimum viable product. You probably know that, so I'll be brief:

[…] The MVP fits your company and customer. It's big enough to cause adoption, satisfaction, and sales, but not bloated and risky. It's the product with the highest ROI/risk. […] — Frank Robinson, SyncDev

MVP is a complete product. It's not a prototype. It's your product's first iteration, which you'll improve. It must drive sales and be user-friendly.

At the MVP stage, you should know your product's core value, audience, and price. We are way deep into early adoption territory.

What about all the things that come before?

Modern product discovery

Eric Ries popularized the term with The Lean Startup in 2011. (Ries would work with the concept since 2008, but wide adoption came after the book was released).

Ries' definition of MVP was similar to Robinson's: "Test the market" before releasing anything. Ries never mentioned money, unlike Jobs. His MVP's goal was learning.

“Remove any feature, process, or effort that doesn't directly contribute to learning” — Eric Ries, The Lean Startup

Product has since become more about "what" to build than building it. What started as a learning tool is now a discovery discipline: fake doors, prototyping, lean inception, value proposition canvas, continuous interview, opportunity tree... These are cheap, effective learning tools.

Over time, companies realized that "maximum ROI divided by risk" started with discovery, not the MVP. MVPs are still considered discovery tools. What is the problem with that?

Time to Market vs Product Market Fit

Waterfall's Time to Market is its biggest flaw. Since projects are sliced horizontally rather than vertically, when there is nothing else to be done, it’s not because the product is ready, it’s because no one cares to buy it anymore.

MVPs were originally conceived as a way to cut corners and speed Time to Market by delivering more customer requests after they paid.

Original product development was waterfall-like.

Time to Market defines an optimal, specific window in which value should be delivered. It's impossible to predict how long or how often this window will be open.

Product Market Fit makes this window a "state." You don’t achieve Product Market Fit, you have it… and you may lose it.

Take, for example, Snapchat. They had a great time to market, but lost product-market fit later. They regained product-market fit in 2018 and have grown since.

An MVP couldn't handle this. What should Snapchat do? Launch Snapchat 2 and see what the market was expecting differently from the last time? MVPs are a snapshot in time that may be wrong in two weeks.

MVPs are mini-projects. Instead of spending a lot of time and money on waterfall, you spend less but are still unsure of the results.

MVPs aren't always wrong. When releasing your first product version, consider an MVP.

Minimum viable product became less of a thing on its own and more interchangeable with Alpha Release or V.1 release over time.

Modern discovery technics are more assertive and predictable than the MVP, but clarity comes only when you reach the market.

MVPs aren't the starting point, but they're the best way to validate your product concept.

The best free tools are probably unknown to you.

Modern startups are easy to build.

Start with free tools.

Let’s go.

Web development — Webflow

Code-free HTML, CSS, and JS.

Webflow isn't like Squarespace, Wix, or Shopify.

It's a super-fast no-code tool for professionals to construct complex, highly-responsive websites and landing pages.

Webflow can help you add animations like those on Apple's website to your own site.

I made the jump from WordPress a few years ago and it changed my life.

No damn plugins. No damn errors. No damn updates.

The best, you can get started on Webflow for free.

Data tracking — Airtable

Spreadsheet wings.

Airtable combines spreadsheet flexibility with database power without code.

• Airtable is modern.

• Airtable has modularity.

• Scaling Airtable is simple.

Airtable, one of the most adaptable solutions on this list, is perfect for client data management.

Clients choose customized service packages. Airtable consolidates data so you can automate procedures like invoice management and focus on your strengths.

Airtable connects with so many tools that rarely creates headaches. Airtable scales when you do.

Airtable's flexibility makes it a potential backend database.

Design — Figma

Better, faster, easier user interface design.

Figma rocks!

• It’s fast.

• It's free.

• It's adaptable

First, design in Figma.

Iterate.

Export development assets.

Figma lets you add more team members as your company grows to work on each iteration simultaneously.

Figma is web-based, so you don't need a powerful PC or Mac to start.

Task management — Trello

Unclock jobs.

Tacky and terrifying task management products abound. Trello isn’t.

Those that follow Marie Kondo will appreciate Trello.

• Everything is clean.

• Nothing is complicated.

• Everything has a place.

Compared to other task management solutions, Trello is limited. And that’s good. Too many buttons lead to too many decisions lead to too many hours wasted.

Trello is a must for teamwork.

Domain email — Zoho

Free domain email hosting.

Professional email is essential for startups. People relied on monthly payments for too long. Nope.

Zoho offers 5 free professional emails.

It doesn't have Google's UI, but it works.

VPN — Proton VPN

Fast Swiss VPN protects your data and privacy.

Proton VPN is secure.

• Proton doesn't record any data.

• Proton is based in Switzerland.

Swiss privacy regulation is among the most strict in the world, therefore user data are protected. Switzerland isn't a 14 eye country.

Journalists and activists trust Proton to secure their identities while accessing and sharing information authoritarian governments don't want them to access.

Web host — Netlify

Free fast web hosting.

Netlify is a scalable platform that combines your favorite tools and APIs to develop high-performance sites, stores, and apps through GitHub.

Serverless functions and environment variables preserve API keys.

Netlify's free tier is unmissable.

• 100GB of free monthly bandwidth.

• Free 125k serverless operations per website each month.

Database — MongoDB

Create a fast, scalable database.

MongoDB is for small and large databases. It's a fast and inexpensive database.

• Free for the first million reads.

• Then, for each million reads, you must pay $0.10.

MongoDB's free plan has:

• Encryption from end to end

• Continual authentication

• field-level client-side encryption

If you have a large database, you can easily connect MongoDB to Webflow to bypass CMS limits.

Automation — Zapier

Time-saving tip: automate repetitive chores.

Zapier simplifies life.

Zapier syncs and connects your favorite apps to do impossibly awesome things.

If your online store is connected to Zapier, a customer's purchase can trigger a number of automated actions, such as:

1. The customer is being added to an email chain.

2. Put the information in your Airtable.

3. Send a pre-programmed postcard to the customer.

4. Alexa, set the color of your smart lights to purple.

Zapier scales when you do.

Email & SMS marketing — Omnisend

Email and SMS marketing campaigns.

This is an excellent Mailchimp option for magical emails. Omnisend's processes simplify email automation.

I love the interface's cleanliness.

Omnisend's free tier includes web push notifications.

Send up to:

• 500 emails per month

• 60 maximum SMSs

• 500 Web Push Maximum

Forms and surveys — Tally

Create flexible forms that people enjoy.

Typeform is clean but restricting. Sometimes you need to add many questions. Tally's needed sometimes.

Tally is flexible and cheaper than Typeform.

99% of Tally's features are free and unrestricted, including:

• Unlimited forms

• Countless submissions

• Collect payments

• File upload

Tally lets you examine what individuals contributed to forms before submitting them to see where they get stuck.

Airtable and Zapier connectors automate things further. If you pay, you can apply custom CSS to fit your brand.

See.

Free tools are the greatest.

Let's use them to launch a startup.