A fraud, free-market, antifragility tale

Crypto's only rival is public opinion.

In less than a week, mainstream media, bloggers, and TikTokers turned on FTX's founder.

While some were surprised, almost everyone with a keyboard and a Twitter account predicted the FTX collapse. These financial oracles should have warned the 1.2 million people Sam Bankman-Fried duped.

After happening, unexpected events seem obvious to our brains. It's a bug and a feature because it helps us cope with disasters and makes our reasoning suck.

Nobody predicted the FTX debacle. Bloomberg? Politicians. Non-famous. No cryptologists. Who?

When FTX imploded, taking billions of dollars with it, an outrage bomb went off, and the resulting shockwave threatens the crypto market's existence.

As someone who lost more than $78,000 in a crypto scam in 2020, I can only understand people’s reactions.  When the dust settles and rationality returns, we'll realize this is a natural occurrence in every free market.

What specifically occurred with FTX? (Skip if you are aware.)

FTX is a cryptocurrency exchange where customers can trade with cash. It reached #3 in less than two years as the fastest-growing platform of its kind.

FTX's performance helped make SBF the crypto poster boy. Other reasons include his altruistic public image, his support for the Democrats, and his company Alameda Research.

Alameda Research made a fortune arbitraging Bitcoin.

Arbitrage trading uses small price differences between two markets to make money. Bitcoin costs $20k in Japan and $21k in the US. Alameda Research did that for months, making $1 million per day.

Later, as its capital grew, Alameda expanded its trading activities and began investing in other companies.

Let's now discuss FTX.

SBF's diabolic master plan began when he used FTX-created FTT coins to inflate his trading company's balance sheets. He used inflated Alameda numbers to secure bank loans.

SBF used money he printed himself as collateral to borrow billions for capital. Coindesk exposed him in a report.

One of FTX's early investors tweeted that he planned to sell his FTT coins over the next few months. This would be a minor event if the investor wasn't Binance CEO Changpeng Zhao (CZ).

The crypto space saw a red WARNING sign when CZ cut ties with FTX. Everyone with an FTX account and a brain withdrew money. Two events followed. FTT fell from $20 to $4 in less than 72 hours, and FTX couldn't meet withdrawal requests, spreading panic.

SBF reassured FTX users on Twitter. Good assets.

He lied.

SBF falsely claimed FTX had a liquidity crunch. At the time of his initial claims, FTX owed about $8 billion to its customers. Liquidity shortages are usually minor. To get cash, sell assets. In the case of FTX, the main asset was printed FTT coins.

Sam wouldn't get out of trouble even if he slashed the discount (from $20 to $4) and sold every FTT. He'd flood the crypto market with his homemade coins, causing the price to crash.

SBF was trapped. He approached Binance about a buyout, which seemed good until Binance looked at FTX's books.

Binance's tweet ended SBF, and he had to apologize, resign as CEO, and file for bankruptcy.

Bloomberg estimated Sam's net worth to be zero by the end of that week. 0!

But that's not all. Twitter investigations exposed fraud at FTX and Alameda Research. SBF used customer funds to trade and invest in other companies.

Thanks to the Twitter indie reporters who made the mainstream press look amateurish. Some Twitter detectives didn't sleep for 30 hours to find answers. Others added to existing threads. Memes were hilarious.

One question kept repeating in my bald head as I watched the Blue Bird. Sam, WTF?

Then I understood.

SBF wanted that FTX becomes a bank.

Think about this. FTX seems healthy a few weeks ago. You buy 2 bitcoins using FTX. You'd expect the platform to take your dollars and debit your wallet, right?

No. They give I-Owe-Yous.

FTX records owing you 2 bitcoins in its internal ledger but doesn't credit your account. Given SBF's tricks, I'd bet on nothing.

What happens if they don't credit my account with 2 bitcoins? Your money goes into FTX's capital, where SBF and his friends invest in marketing, political endorsements, and buying other companies.

Over its two-year existence, FTX invested in 130 companies. Once they make a profit on their purchases, they'll pay you and keep the rest.

One detail makes their strategy dumb. If all FTX customers withdraw at once, everything collapses.

Financially savvy people think FTX's collapse resembles a bank run, and they're right. SBF designed FTX to operate like a bank.

You expect your bank to open a drawer with your name and put $1,000 in it when you deposit $1,000. They deposit $100 in your drawer and create an I-Owe-You for $900. What happens to $900?

Let's sum it up: It's boring and headache-inducing.

When you deposit money in a bank, they can keep 10% and lend the rest. Fractional Reserve Banking is a popular method. Fractional reserves operate within and across banks.

Fractional reserve banking generates $10,000 for every $1,000 deposited. People will pay off their debt plus interest.

As long as banks work together and the economy grows, their model works well.

SBF tried to replicate the system but forgot two details. First, traditional banks need verifiable collateral like real estate, jewelry, art, stocks, and bonds, not digital coupons. Traditional banks developed a liquidity buffer. The Federal Reserve (or Central Bank) injects massive cash into troubled banks.

Massive cash injections come from taxpayers. You and I pay for bankers' mistakes and annual bonuses. Yes, you may think banking is rigged. It's rigged, but it's the best financial game in 150 years. We accept its flaws, including bailouts for too-big-to-fail companies.

Anyway.

SBF wanted Binance's bailout. Binance said no, which was good for the crypto market.

Free markets are resilient.

Nassim Nicholas Taleb coined the term antifragility.

“Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty. Yet, in spite of the ubiquity of the phenomenon, there is no word for the exact opposite of fragile. Let us call it antifragile. Antifragility is beyond resilience or robustness. The resilient resists shocks and stays the same; the antifragile gets better.”

The easiest way to understand how antifragile systems behave is to compare them with other types of systems.

• Glass is like a fragile system. It snaps when shocked.

• Similar to rubber, a resilient system. After a stressful episode, it bounces back.

• A system that is antifragile is similar to a muscle. As it is torn in the gym, it gets stronger.

Time-changed things are antifragile. Culture, tech innovation, restaurants, revolutions, book sales, cuisine, economic success, and even muscle shape. These systems benefit from shocks and randomness in different ways, but they all pay a price for antifragility.

Same goes for the free market and financial institutions. Taleb's book uses restaurants as an example and ends with a reference to the 2008 crash.

“Restaurants are fragile. They compete with each other. But the collective of local restaurants is antifragile for that very reason. Had restaurants been individually robust, hence immortal, the overall business would be either stagnant or weak and would deliver nothing better than cafeteria food — and I mean Soviet-style cafeteria food. Further, it [the overall business] would be marred with systemic shortages, with once in a while a complete crisis and government bailout.”

Imagine the same thing with banks.

Independent banks would compete to offer the best services. If one of these banks fails, it will disappear. Customers and investors will suffer, but the market will recover from the dead banks' mistakes.

This idea underpins a free market. Bitcoin and other cryptocurrencies say this when criticizing traditional banking.

The traditional banking system's components never die. When a bank fails, the Federal Reserve steps in with a big taxpayer-funded check. This hinders bank evolution. If you don't let banking cells die and be replaced, your financial system won't be antifragile.

The interdependence of banks (centralization) means that one bank's mistake can sink the entire fleet, which brings us to SBF's ultimate travesty with FTX.

FTX has left the cryptocurrency gene pool.

FTX should be decentralized and independent. The super-star scammer invested in more than 130 crypto companies and linked them, creating a fragile banking-like structure. FTX seemed to say, "We exist because centralized banks are bad." But we'll be good, unlike the centralized banking system.

FTX saved several companies, including BlockFi and Voyager Digital.

FTX wanted to be a crypto bank conglomerate and Federal Reserve. SBF wanted to monopolize crypto markets. FTX wanted to be in bed with as many powerful people as possible, so SBF seduced politicians and celebrities.

Worst? People who saw SBF's plan flaws praised him. Experts, newspapers, and crypto fans praised FTX. When billions pour in, it's hard to realize FTX was acting against its nature.

Then, they act shocked when they realize FTX's fall triggered a domino effect. Some say the damage could wipe out the crypto market, but that's wrong.

Cell death is different from body death.

FTX is out of the game despite its size. Unfit, it fell victim to market natural selection.

Next?

The challengers keep coming. The crypto economy will improve with each failure.

Free markets are antifragile because their fragile parts compete, fostering evolution. With constructive feedback, evolution benefits customers and investors.

FTX shows that customers don't like being scammed, so the crypto market's health depends on them. Charlatans and con artists are eliminated quickly or slowly.

Crypto isn't immune to collapse. Cryptocurrencies can go extinct like biological species. Antifragility isn't immortality. A few more decades of evolution may be enough for humans to figure out how to best handle money, whether it's bitcoin, traditional banking, gold, or something else.

Keep your BS detector on. Start by being skeptical of this article's finance-related claims. Even if you think you understand finance, join the conversation.

We build a better future through dialogue. So listen, ask, and share. When you think you can't find common ground with the opposing view, remember:

Sam Bankman-Fried lied.

Ethereum's blockchain rules NFTs. Many consider it the one-stop shop for NFTs, and it's become the most talked-about and trafficked blockchain in existence.

Other blockchains are becoming popular in NFTs. Crypto-artists and NFT enthusiasts have sought new places to mint and trade NFTs due to Ethereum's high transaction costs and environmental impact.

When choosing a blockchain to mint on, there are several factors to consider. Size, creator costs, consumer spending habits, security, and community input are important. We've created a high-level summary of blockchains for NFTs to help clarify the fast-paced world of web3 tech.

Ethereum

Ethereum currently has the most NFTs. It's decentralized and provides financial and legal services without intermediaries. It houses popular NFT marketplaces (OpenSea), projects (CryptoPunks and the Bored Ape Yacht Club), and artists (Pak and Beeple).

It's also expensive and energy-intensive. This is because Ethereum works using a Proof-of-Work (PoW) mechanism. PoW requires computers to solve puzzles to add blocks and transactions to the blockchain. Solving these puzzles requires a lot of computer power, resulting in astronomical energy loss.

You should consider this blockchain first due to its popularity, security, decentralization, and ease of use.

Solana

Solana is a fast programmable blockchain. Its proof-of-history and proof-of-stake (PoS) consensus mechanisms eliminate complex puzzles. Reduced validation times and fees result.

PoS users stake their cryptocurrency to become a block validator. Validators get SOL. This encourages and rewards users to become stakers. PoH works with PoS to cryptographically verify time between events. Solana blockchain ensures transactions are in order and found by the correct leader (validator).

Solana's PoS and PoH mechanisms keep transaction fees and times low. Solana isn't as popular as Ethereum, so there are fewer NFT marketplaces and blockchain traders.

Tezos

Tezos is a greener blockchain. Tezos rose in 2021. Hic et Nunc was hailed as an economic alternative to Ethereum-centric marketplaces until Nov. 14, 2021.

Similar to Solana, Tezos uses a PoS consensus mechanism and only a PoS mechanism to reduce computational work. This blockchain uses two million times less energy than Ethereum. It's cheaper than Ethereum (but does cost more than Solana).

Tezos is a good place to start minting NFTs in bulk. Objkt is the largest Tezos marketplace.

Flow

Flow is a high-performance blockchain for NFTs, games, and decentralized apps (dApps). Flow is built with scalability in mind, so billions of people could interact with NFTs on the blockchain.

Flow became the NBA's blockchain partner in 2019. Flow, a product of Dapper labs (the team behind CryptoKitties), launched and hosts NBA Top Shot, making the blockchain integral to the popularity of non-fungible tokens.

Flow uses PoS to verify transactions, like Tezos. Developers are working on a model to handle 10,000 transactions per second on the blockchain. Low transaction fees.

Flow NFTs are tradeable on Blocktobay, OpenSea, Rarible, Foundation, and other platforms. NBA, NFL, UFC, and others have launched NFT marketplaces on Flow. Flow isn't as popular as Ethereum, resulting in fewer NFT marketplaces and blockchain traders.

Asset Exchange (WAX)

WAX is king of virtual collectibles. WAX is popular for digitalized versions of legacy collectibles like trading cards, figurines, memorabilia, etc.

Wax uses a PoS mechanism, but also creates carbon offset NFTs and partners with Climate Care. Like Flow, WAX transaction fees are low, and network fees are redistributed to the WAX community as an incentive to collectors.

WAX marketplaces host Topps, NASCAR, Hot Wheels, and cult classic film franchises like Godzilla, The Princess Bride, and Spiderman.

Binance Smart Chain

BSC is another good option for balancing fees and performance. High-speed transactions and low fees hurt decentralization. BSC is most centralized.

Binance Smart Chain uses Proof of Staked Authority (PoSA) to support a short block time and low fees. The 21 validators needed to run the exchange switch every 24 hours. 11 of the 21 validators are directly connected to the Binance Crypto Exchange, according to reports.

While many in the crypto and NFT ecosystems dislike centralization, the BSC NFT market picked up speed in 2021. OpenBiSea, AirNFTs, JuggerWorld, and others are gaining popularity despite not having as robust an ecosystem as Ethereum.

McMurtry Spéirling outperforms Tesla in speed and efficiency.

EVs were ridiculously slow for decades. However, the 2008 Tesla Roadster revealed that EVs might go extraordinarily fast. The Tesla Model S Plaid and Rimac Nevera are the fastest-accelerating road vehicles, despite combustion-engined road cars dominating the course. A little-known firm beat Tesla and Rimac in the 0-60 race, beat F1 vehicles on a circuit, and boasts a 350-mile driving range. The McMurtry Spéirling is completely insane.

Mat Watson of CarWow, a YouTube megastar, was recently handed a Spéirling and access to Silverstone Circuit (view video above). Mat ran a quarter-mile on Silverstone straight with former F1 driver Max Chilton. The little pocket-rocket automobile touched 100 mph in 2.7 seconds, completed the quarter mile in 7.97 seconds, and hit 0-60 in 1.4 seconds. When looking at autos quickly, 0-60 times can seem near. The Tesla Model S Plaid does 0-60 in 1.99 seconds, which is comparable to the Spéirling. Despite the meager statistics, the Spéirling is nearly 30% faster than Plaid!

My vintage VW Golf 1.4s has an 8.8-second 0-60 time, whereas a BMW Z4 3.0i is 30% faster (with a 0-60 time of 6 seconds). I tried to beat a Z4 off the lights in my Golf, but the Beamer flew away. If they challenge the Spéirling in a Model S Plaid, they'll feel as I did. Fast!

Insane quarter-mile drag time. Its road car record is 7.97 seconds. A Dodge Demon, meant to run extremely fast quarter miles, finishes so in 9.65 seconds, approximately 20% slower. The Rimac Nevera's 8.582-second quarter-mile record was miles behind drag racing. This run hampered the Spéirling. Because it was employing gearing that limited its top speed to 150 mph, it reached there in a little over 5 seconds without accelerating for most of the quarter mile! McMurtry can easily change the gearing, making the Spéirling run quicker.

McMurtry did this how? First, the Spéirling is a tiny single-seater EV with a 60 kWh battery pack, making it one of the lightest EVs ever. The 1,000-hp Spéirling has more than one horsepower per kg. The Nevera has 0.84 horsepower per kg and the Plaid 0.44.

However, you cannot simply construct a car light and power it. Instead of accelerating, it would spin. This makes the Spéirling a fan car. Its huge fans create massive downforce. These fans provide the Spéirling 2 tonnes of downforce while stationary, so you could park it on the ceiling. Its fast 0-60 time comes from its downforce, which lets it deliver all that power without wheel spin.

It also possesses complete downforce at all speeds, allowing it to tackle turns faster than even race vehicles. Spéirlings overcame VW IDRs and F1 cars to set the Goodwood Hill Climb record (read more here). The Spéirling is a dragstrip winner and track dominator, unlike the Plaid and Nevera.

The Spéirling is astonishing for a single-seater. Fan-generated downforce is more efficient than wings and splitters. It also means the vehicle has very minimal drag without the fan. The Spéirling can go 350 miles per charge (WLTP) or 20-30 minutes at full speed on a track despite its 60 kWh battery pack. The G-forces would hurt your neck before the battery died if you drove around a track for longer. The Spéirling can charge at over 200 kW in about 30 minutes. Thus, driving to track days, having fun, and returning is possible. Unlike other high-performance EVs.

Tesla, Rimac, or Lucid will struggle to defeat the Spéirling. They would need to build a fan automobile because adding power to their current vehicle would make it uncontrollable. The EV and automobile industries now have a new, untouchable performance king.

Product game mindsets? How do these vary from Project mindset?

1950s spawned the Iron Triangle. Project people everywhere know and live by it. In stakeholder meetings, it is used to stretch the timeframe, request additional money, or reduce scope.

Quality was added to this triangle as things matured.

Quality was intended to be transformative, but none of these principles addressed why we conduct projects.

Value and benefits are key.

Product value is quantified by ROI, revenue, profit, savings, or other metrics. For me, every project or product delivery is about value.

Most project managers, especially those schooled 5-10 years or more ago (thousands working in huge corporations worldwide), understand the world in terms of the iron triangle. What does that imply? They worry about:

a) enough time to get the thing done.

b) have enough resources (budget) to get the thing done.

c) have enough scope to fit within (a) and (b) >> note, they never have too little scope, not that I have ever seen! although, theoretically, this could happen.

Boom—iron triangle.

To make the triangle function, project managers will utilize formal governance (Steering) to move those things. Increase money, scope, or both if time is short. Lacking funds? Increase time, scope, or both.

In current product development, shifting each item considerably may not yield value/benefit.

Even terrible. This approach will fail because it deprioritizes Value/Benefit by focusing the major stakeholders (Steering participants) and delivery team(s) on Time, Scope, and Budget restrictions.

Pre-agile, this problem was terrible. IT projects failed wildly. History is here.

Value, or benefit, is central to the product method. Product managers spend most of their time planning value-delivery paths.

Product people consider risk, schedules, scope, and budget, but value comes first. Let me illustrate.

Imagine managing internal products in an enterprise. Your core customer team needs a rapid text record of a chat to fix a problem. The consumer wants a feature/features added to a product you're producing because they think it's the greatest spot.

Project-minded, I may say;

Ok, I have budget as this is an existing project, due to run for a year. This is a new requirement to add to the features we’re already building. I think I can keep the deadline, and include this scope, as it sounds related to the feature set we’re building to give the desired result”.

This attitude repeats Scope, Time, and Budget.

Since it meets those standards, a project manager will likely approve it. If they have a backlog, they may add it and start specking it out assuming it will be built.

Instead, think like a product;

What problem does this feature idea solve? Is that problem relevant to the product I am building? Can that problem be solved quicker/better via another route ? Is it the most valuable problem to solve now? Is the problem space aligned to our current or future strategy? or do I need to alter/update the strategy?

A product mindset allows you to focus on timing, resource/cost, feasibility, feature detail, and so on after answering the aforementioned questions.

The above oversimplifies because

Leadership in discovery

Project managers are facilitators of ideas. This is as far as they normally go in the ‘idea’ space.

Business Requirements collection in classic project delivery requires extensive upfront documentation.

Agile project delivery analyzes requirements iteratively.

However, the project manager is a facilitator/planner first and foremost, therefore topic knowledge is not expected.

I mean business domain, not technical domain (to confuse matters, it is true that in some instances, it can be both technical and business domains that are important for a single individual to master).

Product managers are domain experts. They will become one if they are training/new.

They lead discovery.

Product Manager-led discovery is much more than requirements gathering.

Requirements gathering involves a Business Analyst interviewing people and documenting their requests.

The project manager calculates what fits and what doesn't using their Iron Triangle (presumably in their head) and reports back to Steering.

If this requirements-gathering exercise failed to identify requirements, what would a project manager do? or bewildered by project requirements and scope?

They would tell Steering they need a Business SME or Business Lead assigning or more of their time.

Product discovery requires the Product Manager's subject knowledge and a new mindset.

How should a Product Manager handle confusing requirements?

Product Managers handle these challenges with their talents and tools. They use their own knowledge to fill in ambiguity, but they have the discipline to validate those assumptions.

To define the problem, they may perform qualitative or quantitative primary research.

They might discuss with UX and Engineering on a whiteboard and test assumptions or hypotheses.

Do Product Managers escalate confusing requirements to Steering/Senior leaders? They would fix that themselves.

Product managers raise unclear strategy and outcomes to senior stakeholders. Open talks, soft skills, and data help them do this. They rarely raise requirements since they have their own means of handling them without top stakeholder participation.

Discovery is greenfield, exploratory, research-based, and needs higher-order stakeholder management, user research, and UX expertise.

Product Managers also aid discovery. They lead discovery. They will not leave customer/user engagement to a Business Analyst. Administratively, a business analyst could aid. In fact, many product organizations discourage business analysts (rely on PM, UX, and engineer involvement with end-users instead).

The Product Manager must drive user interaction, research, ideation, and problem analysis, therefore a Product professional must be skilled and confident.

Creating vs. receiving and having an entrepreneurial attitude

Product novices and project managers focus on details rather than the big picture. Project managers prefer spreadsheets to strategy whiteboards and vision statements.

These folks ask their manager or senior stakeholders, "What should we do?"

They then elaborate (in Jira, in XLS, in Confluence or whatever).

They want that plan populated fast because it reduces uncertainty about what's going on and who's supposed to do what.

Skilled Product Managers don't only ask folks Should we?

They're suggesting this, or worse, Senior stakeholders, here are some options. After asking and researching, they determine what value this product adds, what problems it solves, and what behavior it changes.

Therefore, to move into Product, you need to broaden your view and have courage in your ability to discover ideas, find insightful pieces of information, and collate them to form a valuable plan of action. You are constantly defining RoI and building Business Cases, so much so that you no longer create documents called Business Cases, it is simply ingrained in your work through metrics, intelligence, and insights.

Product Management is not a free lunch.

Plateless.

Plates and food must be prepared.

In conclusion, Product Managers must make at least three mentality shifts:

1. You put value first in all things. Time, money, and scope are not as important as knowing what is valuable.

2. You have faith in the field and have the ability to direct the search. YYou facilitate, but you don’t just facilitate. You wouldn't want to limit your domain expertise in that manner.

3. You develop concepts, strategies, and vision. You are not a waiter or an inbox where other people can post suggestions; you don't merely ask folks for opinion and record it. However, you excel at giving things that aren't clearly spoken or written down physical form.

Only two of the following three options can be achieved: consistency, availability, and partition tolerance

Someone told me that growing from 30 to 60 is the biggest adjustment for a team or business.

I remember thinking, That's random. Each company is unique. I've seen teams of all types confront the same issues during development periods. With new enterprises starting every year, we should be better at navigating growing difficulties.

As a team grows, its processes and systems break down, requiring reorganization or declining results. Why always? Why isn't there a perfect scaling model? Why hasn't that been found?

The Three Things Productive Organizations Must Have

Any company should be efficient and productive. Three items are needed:

First, it must verify that no two team members have conflicting information about the roadmap, strategy, or any input that could affect execution. Teamwork is required.

Second, it must ensure that everyone can receive the information they need from everyone else quickly, especially as teams become more specialized (an inevitability in a developing organization). It requires everyone's accessibility.

Third, it must ensure that the organization can operate efficiently even if a piece is unavailable. It's partition-tolerant.

From my experience with the many teams I've been on, invested in, or advised, achieving all three is nearly impossible. Why a perfect organization model cannot exist is clear after analysis.

The CAP Theorem: What is it?

Eric Brewer of Berkeley discovered the CAP Theorem, which argues that a distributed data storage should have three benefits. One can only have two at once.

The three benefits are consistency, availability, and partition tolerance, which implies that even if part of the system is offline, the remainder continues to work.

This notion is usually applied to computer science, but I've realized it's also true for human organizations. In a post-COVID world, many organizations are hiring non-co-located staff as they grow. CAP Theorem is more important than ever. Growing teams sometimes think they can develop ways to bypass this law, dooming themselves to a less-than-optimal team dynamic. They should adopt CAP to maximize productivity.

Path 1: Consistency and availability equal no tolerance for partitions

Let's imagine you want your team to always be in sync (i.e., for someone to be the source of truth for the latest information) and to be able to share information with each other. Only division into domains will do.

Numerous developing organizations do this, especially after the early stage (say, 30 people) when everyone may wear many hats and be aware of all the moving elements. After a certain point, it's tougher to keep generalists aligned than to divide them into specialized tasks.

In a specialized, segmented team, leaders optimize consistency and availability (i.e. every function is up-to-speed on the latest strategy, no one is out of sync, and everyone is able to unblock and inform everyone else).

Partition tolerance suffers. If any component of the organization breaks down (someone goes on vacation, quits, underperforms, or Gmail or Slack goes down), productivity stops. There's no way to give the team stability, availability, and smooth operation during a hiccup.

Path 2: Partition Tolerance and Availability = No Consistency

Some businesses avoid relying too heavily on any one person or sub-team by maximizing availability and partition tolerance (the organization continues to function as a whole even if particular components fail). Only redundancy can do that. Instead of specializing each member, the team spreads expertise so people can work in parallel. I switched from Path 1 to Path 2 because I realized too much reliance on one person is risky.

What happens after redundancy? Unreliable. The more people may run independently and in parallel, the less anyone can be the truth. Lack of alignment or updated information can lead to people executing slightly different strategies. So, resources are squandered on the wrong work.

Path 3: Partition and Consistency "Tolerance" equates to "absence"

The third, least-used path stresses partition tolerance and consistency (meaning answers are always correct and up-to-date). In this organizational style, it's most critical to maintain the system operating and keep everyone aligned. No one is allowed to read anything without an assurance that it's up-to-date (i.e. there’s no availability).

Always short-lived. In my experience, a business that prioritizes quality and scalability over speedy information transmission can get bogged down in heavy processes that hinder production. Large-scale, this is unsustainable.

Accepting CAP

When two puzzle pieces fit, the third won't. I've watched developing teams try to tackle these difficulties, only to find, as their ancestors did, that they can never be entirely solved. Idealized solutions fail in reality, causing lost effort, confusion, and lower production.

As teams develop and change, they should embrace CAP, acknowledge there is a limit to productivity in a scaling business, and choose the best two-out-of-three path.