Bitcoin’s scripting environment is intentionally restrictive — designed more for safety and simplicity than expressive programmability. This design limits the native ability to perform stateful or Turing-complete computations, which are crucial for enabling trust-minimized bridges to Bitcoin L2s.

BitVM2 and ColliderVM proposes mechanisms to circumvent these limitations and bring general-purpose computation to Bitcoin, enabling trust-minimized bridges without requiring a consensus fork. Though they share the same end goal, their approaches diverge significantly in architecture, assumptions, and trade-offs.

This article aims to present a high-level, dumbed-down overview on both protocols. For those of you with a more technical background, I will recommend directly reading from the water source — here are links to BitVM2 and ColliderVM papers.

How BitVM2 works

BitVM2 is a framework built around optimistic computation. The core idea is that computation is assumed to be honest unless proven otherwise (via fraud proofs). To achieve this, BitVM2 leverages SNARKs (succinct non-interactive arguments of knowledge), particularly Groth16, to verify arbitrary off-chain computations. However, since verifying a Groth16 SNARK on Bitcoin is too resource-intensive to fit in a single script (often gigabytes in size), BitVM2 splits the verifier into smaller sub-programs, each small enough to be executed within Bitcoin's transaction and block constraints.

In practice, an operator commits on-chain to the result of a computation (e.g., a bridge withdrawal). If no one challenges this claim, it goes through after the timeout window passes. But if someone does challenge, they must present a fraud proof, pinpointing the specific step in the computation that was falsified. This involves running that specific sub-program on-chain and showing that the claimed intermediate value is invalid. All of this can be resolved with just three on-chain transactions, making the system quite efficient compared to older fraud-proof designs like Truebit or the original BitVM.

The BitVM2 system depends on three key roles:

• A committee of signers who enforce the transaction flow via pre-signed transactions (or future covenants).

• Operators who execute the computation.

• Challengers, anyone in the Bitcoin network who can verify and disprove dishonest computation.

As long as one signer is honest during setup, one operator is honest for liveness, and one rational challenger is active, the system is secure.

How ColliderVM works

ColliderVM, by contrast, takes a pessimistic route. It avoids fraud proofs entirely and instead uses a clever cryptographic commitment scheme based on hash collision resistance to ensure correct computation.

It builds on the ColliderScript concept but drastically improves its efficiency, reducing the number of required hash evaluations by over 10,000×. The essence of ColliderVM is this: A signer pre-signs a series of Bitcoin transactions that collectively represent the logic of a program, split into multiple subfunctions. Each flow enforces the order of operations (e.g., f₁ → f₂ → f₃) without being bound to a specific input value.

To ensure that the same input is used consistently throughout the flow (and to prevent cheating by providing different inputs to each step), ColliderVM uses a hash-commitment mechanism. The operator must find a nonce r such that H(x, r) maps to a pre-defined set D. If the operator tries to cheat by using inconsistent inputs, they would have to find a hash collision within D, a computationally intensive task that will be economically infeasible for anyone to attempt.

Take, for example, setting the parameters to L = 36 and B = 100. This requires 236 presigned flows; an honest operator needs to perform 64 bits of work to evaluate f, while a malicious operator needs 82. As mentioned, currently (April 2025) mining Bitcoin require 78 bits of work for which the miner gets 3.125 BTC.

Therefore, the attacker needs to spend work equivalent to around 50 BTC. The legitimate operator, at least for the hashing part, needs work that is ≈ 3.125/2¹⁴ BTC, which represents ~262,144x less work than the attacker!

As such, ColliderVM does not require on-chain fraud proofs or slashing mechanisms. Security arises from cryptographic hardness assumptions, making the system more passive from a network perspective but also more front-loaded in setup complexity.

Which way, Bitcoin man?

BitVM2 is conceptually elegant and operationally proven in similar systems like Arbitrum and the OP Stack. It benefits from fast dispute resolution (3 transactions) and permissionless verification. But it depends on active monitoring, economic incentives for challengers, and the setup cost of handling large verifier scripts on Bitcoin — even in sub-program chunks. Moreover, the system remains capital inefficient, requiring operators to fund user withdrawals upfront while waiting out challenge windows.

On the other hand, ColliderVM has no fraud proof window, no need for economic incentives to challenge, and operators do not need to pre-fund withdrawals. This makes it more aligned with the more “traditional” beliefs of Bitcoiners — minimal trust, no long-running watchers, and no slashing. However, ColliderVM’s main challenge is in its setup scalability: generating and managing billions of pre-signed flows is a logistical and engineering hurdle. While this can be mitigated through improvements in tooling or parameter tuning, as of now it remains a considerable barrier to practical deployment — there is still not enough transactional demand on Bitcoin L2s to justify ColliderVM’s massive computational overhead per deposit or withdrawal on Bitcoin.

In the realm of trust-minimized Bitcoin bridges, BitVM2 is relatively more mature and may be easier to deploy in early designs — especially where challenger incentives and fraud windows are acceptable tradeoffs. ColliderVM, while still experimental, offers a compelling future path for "set-and-forget" secure computation on Bitcoin.

In the long run, ColliderVM’s model may be more aligned with Bitcoin’s ethos: trustless, final, and economically lean. But for immediate scalability, especially with existing SNARK ecosystems, BitVM2 may be the more practical short-term solution. The best design might even combine both — using BitVM2’s challenge mechanisms in early stages and evolving into ColliderVM-style enforcement as tooling and hardware capabilities mature.

Also published on X: https://x.com/delken_/status/1912138039867883849

For prediction markets to grow beyond being just a quadrennial spectacle (and the plaything of nerds) to be a regular fixture in people’s lives and become their go-to authoritative source for most event probabilities, entails moving away from the design of first-generation prediction markets.

First-generation protocols, where liquidity provision is a loss-making gambit (and hence constrains liquidity provision to centralized entities with ulterior motives), is simply inadequate for a future where you want prediction markets to become a staple of people’s information diet — the decentralized source of truth spanning hundreds of concurrent world events.

This article will dissect the concept of prediction markets, discuss the historical evolution of prediction markets, what designs do prediction market protocols tend to converge towards in the past, and the bottleneck in liquidity provision confining the scale of current prediction markets.

A Primer on Prediction Markets

Prediction markets are fundamentally a simple premise: it is a bidirectional trading market for bettors to express a view over an outcome.

The concept borrows from Friedrich Hayes’ assertion, that the price system in a free market accurately expresses the aggregate views of market participants over the traded asset. In the case of prediction markets, assuming a free market environment, the price per share will reflect the aggregate view of market participants over the likelihood of the traded outcome.

Hence, prediction markets form reliable unbiased indicators over the probabilities of an outcome, backed by the skin-in-the-game of profit-motivated entities participating in the market.

Isn’t it just glorified betting?

The main difference between prediction markets and betting platforms lie in the manner of how odds (or probabilities) are derived for an outcome:

• In prediction markets, the free market determines the odds of an event, calculated as a byproduct of betting flows on either side of the bidirectional trade.

• In betting platforms, the operator or bookie forms an opinionated understanding on an event and sets the odds for bettors to bet on (with a margin of error). Bettors are welcome to bet against this opinion, and if they’re proven correct, then the operator will lose money. The free market has little influence over a bookie’s offered odds — “feedback” is in form of profits (if the bookie’s opinion is in line with the free market) or losses (if “wrong” from actual truth).

Henceforth, prediction markets are treated as a more credible source denoting the ‘true’ odds of an outcome happening. Odds obtained from betting platforms merely represent the opinion of the operator or bookie (although they are incentivized to make them as competitive as possible in order to attract betting volume) — it doesn’t reflect the true probability of an outcome.

The Bettor-Viewer Flywheel

Betting and prediction markets are not mutually exclusive. Betting volumes contribute to the liquidity stock of a well-functioning prediction market, and the more liquidity is involved in a prediction market, the more accurate its odds will be perceived, since there are more people with skin-in-the-game and more monetary resources at-stake in that said prediction market.

An efficient prediction market is the result of two thriving yet distinct user groups feeding off each other: profit-seeking bettors who form the “money base” of the market, and information-curious viewers who form the “attention base” of the market.

• Increased attention helps get prediction markets to the eyes of profit-seeking bettors;

• Bettors place bets against what they deem to be mispriced odds on a prediction market, contributing to that market’s volume and repricing of odds;

• Interested viewers put greater weight on the accuracy of the prediction market due to the increased volumes, increasing attention and attracting more bettors into the mix;

• Bettors place increasingly sized bets against the prediction market’s odds as open interest (OI) grows and the market becomes able to take in top-dollar bets;

• Volumes boom, and viewers increasingly regard the prediction market as the source of truth for that event, further increasing its popularity which attracts more bettor eyeballs;

• ad infinitum.

Prediction Markets, v1

Pioneered by Augur, refined by Gnosis, and later popularized by Polymarket, first-generation prediction markets are implemented either via AMMs or orderbook.

AMM

AMMs became prevalent at a time when blockchains haven’t possessed sufficient scaling capacity to facilitate orderbook-based markets. In the case of prediction markets, each event is represented via a simple 2-pool AMM consisting of two tokens: a YES token, and a NO token.

Initial liquidity is seeded to the AMM by an entity (e.g., market makers) — this forms the market’s redeemable collateral base on event resolution. Participants trade YES and NO tokens against the AMM, which moves prices depending on betting flows. Also, the more liquidity the AMM is seeded with, the less sensitive prices will change per dollar of flow.

Orderbook (CLOB)

Advances made in blockchain scalability (and proving capabilities) results in the renaissance of the onchain CLOB model. In the case of prediction markets, each event has their own orderbook where participants may place bid/ask orders to trade YES and NO tokens.

Market makers are employed to make liquidity for each orderbook-based prediction market, and price movements will depend on betting flows with regards to liquidity: the more liquidity market-makers dedicate to the orderbook, the less sensitive prices will change per dollar of flow.

The Liquidity Bottleneck

When providing liquidity to a market, you will be exposed to the risk of Impermanent Loss (IL). In the case of AMMs, this will be the price differential between the point when you first deposited liquidity into the pool and the current point to which you want to withdraw your liquidity from the pool. In the case of CLOBs, this will be the difference between the orderbook’s current price and the aggregate prices of your top-of-book liquidity provision (buy/sell orders) for the orderbook.

Market-making in “conventional” markets (e.g., spot markets) is already hard enough: Uniswap LPs often had to be compensated via external rewards outside of fees just to breakeven when providing liquidity for non-correlated asset pairs. This is demonstrated by the makeup of LPs on Uniswap, where the majority of its LPs are in fact made up of highly sophisticated entities (i.e., Wintermute).

First-generation protocols, whether AMM- or CLOB-based, impose unrealistic expectations on LPs to manage their liquidity on individual prediction markets. For prediction markets, where odds swing from 40% to 95% in as short as a few minutes time, liquidity provision is simply a fool’s errand. One injury-time goal, the sudden withdrawal of a political candidate, the revelation of an election’s quick count results, or a knockout win by an MMA fighter — all of these cases will leave LPs on the hook, staring down at the barrel of their now-unrecoverable ILs.

With such high levels of principal risk, nobody is simply bothered enough to provide liquidity for prediction markets — ironically the very lifeblood driving accurate odds in the first place. This constrains the available pool of liquidity only to well-resourced centralized entities who are able to shoulder the principal risk in exchange for under-the-table benefits — definitely not the ideal status quo if you want a truly decentralized yet scalable prediction markets protocol.

Towards Scalable Prediction Markets

The cardinal rule to market efficiency: the more liquidity available for a market, the more it attracts market participants, the more efficient the market gets, and the more accurate its prices will reflect the reality of its underlying asset.

This applies to bond markets, currency markets, stock markets, and especially prediction markets, for which its entire premise lies in its ability to report accurate probabilities for a particular event or outcome.

“Liquidity is by far the biggest issue. When markets are illiquid, they are inefficient, which then calls into question whether they are indeed a source of truth. The more liquid a market is, the more efficient and ‘truthful’ it becomes.” — @mrink0

As prediction markets are increasingly being relied upon by society as an unbiased source of truth for world events, enabling trust-minimized and scalable liquidity provision is of paramount importance.

Unlike most of its industry peers, Azuro does not use the orderbook model as the mechanism underpinning its prediction markets, opting for a dynamic AMM-based approach under a singular concentrated liquidity pool model. It is the only protocol in production today that enables passive algorithmic liquidity provision, where LPs are protected from the risk of Impermanent Loss (IL).

This article is the first part of the “Crossing the Chasm” series on prediction markets.

The second part will be a deep-dive on the architecture of Azuro protocol. Stay tuned!

Finding specific knowledge

Life is about finding out your specific knowledge, the 1% in life that matters.

99% of exams you’ve taken, books you’ve read, things you learned, they don’t apply.

Specific knowledge is a sum of all your life experiences: how were you raised, where do you reside, your social experiences, your innate likes and dislikes.

Seek out this specific knowledge of yours, and devote 99% of your professional time to it: where to start, what to build, how to scale it.

Compounding specific knowledge is an unstoppable life leverage that no one could ever compete with. All returns in life, whether in wealth, relationships, or knowledge, come from compound interest.

Addendum

No one in the world is going to beat you at being you.

Follow your genuine intellectual curiosity, and it will lead you to your specific knowledge. When you do things for their own sake, you create your best work.

Knowledge only you know or only a small set of people knows is going to come out of your passions and your hobbies. If it entertains you now but will bore you someday, it is a distraction, which means you should keep looking.

Three big decisions

Spend more time making the big decisions: where you live, who you’re with, and what you do.

Choosing what city to live in can almost completely determine the trajectory of your life, your spouse makes up the majority of your time spent in social relationships, and you spend the majority of your waking hours on working.

Be extremely deliberate with these decisions.

Addendum

Advice to a young tech professional considering moving to San Francisco: “Do you want to leave your family & friends behind, or be the one who’s left behind?”

Building your network

Conventional business networking is bullshit.

Develop your specific knowledge, put yourself out there, and let people find you. Build a purposeful network — don’t network just for the sake of it.

Having a quality network increases the chances of you “making your own luck”.

For example: if you’re known to be within the top five of the world's best deep-sea divers, someone who discovers a deep-sea treasure but doesn’t have the means to dive and extract it, is going to find you and share their “luck”.

Addendum

There are different types of luck:

1. Blind luck (winning a lottery)

2. Luck through persistence (cold emailing tons of people and finally getting a reply back)

3. Lucky breaks (a VC just closed a new fund; you capitalize on it and reach out to their GPs for potential analyst openings)

4. Luck coming to find you (deep-sea diver example).

While you can’t control blind luck, you can do something about the rest to skew them in your favor:

• Hone specific knowledge

• Be persistent, aware, and patient.

On critical thinking

Be deliberate on what kind of information to absorb as the basis of your worldview. Garbage in, garbage out.

Just like that song that gets stuck in your head, what you read will get internalized within your psyche.

Develop a strong mental model (the result of years of conscious self-reflection), then rely on it to objectively filter out any incoming new information by breaking it down from first principles.

“Does this makes sense?"

"How do you make sense of it?"

"Why does it make sense in the first place?”

Addendum

People get stuck on ridiculous conspiracy theories because they have a weak mental model.

They seldom self-reflect. Hence, they lack first-principles thinking skills.

Mental models are hard to ascribe into words – they’re within your subconscious.

When you read Warren Buffett, you get a glimpse of his mental model, and how he used it to come up with his investing strategies.

Dive into the mental models of great thinkers (by reading them), and you’ll find yourself strengthening your own mental model as a byproduct.

We all have biases – the most important thing is to be aware of it. This will prevent us from being blindly dictated by whatever ideas thrown at us.

Develop the ability to recognize what is “right”, and what is “wrong”.

Achieving happiness

Desire is a chosen unhappiness, a contract that you make with yourself to be unhappy until you get what you want.

Build on top of one desire at a time. More desires mean more unhappiness, which dilutes your capacity to think clearly, causing you to make bad choices that will only lead you to compound more unhappiness.

A state of total happiness is when you stop desiring for new things – something that even rich people struggle with.

Play the game of life, but define what’s enough, and then to actually stop playing once this “peak desire” of yours has been reached.

Addendum

Whenever you’re overwhelmed with desires, embrace death – this will help you narrow your desires down to what’s actually important.

There’s no legacy. There’s nothing to leave. We’re all going to be gone. Our children will be gone. Our works will be dust. Our civilizations will be dust. Our planet will be dust. Our solar system will be dust. In the grand scheme of things, the Universe has been around for ten billion years. And it’ll be around for another ten billion years.

Colosseum (n): an ancient Roman arena where gladiators fight for life and death as a public spectacle — the victor redeems his honour, proving worthy of his unmerited gift of life.

Nihilists (n): individuals who have resigned to their lack of upward mobility, taking an all-or-nothing view to financial success in life.

Gambling: a pastime as old as time

We humans sure love to bet. Fully knowing that betting is a loss-making gambit in the long run, we nonetheless submit to our primal urges, putting your money to where your proverbial mouth is.

Peasants and aristocrats alike, we all indulge in some form of gambling one way or another. While the societal high-class engage in the pastime atop of their glittered ivory towers, peasants and the average Joes retreat to their humble dens to “shoot their shot” amongst peers of the same strata.

The above still holds true in the modern world. The haves with unfettered access to the global financial system, gamble away in the streets of Las Vegas and Macau. For the sports aficionados, licensed sports betting sites like bet365 / DraftKings happily roll up their sleeves to serve their gambling needs. But for the have-nots unlucky enough to live under a nanny-state, these avenues that the Western world has taken for granted, seemed so close yet so far.

Close to a third of the world population reside in countries where gambling exists in a grey area (or is straight-up illegal and persecuted).

On paper, everything seems all rosy: their citizens will stay away from the sin of gambling, and lead a life guided by moral principles. In reality though, these restrictions only drove people towards non-licensed online operators to do their “deed”, in which not only they get markedly worse odds and pay more in fees, they are multiple times more likely to be a victim of fraud or scams as a result of dealing with these preying shady operators.

The age of financial nihilism

Fueled by social media, the inclination of humans to “one up each other” becomes a global spectacle for the digital town hall to witness. 100x levered punts on memecoins, 10-game parlays, etc. — everyone is looking for that “one shot to glory”, aka the theory of financial nihilism.

Central to financial nihilism, is the lack of upward mobility that is afforded to young people of the present day.

For better or worse, the evidence shows: record-on-record numbers for the online gambling industry during the past few years, and the sky is still the limit!

The demand for gambling amongst financial nihilists is insatiable, so much so that people in restrictive jurisdictions are willing to trust third-party contacts or jump through hoops just to gamble on an unlicensed sketchy site where your money can go poof at any moment.

Don’t buck the trend: if financial nihilism is inevitable, then we might as well have the best version of it!

Azuro: permissionless, non-custodial, no limits

Crypto is the great global equalizer. No matter who you are or where you’re from, all you need is an internet-connected device to be your own wealth custodian. No background checks, salary slips, or proof of residence necessary — setup your wallet, and you’re ready to go!

Where other betting sites (even your so-called “crypto-native” betting operators) enforce mandatory KYC and acts as a custodian to your deposited funds, Azuro fully preserves the core tenets of crypto and takes the opposite approach: all you need to do is to connect your wallet to the front-end, and you’re set.

Permissionless, non-custodial, no limits — bet to your heart’s content!

The Liquidity Tree: one LP for all markets

Azuro's peer-to-pool "Liquidity Tree" model consolidates all liquidity into a single pool, acting as the counterparty to all bets placed on Azuro contracts. It allows Azuro to facilitate high-value bets with minimal slippage, as the full weight of a single LP can be thrown to support a singular bet if necessary (albeit with predefined limits to prevent LP ruin).

This approach differs from the capital-inefficient peer-to-peer model (where liquidity is siloed per market) used by virtually all of Azuro’s industry peers. At the time of writing, Azuro is the only protocol that employs a peer-to-pool model to serve each of its betting markets.

Azuro elegantly iterates upon the tried-and-tested “house liquidity” model used by traditional betting operators, implementing it as a set of smart contracts deployed to a public blockchain. Anyone can contribute their capital and be an Azuro LP, essentially partaking as a member of the Azuro decentralized house. LPers are entitled to a share of profits generated from Azuro’s “house edge”, in exchange for weathering out the volatility owed to the variability of betting outcomes.

Separation of concerns: the protocol and the “app”

Azuro is not a betting site, nor a company. Azuro is merely a moniker for the set of deployed smart contracts that anyone can interact with. People interface with Azuro in various ways — skilled developers may choose to build their own front-end locally, while the rest of us mere mortals may opt to rely on front-ends operated by third parties.

This “separation of concerns” bodes well for the going-concern of Azuro. By disassociating the front-end from the contracts, Azuro avoids pesky meatspace headaches — each front-end operator is responsible (if they choose to) for obtaining the relevant licenses, dealing with authorities of the jurisdictions they intend to serve, and doing the marketing campaigns to attract bettors to their front-end. In exchange for their hard work, front-ends are entitled to a mammoth 60% (at time of writing) of house profits generated from bets submitted through their site.

Since front-ends do not custody user funds (they are merely “pointers” to Azuro contracts on the public blockchain), they will be judged solely by their quality of service. In Azuro-land, bettors don’t deposit/withdraw funds to/from a front-end — they simply take their onchain funds and place bets directly on Azuro contracts via the front-end. All front-ends source the same odds and interact with the same set of contracts — the only differentiation point lies in the user interface and experience that each can bring to the table.

Lesson in there: when in doubt, the free market is your friend. Don’t take my word for it — nowhere else will you find a better collection of front-ends feeding off from the same protocol, all competing to satisfy your betting needs.

Prefer a tried-and-tested “boomer” front-end? Bookmaker is where you’re at. You want a front-end for degens with generous cashbacks on your losses? Try GambleFukkers. Gasless betting under an integrated wallet experience? DexWin is there for you. Heck, what if you’re too lazy to do any of the above? Look no further than BoxBet, where you can bet straight from the Telegram app!

Less intermediaries, less overhead, lower vigs!

For Azuro to remain “operational”, it essentially only needs a front-end operator (which can range from a single savvy individual to a global remote-first team). Upon deployment, Azuro contracts essentially require no further human intervention (except for upgrades, in which it will no longer be the case once Azuro reaches steady-state and admin keys are relinquished) — Azuro contracts will continue to run autonomously so long as the blockchain continues producing blocks.

In contrast to custodial betting houses, there’s the overhead of developing and maintaining the infrastructure needed to custody user funds (and invest in security practices for hack or breach prevention). Surprisingly it seems, that when you do away with less intermediaries and less overhead, you’ll be able to offer the lowest vigs (”house edge”) on the market!

Don’t hate the player, hate the game

“The idea that cost of living is strangling most Americans; that upward mobility opportunity is out of reach for increasingly more people; and that median home prices divided by median income is at a completely untenable level.

So why not put $500 into a memecoin that could 50x, knowing that you could likely lose most or all of it? It’s not like the $500 is enough to make any difference anyways. Neither is $1k or $5k.

That mindset, which is becoming pervasive in America, is financial nihilism.”

—Travis Kling

If financial nihilism becomes an increasingly likely reality that all of us must bear witness to, the best we can do is to make the game the best version of what it can be. If Americans are given the “privilege” of placing a 10-game parlay on a licensed reputable operator like DraftKings, it would be anything but fair if a third of the world population do not have the same ability to do so.

In the age of social media and the internet, a restrict-first and ban-first approach on online goods and services just won’t work. Doing so will only encourage the proliferation of black underground markets, which presents a worse outcome for everyone had the government respect individual liberty and just let the free market run its course. Meaning to say, banning online gambling will only lead to people resorting to shady operators that could run with their money at any moment.

Azuro presents a much better alternative to these opaque black market gambling dens — a permissionless and self-custodial platform where people retain full agency over their funds, and their identity.

An internet-connected device, some spare change, and game-set-match. No questions asked!

Now what does the charts say? Upwards, and to the right!

Disclosure: The author is a core contributor for Azuro. Views expressed in this article may be influenced by the author’s affiliation. Readers are encouraged to DYOR.

Crypto here, crypto there. Countless “introductory” webinars and article reads later, you still don’t quite grasp how this whole thing works. Rest assured, you’re far from being the only one.

Cryptocurrency is notorious for its high learning curve, so don’t beat yourself up if you can’t seem to understand. This article will provide a concise breakdown on how cryptocurrencies actually work, and why they represent a superior form of money over fiat currencies.

The nuts and bolts

In essence, cryptocurrencies are programmable money living on a decentralized network (the blockchain) — a shared public ledger.

User independence on their funds is achieved through encryption/decryption processes via public keys (your public key or crypto address, like your bank account number) and private keys (your private key or seed phrase, like your bank account password). This is referred to as public key cryptography.

Complex math is behind public key cryptography, specifically designed so that you can encrypt a piece of data with your public key, but the decryption can only be done with your private key. Vice versa, you can encrypt a piece of data with your private key, but it can only be decrypted with your public key.

Furthermore, it is also designed in such a way that although the public key is generated from its private key, you can never work backwards to derive the private key from its public key — again, enforced via mathematical algorithms.

To put things into perspective, as an analogy, if you receive a package from Amazon, you want to make sure that: a) Indeed Amazon has sent the package and not some bio-terrorist (signing) b) While in transit, nobody else knows what is inside the package (confidentiality) c) The package is not tampered while in transit (tamper-proofing).

Similarly, a network transaction also involves a sender, the ‘in-transit’ or network pipe, and a receiver. Public key cryptography comes in to solve the problem of signing, confidentiality and tamper-proofing of network transactions, all in one neat package.

Bear with me, let’s see how cryptocurrencies aka “data” are sent in practice:

1. The sender encrypts the data that the sender wants to send to the receiver with the sender’s private key to create the signature “sender-private-encrypted-data”. This is then combined with the data once again to form “data + sender-private-encrypted-data”.

2. The sender will again encrypt the above with the receiver’s public key to form “receiver-public-encrypted-data”. This is broadcasted on the blockchain network — no intruder can decipher this message as only the receiver’s private key can decrypt it.

3. The receiver would for the first time decrypt the above with the receiver’s private key, from “receiver-public-encrypted-data” to “data + sender-private-encrypted-data”. Since only the receiver can see “data”, confidentiality is achieved.

4. The receiver would for the second time decrypt only the “sender-private-encrypted-data” using the sender’s public key, resulting in “data”. Being able to decrypt it with the sender’s public key ensures that signing is achieved, and the fact that decrypting it with both the receiver’s private key and the sender’s public key results in the same “data” means that tamper-proofing is achieved as well.

Once a transaction has been authorized (or “signed”), it will be made eligible for inclusion into the blockchain (or the shared public ledger). Only when the transaction has been successfully included, then the balance change will be reflected on both your address and the receiver’s address.

With that said, we need to decide on a mechanism to govern who gets to write this transaction into the blockchain in the first place: enter what we call as “consensus mechanism”. Although there are various models of consensus, the two most prevalent ones are proof-of-work and proof-of-stake.

In proof-of-work, people (referred to as miner nodes) compete to solve a complex mathematical problem, and the first miner to get to the solution gets to group a bunch of pending transactions into a “block”, then include it into the blockchain — obtaining cryptocurrencies as compensation for each successful block inclusion. Therefore, the more powerful a miner’s mining rig, the better chance they will have on being the first one to solve the math problem, and hence the likelier that they will be able to “mine” the next block.

In proof-of-stake, the probability of a node mining the next block will be equivalent to the percentage of their staked tokens relative to the total tokens staked in the network. For example, if you staked 1 $ETH, and the total staked in the network is 100 $ETH, then you will have a 1% chance of mining the next block. Similar to proof-of-work, the miner will be rewarded with cryptocurrencies as compensation for each successful block inclusion.

Once a block has been mined, all transactions included inside this block can’t be reversed or tampered with — the block will be stacked on top of the previous block, such that the series of stacked blocks (hence the term “blockchain”) present a chronological view of transactions. These “stacks” are engineered in such a way that each node on the network will be able to verify that the latest block is indeed stacked (or “chained”) by the “winning” miner — facilitated via a hash-based data structure called the Merkle Tree.

Now that we know how cryptocurrencies work under-the-hood, the remaining parts of this article will elaborate on why cryptocurrencies are a superior form of money in comparison to fiat.

Fiat: centralized opaque money

Oversimplified, the current financial system is just a network of silo-ed bank ledgers, with each country’s central bank at the top coordinating everything: from interbank transfers to the reduction or expansion of its currency’s money supply.

To illustrate, when you transfer $1 to a friend, the money doesn’t actually “move” per se. Instead, the bank will just adjust you and your friend’s balances accordingly on its internal ledger, debiting $1 from your account and crediting $1 to your friend’s account. If your friend uses a different bank, both of your banks simply account for this movement internally until the central bank adjusts for this interbank money movement on its ledger.

Hold your horses, this gets even more complicated for international transfers — involving what we refer to as nostro and vostro accounts.

As a byproduct of how our current financial system is arranged, besides being highly inefficient by itself, it gives financial intermediaries a bird’s eye view on transactions, in which they can intervene at will.

Donating money to a political opposition of the current government? Blocked, whereabouts tracked, then jailed. Moving money out of the country? Restricted, whereabouts tracked, then questioned. While this might seem exaggerated for those living in functional democracies, just ask the citizens of China or Vietnam — they would beg to differ.

You could even go as far to say that banks are ultimately the ones controlling “your” money. What you are holding is simply a receipt that says that your money is with the associated bank, backed by ‘good-faith’ that the receipt will be honored at all times.

While highly unlikely, if your bank goes belly-up, your money will be at risk (in the United States, the FDIC will only insure up to $250k per individual per bank). Again, although this might seem exaggerated, just ask Saudi Arabia women on whether they can open a bank account without involving a male guardian, or Venezuela citizens on whether they think saving money in a bank is a good idea.

In addition, due to the silo-ed nature of the current financial system, opacity in financial markets is inevitable. For example, an asset can be securitized by a bank, sold to the bank’s investors, gets further repackaged by these same investors, and then resold again to other entities. Extrapolate this instance with every representable asset on the financial system, and what you get is a messy convoluted spiderweb of financial products with untraceable “source” assets.

In fact, this is exactly what happened during the 2008 Global Financial Crisis, culminating in the bankruptcy of Lehman Brothers (at the time the fourth largest investment bank in the US) and the bailouts of other firms deemed to be “too big to fail” (the likes of Bear Stearns and AIG). This would not have happened in the first place if everything is out in the open for the public to scrutinize — allowing anyone to transparently evaluate the tangible value of these repackaged securities for themselves over being forced to blindly trust the security underwriter’s word for it.

Crypto: decentralized transparent money

Cryptocurrencies allow you to no longer subject yourselves to a bank’s internal ledger for money movements. Anyone is able to initiate a transaction, and no one is able to do anything to prevent your transaction from going through — unless you pay absurdly low amounts of gas fees (miners won’t bother including your transaction into their block, as they feel they are not compensated enough for it).

Gone are the days when we have to adhere to your bank’s working hours, wait 10 minutes (or even a few days) for a transaction to be confirmed, or pay $50 in fees per transaction — blockchain networks like Solana or Avalanche operate 24/7, confirm within a few seconds, and charge mere cents in fees.

Without needing to involve banks, intermediary banks, and central banks for international money transfers, sending money via cryptocurrencies to a friend residing on the other side of the world would be as if you’re sending money to your neighbour living just a few blocks down the road!

Moreover, instead of being forced to trust the ‘good-faith’ of banks to store our money, cryptocurrencies provide anyone with the option to store money on a decentralized network that is impossible to shut down (unless the whole internet goes off, which if it does, we would have bigger problems to worry about). As such, as far as saving money goes, options are no longer restricted to the currency of the country that you are residing in or are a citizen of.

Donating to an opposition political party? Go ahead. Handling $1m as a 12-year-old business owner? Why not. Opening a bank account without a male guardian as a woman in Saudi Arabia? Who needs one when you can save in cryptocurrencies!

This might seem trivial for people living in countries with stable currencies, but for those living under oppressive (like Saudi Arabia or Afghanistan for women) or corrupt regimes with highly inflationary currencies (such as Argentina or Venezuela), cryptocurrencies present the only lifeline for them to store wealth and escape the continuously eroding purchasing power of their local fiat currencies.

To top it off, blockchain networks enable anyone to have equal access to transaction records, compared to our current financial system where only select financial institutions are provided with this privilege — significantly reducing information asymmetry.

Recall the example of an asset being securitized and repackaged repeatedly. If every transaction is done on the blockchain, then no matter the number of ‘iterations’ that a securitized asset has been subjected to, we can always trace it back to the “source” asset with confidence, knowing that any transaction recorded on the blockchain will be immutable — no entity is able to reverse or tamper with an already confirmed block.

A force greater than the sum of its parts

Cryptocurrency is an amalgamation of various technological components elegantly intertwined with one another: public key cryptography, consensus mechanism, and the Merkle Tree data structure, just to name a few.

A new frontier of a similar magnitude to the internet in the 1990s, the advent of cryptocurrencies made it possible for us to reimagine the entire stack of our financial system — away from the inefficient, centralized, and opaque nature of fiat money.

Money is the lifeblood of the economy. Cryptocurrency might just be the messiah the world desperately needs: a superior form of money to catalyze a fairer, freer economy.

SegWit → Taproot

SegWit is an upgrade to segregate witness data (digital signature) from transaction, and have it appended at the end of the block in form of a compact root signature representing each transaction (75% smaller in size, freeing up block space).

Taproot utilizes this new witness data from the previous SegWit upgrade to enable Schnorr schemes (allows aggregated signatures and multisigs, while maintaining constant data size), which in turn paves the way for the Lightning Network.

Further reading: https://bitcoinmagazine.com/technical/bitcoin-taproot-explainer

Taproot effect: comparing ECDSA vs Schnorr signature schemes

• Onchain multisig structure: multiple public keys (signers are revealed onchain) vs one public key (signers are hidden — onchain only shows one public key signing a transaction);

• Key-pair programmability: non-linear (adapting keys like to encrypt/decrypt is hard — involves complicated math prone to errors) vs linear (adapting keys is a matter of simple addition/subtraction). In Schnorr, when you add the same thing to both public and private key, they will still be a valid key pair: when you “tweak” a Schnorr public key with a Merkle root (add that Merkle root to the public key), then you can simply add the Merkle root to the original private key and generate the spending key for the new tweaked public key.

The ability to commit to different spending scripts in a Merkle tree and only reveal the used script is a massive scalability win in terms of smart contract complexity that is possible to build on Bitcoin. This is how the Taproot upgrade paves the way for Lightning Network: all of the non-cooperative clauses in a Lightning channel such as penalty keys, or timelocks to allow them to be used, can be buried under a MAST with Taproot.

Examples of Taproot-enabled primitives

• PSBT (partially signed bitcoin transactions): allows multiple parties to construct a conditional transaction and combine signatures for it offchain, before one party aggregates the received signatures and send the transaction onchain. Since signatures only represent authorization of a transaction under a specific condition that the signer has agreed to, the broadcaster can’t just arbitrarily modify the broadcasted transaction: the aggregated signatures will become gibberish, and the transaction won’t get broadcasted onchain. For example: a trade where bc123 signs for “send 1 BTC to bcABC if bcABC sends 1000 ORDI to bc123”, bcABC takes bc123’s signature and adds their own “send 1000 ORDI to bc123 if bc123 send 1 BTC to bcABC” signature, and then combine both signatures together to finally broadcast this PSBT onchain (where it’d be represented as a single Script, to be executed atomically by miners upon inclusion).

• DLC (discreet locked contracts): allows an oracle to act as the third-party in 2-of-2 multisigs — event triggers are agreed upon and laid down in prior, and in the future, the oracle’s public key will send its signature to the DLC, indicating for an event from the list (and allowing the party associated with the backed event to claim the multisig funds).

An example use case is Liquidium, a peer-to-peer Bitcoin lending dApp. It utilizes PSBT to construct the lending DLC Script in the first place (involving lender and borrower), where its oracle will feed an event trigger into this onchain 2-of-2 multisig to determine the outcome (if the oracle feeds “borrower has paid 2 BTC” event, the borrower can then claim the Ordinal NFT within this 2-of-2 multisig; if no event is emitted until the multisig’s HTLC expiry date, the lender can then claim the Ordinal NFT).

Caveat: the trust lies on the oracle. If the Liquidium oracle feeds a false event, the onchain multisig is then compelled to execute based on the pre-programmed outcome, as it can’t discern between fraudulent or “truthful” offchain events.

Lightning Network

The Lightning Network (LN) is essentially a network enabling off-chain payment channels between two counterparties, where both parties deposit to a shared on-chain multisig address and conduct off-chain payments (in which each transaction is stacked on top of the previous transaction’s hash). To close the channel, any party may submit the most recent transaction hash onchain — upon a certain timelock period with no challenges (timelock logic lives natively on the multisig), the multisig redistributes the funds to its constituent addresses based on the submitted transaction hash.

This timelock exists to counteract malicious transaction hash submissions (not submitting the latest transaction hash), so that the honest party is given enough time to submit the latest transaction hash (if not, once the funds are released on-chain, there’s nothing the honest party can do to reverse the transaction). As a deterrent, the multisig is embedded with “justice close” (logic is on-chain), such that even if a party submits a malicious transaction hash, as long as the multisig is able to receive the honest transaction hash within the timelock period, the entirety of the channel’s balance will be forfeited to the honest party.

LN Watchtowers

Watchtowers are opt-in third-party nodes that store your channel’s list of transaction hashes, such that in the event of an attempted fraud, they can submit the latest transaction hash to the on-chain multisig on your behalf to thwart the breach. Not relying on watchtowers means you need to be chronically online to submit the transaction hash on your own within the timelock period in case of a breach attempt. If you don’t make it on time, the multisig will have no choice but to release the funds under the attacker’s terms (the transaction hash could even indicate that you transferred all of your bitcoins to the attacker).

Relying on watchtowers means they’ll be the ones chronically online to monitor for any attempted breach against you. If two peers opted in to watchtowers, the multisig can be configured to accommodate them such that on any channel closing events, they can step in (if needed) to thwart a fraudulent transaction hash by providing the latest transaction hash, but can do nothing to the multisig if there’s no channel closing events. Now, watchtowers are altruistically maintained by Lightning core devs, and that all channels are opted-in by default.

In practice, users don’t directly setup on-chain multisig and run a Lightning node on their own as it’s too cumbersome. Instead, they rely on Lightning nodes to transact on their behalf (and maintain channels with other nodes). As such, most users are actually custodying their bitcoins with a trusted Lightning node provider (where theoretically, they can collude with other nodes to force close channels, then send the bitcoins in custody to their own addresses).

The adoption chasm of non-custodial LN

The fact that users are required to run their own Lightning node to ensure their BTC is non-custodial, is a bottleneck to adoption (contrary to cypherpunks belief, no one wants to run a node).

This is notwithstanding the complicated liquidity management processes for your own Lightning channel. For example: if routing a payment from A to B typically involves four intermediate channels, it would in total require preloaded values five times as large as the actual payment amount — the typical user, who might upload, say, USD 200 to finance small expenses, would certainly unwilling to foot another USD 800 just to support the network's routing capacity.

There are actually non-custodial Lightning wallet solutions (i.e., Phoenix) out there that allows you to run your own Lightning node straight from an app on your phone — as long as the app is running in the background, your Lightning node remains active.

But this is a stop-gap solution IMO: channel funding is still trusted (users have to deposit via Phoenix’s Lightning node, which then routes the payment to the user’s own channel), and channel closing is also trusted (users route payment to Phoenix’s Lightning node, which then makes the transaction to the user’s on-chain address). The holy grail, at least for me, is still a trust-minimized 1-to-1 BTC bridge to a scalable PoS layer. At least, users don’t need to run a node to be non-custodial – if they feel a PoS network’s security is degrading (or just don’t align with its values), they are free to exit back to mainchain and explore other PoS layer options.

Ordinal Theory

Ordinals are merely file inscriptions on sats. Due to Bitcoin's UTXO model, each sat can be serialized based on the block it's issued (the 1st BTC mined on genesis block represents sat #1-100m; the 50th BTC mined represents sat #5b-500b; etc.). Any arbitrary data can then be "inscribed" into these unique sats via its witness data field (originally meant to store transaction signatures: SegWit introduces a diff signature scheme that is appended at the end of the block instead of each transaction, resulting in 75% smaller data size), tying the inscribed data to the unique sat (if the sat moves address, the inscription follows).

Note that ordinal numbers and sat rarity are different. Assume you hold a 0.5 BTC balance since 2015 (which consists of numerous sats). Upon the release of ordinal theory, you actually found out that you hold sat #100, meaning that some sats forming your 0.5 BTC balance is actually mined from genesis!

Even if you only choose to inscribe the sat in 2025, the fact that your sat is #100 would definitely have you subject to monstrous bids! Theoretically speaking, if we strictly look from a monetary-maximizing lens, the best combo would be to inscribe a sub-10k ordinal (you're among the first 10k inscriptors) with a sought-after sat (e.g., #1000, #10000, #69420, etc.).

BRC20

BRC20 is a standard built on top of ordinal theory. Instead of inscribing files, they inscribe JSON to create a fungible token (e.g: "deploy ORDI token, max supply 1b, max mint 1k per address"). People can inscribe another JSON to a random sat for minting ("mint 1k ORDI"), which can then be transferred to anyone. If you hold a "mint 1k ORDI" ordinal, and wants to transfer 200 ORDI, you do additional JSON inscriptions on more random sats to break your "1k ORDI" ordinal to smaller chunks ("300 ORDI chunk", "200 ORDI chunk", "500 ORDI chunk"), then transfer the "200 ORDI chunk" ordinal to your counterparty.

Anyone can index the chain to correctly derive each address' BRC20 balances – easy to identify "faulty" inscriptions and disregard it just by referencing the chain's ordering (e.g: a "mint 2k ORDI" inscription is ignored since it doesn't obey the "max mint 1k ORDI per address" parameter; a "500 ORDI chunk" inscription is ignored since the address doesn't currently hold ordinals like "mint 1k ORDI" or "800 ORDI chunk", that if added together doesn't total to at least 500 ORDI balance).

Runes

On paper, the only glaring difference between BRC20s and Runes is on how data is stored. BRC20 inscribes data on sats, while Runes make use of the OP_RETURN field to store data. However, this seemingly inconsequential data storage choice, presents wildly differing tradeoffs for each respective protocol.

BRC20 has a high onchain footprint, due to the high amounts of UTXOs being produced for its inscriptions. Runes aims to solve this by identifying unspent UTXOs, then uses this to create new transactions containing protocol messages with details like ID, output index, and amount, all stored in an OP_RETURN output.

The result is less “junk” UTXOs, which means less onchain bloat (and faster, cheaper, and more dependable transactions compared to BRC20s).