An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2
(Edited)
More on Web3 & Crypto
Isaac Benson
11 months ago
What's the difference between Proof-of-Time and Proof-of-History?
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.
Vitalik
1 year ago
Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.
Shan Vernekar
5 months ago
How the Ethereum blockchain's transactions are carried out
Overview
Ethereum blockchain is a network of nodes that validate transactions. Any network node can be queried for blockchain data for free. To write data as a transition requires processing and writing to each network node's storage. Fee is paid in ether and is also called as gas.
We'll examine how user-initiated transactions flow across the network and into the blockchain.
Flow of transactions
A user wishes to move some ether from one external account to another. He utilizes a cryptocurrency wallet for this (like Metamask), which is a browser extension.
The user enters the desired transfer amount and the external account's address. He has the option to choose the transaction cost he is ready to pay.
Wallet makes use of this data, signs it with the user's private key, and writes it to an Ethereum node. Services such as Infura offer APIs that enable writing data to nodes. One of these services is used by Metamask. An example transaction is shown below. Notice the “to” address and value fields.
var rawTxn = {
nonce: web3.toHex(txnCount),
gasPrice: web3.toHex(100000000000),
gasLimit: web3.toHex(140000),
to: '0x633296baebc20f33ac2e1c1b105d7cd1f6a0718b',
value: web3.toHex(0),
data: '0xcc9ab24952616d6100000000000000000000000000000000000000000000000000000000'
};The transaction is written to the target Ethereum node's local TRANSACTION POOL. It informed surrounding nodes of the new transaction, and those nodes reciprocated. Eventually, this transaction is received by and written to each node's local TRANSACTION pool.
The miner who finds the following block first adds pending transactions (with a higher gas cost) from the nearby TRANSACTION POOL to the block.
The transactions written to the new block are verified by other network nodes.
A block is added to the main blockchain after there is consensus and it is determined to be genuine. The local blockchain is updated with the new node by additional nodes as well.
Block mining begins again next.
The image above shows how transactions go via the network and what's needed to submit them to the main block chain.
References
ethereum.org/transactions How Ethereum transactions function, their data structure, and how to send them via app. ethereum.org
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SAHIL SAPRU
8 months ago
Growth tactics that grew businesses from 1 to 100
Everyone wants a scalable startup.
Innovation helps launch a startup. The secret to a scalable business is growth trials (from 1 to 100).
Growth marketing combines marketing and product development for long-term growth.
Today, I'll explain growth hacking strategies popular startups used to scale.
1/ A Facebook user's social value is proportional to their friends.
Facebook built its user base using content marketing and paid ads. Mark and his investors feared in 2007 when Facebook's growth stalled at 90 million users.
Chamath Palihapitiya was brought in by Mark.
The team tested SEO keywords and MAU chasing. The growth team introduced “people you may know”
This feature reunited long-lost friends and family. Casual users became power users as the retention curve flattened.
Growth Hack Insights: With social network effect the value of your product or platform increases exponentially if you have users you know or can relate with.
2/ Airbnb - Focus on your value propositions
Airbnb nearly failed in 2009. The company's weekly revenue was $200 and they had less than 2 months of runway.
Enter Paul Graham. The team noticed a pattern in 40 listings. Their website's property photos sucked.
Why?
Because these photos were taken with regular smartphones. Users didn't like the first impression.
Graham suggested traveling to New York to rent a camera, meet with property owners, and replace amateur photos with high-resolution ones.
A week later, the team's weekly revenue doubled to $400, indicating they were on track.
Growth Hack Insights: When selling an “online experience” ensure that your value proposition is aesthetic enough for users to enjoy being associated with them.
3/ Zomato - A company's smartphone push ensured growth.
Zomato delivers food. User retention was a challenge for the founders. Indian food customers are notorious for switching brands at the drop of a hat.
Zomato wanted users to order food online and repeat orders throughout the week.
Zomato created an attractive website with “near me” keywords for SEO indexing.
Zomato gambled to increase repeat orders. They only allowed mobile app food orders.
Zomato thought mobile apps were stickier. Product innovations in search/discovery/ordering or marketing campaigns like discounts/in-app notifications/nudges can improve user experience.
Zomato went public in 2021 after users kept ordering food online.
Growth Hack Insights: To improve user retention try to build platforms that build user stickiness. Your product and marketing team will do the rest for them.
4/ Hotmail - Signaling helps build premium users.
Ever sent or received an email or tweet with a sign — sent from iPhone?
Hotmail did it first! One investor suggested Hotmail add a signature to every email.
Overnight, thousands joined the company. Six months later, the company had 1 million users.
When serving an existing customer, improve their social standing. Signaling keeps the top 1%.
5/ Dropbox - Respect loyal customers
Dropbox is a company that puts people over profits. The company prioritized existing users.
Dropbox rewarded loyal users by offering 250 MB of free storage to anyone who referred a friend. The referral hack helped Dropbox get millions of downloads in its first few months.
Growth Hack Insights: Think of ways to improve the social positioning of your end-user when you are serving an existing customer. Signaling goes a long way in attracting the top 1% to stay.
These experiments weren’t hacks. Hundreds of failed experiments and user research drove these experiments. Scaling up experiments is difficult.
Contact me if you want to grow your startup's user base.
Akshad Singi
7 months ago
Four obnoxious one-minute habits that help me save more than 30 hours each week
These four, when combined, destroy procrastination.
You're not rushed. You waste it on busywork.
You'll accept this eventually.
In 2022, the daily average usage of a user on social media is 2.5 hours.
By 2020, 6 billion hours of video were watched each month by Netflix's customers, who used the service an average of 3.2 hours per day.
When we see these numbers, we think "Wow!" People squander so much time as though they don't contribute. True. These are yours. Likewise.
We don't lack time; we just waste it. Once you realize this, you can change your habits to save time. This article explains. If you adopt ALL 4 of these simple behaviors, you'll see amazing benefits.
Time-blocking
Cal Newport's time-blocking trick takes a minute but improves your day's clarity.
Divide the next day into 30-minute (or 5-minute, if you're Elon Musk) segments and assign responsibilities. As seen.
Here's why:
The procrastination that results from attempting to determine when to begin working is eliminated. Procrastination is a given if you choose when to begin working in real-time. Even if you may assume you'll start working in five minutes, it won't take you long to realize that five minutes have turned into an hour. But if you've already determined to start working at 2:00 the next day, your odds of procrastinating are greatly decreased, if not eliminated altogether.
You'll also see that you have a lot of time in a day when you plan your day out on paper and assign chores to each hour. Doing this daily will permanently eliminate the lack of time mindset.
5-4-3-2-1: Have breakfast with the frog!
“If it’s your job to eat a frog, it’s best to do it first thing in the morning. And If it’s your job to eat two frogs, it’s best to eat the biggest one first.”
Eating the frog means accomplishing the day's most difficult chore. It's better to schedule it first thing in the morning when time-blocking the night before. Why?
The day's most difficult task is also the one that causes the most postponement. Because of the stress it causes, the later you schedule it, the more time you risk wasting by procrastinating.
However, if you do it right away in the morning, you'll feel good all day. This is the reason it was set for the morning.
Mel Robbins' 5-second rule can help. Start counting backward 54321 and force yourself to start at 1. If you acquire the urge to work on a goal, you must act within 5 seconds or your brain will destroy it. If you're scheduled to eat your frog at 9, eat it at 8:59. Start working.
Micro-visualisation
You've heard of visualizing to enhance the future. Visualizing a bright future won't do much if you're not prepared to focus on the now and develop the necessary habits. Alexander said:
People don’t decide their futures. They decide their habits and their habits decide their future.
I visualize the next day's schedule every morning. My day looks like this
“I’ll start writing an article at 7:30 AM. Then, I’ll get dressed up and reach the medicine outpatient department by 9:30 AM. After my duty is over, I’ll have lunch at 2 PM, followed by a nap at 3 PM. Then, I’ll go to the gym at 4…”
etc.
This reinforces the day you planned the night before. This makes following your plan easy.
Set the timer.
It's the best iPhone productivity app. A timer is incredible for increasing productivity.
Set a timer for an hour or 40 minutes before starting work. Your call. I don't believe in techniques like the Pomodoro because I can focus for varied amounts of time depending on the time of day, how fatigued I am, and how cognitively demanding the activity is.
I work with a timer. A timer keeps you focused and prevents distractions. Your mind stays concentrated because of the timer. Timers generate accountability.
To pee, I'll pause my timer. When I sit down, I'll continue. Same goes for bottle refills. To use Twitter, I must pause the timer. This creates accountability and focuses work.
Connecting everything
If you do all 4, you won't be disappointed. Here's how:
Plan out your day's schedule the night before.
Next, envision in your mind's eye the same timetable in the morning.
Speak aloud 54321 when it's time to work: Eat the frog! In the morning, devour the largest frog.
Then set a timer to ensure that you remain focused on the task at hand.
Eve Arnold
9 months ago
Your Ideal Position As a Part-Time Creator
Inspired by someone I never met
Inspiration is good and bad.
Paul Jarvis inspires me. He's a web person and writer who created his own category by being himself.
Paul said no thank you when everyone else was developing, building, and assuming greater responsibilities. This isn't success. He rewrote the rules. Working for himself, expanding at his own speed, and doing what he loves were his definitions of success.
Play with a problem that you have
The biggest problem can be not recognizing a problem.
Acceptance without question is deception. When you don't push limits, you forget how. You start thinking everything must be as it is.
For example: working. Paul worked a 9-5 agency work with little autonomy. He questioned whether the 9-5 was a way to live, not the way.
Another option existed. So he chipped away at how to live in this new environment.
Don't simply jump
Internet writers tell people considering quitting 9-5 to just quit. To throw in the towel. To do what you like.
The advice is harmful, despite the good intentions. People think quitting is hard. Like courage is the issue. Like handing your boss a resignation letter.
Nope. The tough part comes after. It’s easy to jump. Landing is difficult.
The landing
Paul didn't quit. Intelligent individuals don't. Smart folks focus on landing. They imagine life after 9-5.
Paul had been a web developer for a long time, had solid clients, and was respected. Hence if he pushed the limits and discovered another route, he had the potential to execute.
Working on the side
Society loves polarization. It’s left or right. Either way. Or chaos. It's 9-5 or entrepreneurship.
But like Paul, you can stretch polarization's limits. In-between exists.
You can work a 9-5 and side jobs (as I do). A mix of your favorites. The 9-5's stability and creativity. Fire and routine.
Remember you can't have everything but anything. You can create and work part-time.
My hybrid lifestyle
Not selling books doesn't destroy my world. My globe keeps spinning if my new business fails or if people don't like my Tweets. Unhappy algorithm? Cool. I'm not bothered (okay maybe a little).
The mix gives me the best of both worlds. To create, hone my skill, and grasp big-business basics. I like routine, but I also appreciate spending 4 hours on Saturdays writing.
Some days I adore leaving work at 5 pm and disconnecting. Other days, I adore having a place to write if inspiration strikes during a run or a discussion.
I’m a part-time creator
I’m a part-time creator. No, I'm not trying to quit. I don't work 5 pm - 2 am on the side. No, I'm not at $10,000 MRR.
I work part-time but enjoy my 9-5. My 9-5 has goodies. My side job as well.
It combines both to meet my lifestyle. I'm satisfied.
Join the Part-time Creators Club for free here. I’ll send you tips to enhance your creative game.