I can't believe they’d even think it works!

Developers are usually interviewed before being hired, right? Every organization wants candidates who meet their needs. But they also want to avoid fraud.

There are cheaters in every field. Only two come to mind for the hiring process:

• Lying on a resume.

• Cheating on an online test.

Recently, I observed another one. One of my coworkers invited me to replace another developer during an online interview! I was astonished, but it’s not new.

The specifics

My ex-colleague recently texted me. No one from your former office will ever approach you after a year unless they need something.

Which was the case. My coworker said his wife needed help as a programmer. I was glad someone asked for my help, but I'm still a junior programmer.

Then he informed me his wife was selected for a fantastic job interview. He said he could help her with the online test, but he needed someone to help with the online interview.

Okay, I guess. Preparing for an online interview is beneficial. But then he said she didn't need to be ready. She needed someone to take her place.

I told him it wouldn't work. Every remote online interview I've ever seen required an open camera.

What followed surprised me. She'd ask to turn off the camera, he said.

I asked why.

He told me if an applicant is unwell, the interviewer may consider an off-camera interview. His wife will say she's sick and prefers no camera.

The plan left me speechless. I declined politely. He insisted and promised $2k if she got the job.

I felt insulted and told him if he persisted, I'd inform his office. I was furious. Later, I apologized and told him to stop.

I'm not sure what they did after that

I'm not sure if they found someone or listened to me. They probably didn't. How would she do the job if she even got it?

It's an internship, he said. With great pay, though. What should an intern do?

I suggested she do the interview alone. Even if she failed, she'd gain confidence and valuable experience.

Conclusion

Many interviewees cheat. My profession is vital to me, thus I'd rather improve my abilities and apply honestly. It's part of my identity.

Am I truthful? Most professionals are not. They fabricate their CVs. Often.

When you support interview cheating, you encourage more cheating! When someone cheats, another qualified candidate may not obtain the job.

One day, that could be you or me.

I relocated my notes database from Roam Research to Obsidian earlier this year expecting to stay there for a long. Obsidian is a terrific tool, and I explained my move in that post.

Moving everything to Tana faster than intended. Tana? Why?

Tana is just another note-taking app, but it does it differently. Three note-taking apps existed before Tana:

1. simple note-taking programs like Apple Notes and Google Keep.

2. Roam Research and Obsidian are two graph-style applications that assisted connect your notes.

3. You can create effective tables and charts with data-focused tools like Notion and Airtable.

Tana is the first great software I've encountered that combines graph and data notes. Google Keep will certainly remain my rapid notes app of preference. This Shu Omi video gives a good overview:

Tana handles everything I did in Obsidian with books, people, and blog entries, plus more. I can find book quotes, log my workouts, and connect my thoughts more easily. It should make writing blog entries notes easier, so we'll see.

Tana is now invite-only, but if you're interested, visit their site and sign up. As Shu noted in the video above, the product hasn't been published yet but seems quite polished.

Whether I stay with Tana or not, I'm excited to see where these apps are going and how they can benefit us all.

Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.

To boost employee efficiency.

Not surprising. Few envisioned Google declaring a productivity drive.

Sunder Pichai's speech:

“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”

The primary driver driving Google's efficiency push is:

Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.

Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.

Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.

Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.

In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.

FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.

Google has hardly ever discussed effectiveness:

Apparently openly.

Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.

Amazon trumps Google. In reality, it treats its employees poorly.

Google was the founding father of the modern-day open culture.

Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.

20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.

After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.

• Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?

• If so, would Google follow suit?

• If so, how does Google go about doing it?

Before discussing Google's likely plan, let's examine programming productivity.

What determines a programmer's productivity is simple:

How would we answer Google's questions?

As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.

Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.

Deconstruct our main question.

• How exactly do you change the culture of the firm so that productivity increases?

• How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.

• How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)

• How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?

When implementing a large-scale organizational change, success must be carefully measured.

The fastest way to do something is to do it right, no matter how long it takes.

You require clearly-defined group/team/role segregation and solid pass/fail matrices to:

• You can give performers rewards.

• Ones that are average can be inspired to improve

• Underachievers may receive assistance or, in the worst-case scenario, rehabilitation

As a 20-year programmer, I associate productivity with greatness.

Doing something well, no matter how long it takes, is the fastest way to do it.

Let's discuss a programmer's productivity.

Why productivity is a strange term in programming:

Productivity is work per unit of time.

Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.

As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.

All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.

Time is money — is not just a proverb, but an economical fact.

Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.

Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.

Programming productivity isn't linear, unlike manufacturing and maintenance.

Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.

Reversing the programming duties has no effect. Experts aren't needed for productivity.

These patterns remind me of an XKCD comic.

Programming productivity depends on two factors:

• The capacity of the programmer and his or her command of the principles of computer science

• His or her productive bursts, how often they occur, and how long they last as they engineer the answer

At some point, productivity measurement becomes Schrödinger’s cat.

Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.

Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.

Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.

Google can pull it off if it wants to.

What Google meant in reality when it said that employee productivity has decreased:

When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.

They can't multiply their work's influence over time.

• Programmers who produce excellent modules or products are unsure on how to use them.

• The best data scientists are unable to add the proper parameters in their models.

• Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.

• Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.

• Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.

So, Google employees aren't productive.

How to fix it?

• Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.

• SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.

• Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.

• Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.

• Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).

In conclusion:

Software development isn't linear. Why should the makers be measured?

Notation for The Big O

I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)

The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)

Google (or any large corporation) can do this.

1. Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.

2. Plot the influence of each employee over time using the X and Y axes, respectively.

3. Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).

4. Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.

After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.

Example of a Big(O) Category:

If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.

The Google interview truth:

O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.

O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.

CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.

Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.

UX/UI Designers must still prototype UI elements despite improved design tools.

All test cases are proportional to use cases/functional units, hence testers' work is O(N).

Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.

Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.

Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.

The fastest way to do something is to do it right, no matter how long it takes.

Conclusion:

Google is at the liberal extreme of the employee-handling spectrum

Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.

Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.

Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.

Any attempt to redefine people's measurements will affect the organization emotionally.

The more Google compares apples to apples, the higher its chances for future rebirth.

Introduction

Markets rely on knowledge.

The internet provided practically endless knowledge and wisdom. Humanity has never seen such leverage. Technology's progress drives us to adapt to a changing world, changing our routines and behaviors.

In a digital age, people may struggle to live in the analogue world of their upbringing. Can those who can't adapt change their lives? I won't answer. We should teach those who are willing to learn, nevertheless. Unravel the modern world's riddles and give them wisdom.

Adapt or die . Accept the future or remain behind.

This essay will help you comprehend Bitcoin better than most market participants and the general public. Let's dig into Bitcoin.

Join me.

Ascension

Bitcoin.org was registered in August 2008. Bitcoin whitepaper was published on 31 October 2008. The document intrigued and motivated people around the world, including technical engineers and sovereignty seekers. Since then, Bitcoin's whitepaper has been read and researched to comprehend its essential concept.

I recommend reading the whitepaper yourself. You'll be able to say you read the Bitcoin whitepaper instead of simply Googling "what is Bitcoin" and reading the fundamental definition without knowing the revolution's scope. The article links to Bitcoin's whitepaper. To avoid being overwhelmed by the whitepaper, read the following article first.

Bitcoin isn't the first peer-to-peer digital currency. Hashcash or Bit Gold were once popular cryptocurrencies. These two Bitcoin precursors failed to gain traction and produce the network effect needed for general adoption. After many struggles, Bitcoin emerged as the most successful cryptocurrency, leading the way for others.

Satoshi Nakamoto, an active bitcointalk.org user, created Bitcoin. Satoshi's identity remains unknown. Satoshi's last bitcointalk.org login was 12 December 2010. Since then, he's officially disappeared. Thus, conspiracies and riddles surround Bitcoin's creators. I've heard many various theories, some insane and others well-thought-out.

It's not about who created it; it's about knowing its potential. Since its start, Satoshi's legacy has changed the world and will continue to.

Block-by-block blockchain

Bitcoin is a distributed ledger. What's the meaning?

Everyone can view all blockchain transactions, but no one can undo or delete them.

Imagine you and your friends routinely eat out, but only one pays. You're careful with money and what others owe you. How can everyone access the info without it being changed?

You'll keep a notebook of your evening's transactions. Everyone will take a page home. If one of you changed the page's data, the group would notice and reject it. The majority will establish consensus and offer official facts.

Miners add a new Bitcoin block to the main blockchain every 10 minutes. The appended block contains miner-verified transactions. Now that the next block has been added, the network will receive the next set of user transactions.

Bitcoin Proof of Work—prove you earned it

Any firm needs hardworking personnel to expand and serve clients. Bitcoin isn't that different.

Bitcoin's Proof of Work consensus system needs individuals to validate and create new blocks and check for malicious actors. I'll discuss Bitcoin's blockchain consensus method.

Proof of Work helps Bitcoin reach network consensus. The network is checked and safeguarded by CPU, GPU, or ASIC Bitcoin-mining machines (Application-Specific Integrated Circuit).

Every 10 minutes, miners are rewarded in Bitcoin for securing and verifying the network. It's unlikely you'll finish the block. Miners build pools to increase their chances of winning by combining their processing power.

In the early days of Bitcoin, individual mining systems were more popular due to high maintenance costs and larger earnings prospects. Over time, people created larger and larger Bitcoin mining facilities that required a lot of space and sophisticated cooling systems to keep machines from overheating.

Proof of Work is a vital part of the Bitcoin network, as network security requires the processing power of devices purchased with fiat currency. Miners must invest in mining facilities, which creates a new business branch, mining facilities ownership. Bitcoin mining is a topic for a future article.

More mining, less reward

Bitcoin is usually scarce.

Why is it rare? It all comes down to 21,000,000 Bitcoins.

Were all Bitcoins mined? Nope. Bitcoin's supply grows until it hits 21 million coins. Initially, 50BTC each block was mined, and each block took 10 minutes. Around 2140, the last Bitcoin will be mined.

But 50BTC every 10 minutes does not give me the year 2140. Indeed careful reader. So important is Bitcoin's halving process.

What is halving?

The block reward is halved every 210,000 blocks, which takes around 4 years. The initial payout was 50BTC per block and has been decreased to 25BTC after 210,000 blocks. First halving occurred on November 28, 2012, when 10,500,000 BTC (50%) had been mined. As of April 2022, the block reward is 6.25BTC and will be lowered to 3.125BTC by 19 March 2024.

The halving method is tied to Bitcoin's hashrate. Here's what "hashrate" means.

What if we increased the number of miners and hashrate they provide to produce a block every 10 minutes? Wouldn't we manufacture blocks faster?

Every 10 minutes, blocks are generated with little asymmetry. Due to the built-in adaptive difficulty algorithm, the overall hashrate does not affect block production time. With increased hashrate, it's harder to construct a block. We can estimate when the next halving will occur because 10 minutes per block is fixed.

Building with nodes and blocks

For someone new to crypto, the unusual terms and words may be overwhelming. You'll also find everyday words that are easy to guess or have a vague idea of what they mean, how they work, and what they do. Consider blockchain technology.

Nodes and blocks: Think about that for a moment. What is your first idea?

The blockchain is a chain of validated blocks added to the main chain. What's a "block"? What's inside?

The block is another page in the blockchain book that has been filled with transaction information and accepted by the majority.

We won't go into detail about what each block includes and how it's built, as long as you understand its purpose.

What about nodes?

Nodes, along with miners, verify the blockchain's state independently. But why?

To create a full blockchain node, you must download the whole Bitcoin blockchain and check every transaction against Bitcoin's consensus criteria.

What's Bitcoin's size? 

In April 2022, the Bitcoin blockchain was 389.72GB.

Bitcoin's blockchain has miners and node runners.

Let's revisit the US gold rush. Miners mine gold with their own power (physical and monetary resources) and are rewarded with gold (Bitcoin). All become richer with more gold, and so does the country.

Nodes are like sheriffs, ensuring everything is done according to consensus rules and that there are no rogue miners or network users.

Lost and held bitcoin

Does the Bitcoin exchange price match each coin's price? How many coins remain after 21,000,000? 21 million or less?

Common reason suggests a 21 million-coin supply.

What if I lost 1BTC from a cold wallet?

What if I saved 1000BTC on paper in 2010 and it was damaged?

What if I mined Bitcoin in 2010 and lost the keys?

Satoshi Nakamoto's coins? Since then, those coins haven't moved.

How many BTC are truly in circulation?

Many people are trying to answer this question, and you may discover a variety of studies and individual research on the topic. Be cautious of the findings because they can't be evaluated and the statistics are hazy guesses.

On the other hand, we have long-term investors who won't sell their Bitcoin or will sell little amounts to cover mining or living needs.

The price of Bitcoin is determined by supply and demand on exchanges using liquid BTC. How many BTC are left after subtracting lost and non-custodial BTC? 

We have significantly less Bitcoin in circulation than you think, thus the price may not reflect demand if we knew the exact quantity of coins available.

True HODLers and diamond-hand investors won't sell you their coins, no matter the market.

What's UTXO?

Unspent (U) Transaction (TX) Output (O)

Imagine taking a $100 bill to a store. After choosing a drink and munchies, you walk to the checkout to pay. The cashier takes your $100 bill and gives you $25.50 in change. It's in your wallet.

Is it simply 100$? No way.

The $25.50 in your wallet is unrelated to the $100 bill you used. Your wallet's $25.50 is just bills and coins. Your wallet may contain these coins and bills:

2x 10$ 1x 10$

1x 5$ or 3x 5$

1x 0.50$ 2x 0.25$

Any combination of coins and bills can equal $25.50. You don't care, and I'd wager you've never ever considered it.

That is UTXO. Now, I'll detail the Bitcoin blockchain and how UTXO works, as it's crucial to know what coins you have in your (hopefully) cold wallet.

You purchased 1BTC. Is it all? No. UTXOs equal 1BTC. Then send BTC to a cold wallet. Say you pay 0.001BTC and send 0.999BTC to your cold wallet. Is it the 1BTC you got before? Well, yes and no. The UTXOs are the same or comparable as before, but the blockchain address has changed. It's like if you handed someone a wallet, they removed the coins needed for a network charge, then returned the rest of the coins and notes.

UTXO is a simple concept, but it's crucial to grasp how it works to comprehend dangers like dust attacks and how coins may be tracked.

Lightning Network: fast cash

You've probably heard of "Layer 2 blockchain" projects.

What does it mean?

Layer 2 on a blockchain is an additional layer that increases the speed and quantity of transactions per minute and reduces transaction fees.

Imagine going to an obsolete bank to transfer money to another account and having to pay a charge and wait. You can transfer funds via your bank account or a mobile app without paying a fee, or the fee is low, and the cash appear nearly quickly. Layer 1 and 2 payment systems are different.

Layer 1 is not obsolete; it merely has more essential things to focus on, including providing the blockchain with new, validated blocks, whereas Layer 2 solutions strive to offer Layer 1 with previously processed and verified transactions. The primary blockchain, Bitcoin, will only receive the wallets' final state. All channel transactions until shutting and balancing are irrelevant to the main chain.

Layer 2 and the Lightning Network's goal are now clear. Most Layer 2 solutions on multiple blockchains are created as blockchains, however Lightning Network is not. Remember the following remark, as it best describes Lightning.

Lightning Network connects public and private Bitcoin wallets.

Opening a private channel with another wallet notifies just two parties. The creation and opening of a public channel tells the network that anyone can use it.

Why create a public Lightning Network channel?

Every transaction through your channel generates fees.

Money, if you don't know.

See who benefits when in doubt.

Anonymity, huh?

Bitcoin anonymity? Bitcoin's anonymity was utilized to launder money.

Well… You've heard similar stories. When you ask why or how it permits people to remain anonymous, the conversation ends as if it were just a story someone heard.

Bitcoin isn't private. Pseudonymous.

What if someone tracks your transactions and discovers your wallet address? Where is your anonymity then?

Bitcoin is like bulletproof glass storage; you can't take or change the money. If you dig and analyze the data, you can see what's inside.

Every online action leaves a trace, and traces may be tracked. People often forget this guideline.

A tool like that can help you observe what the major players, or whales, are doing with their coins when the market is uncertain. Many people spend time analyzing on-chain data. Worth it?

Ask yourself a question. What are the big players' options?  Do you think they're letting you see their wallets for a small on-chain data fee?

Instead of short-term behaviors, focus on long-term trends.

More wallet transactions leave traces. Having nothing to conceal isn't a defect. Can it lead to regulating Bitcoin so every transaction is tracked like in banks today?

But wait. How can criminals pay out Bitcoin? They're doing it, aren't they?

Mixers can anonymize your coins, letting you to utilize them freely. This is not a guide on how to make your coins anonymous; it could do more harm than good if you don't know what you're doing.

Remember, being anonymous attracts greater attention.

Bitcoin isn't the only cryptocurrency we can use to buy things. Using cryptocurrency appropriately can provide usability and anonymity. Monero (XMR), Zcash (ZEC), and Litecoin (LTC) following the Mimblewimble upgrade are examples.

Summary

Congratulations! You've reached the conclusion of the article and learned about Bitcoin and cryptocurrency. You've entered the future.

You know what Bitcoin is, how its blockchain works, and why it's not anonymous. I bet you can explain Lightning Network and UTXO to your buddies.

Markets rely on knowledge. Prepare yourself for success before taking the first step. Let your expertise be your edge.

This article is a summary of this one.

Some AI-generated artworks sell for enormous sums of money.

But can you sell AI-Generated Artwork?

Simple answer: yes.

However, not all AI services enable allow usage and redistribution of images.

Let's check some of my favorite AI text-to-image generators:

• Dall-E2 by OpenAI

• MidJourney

• Dream by Wombo

Dall-E2 by OpenAI

The AI art generator Dall-E2 is powerful. Since it’s still in beta, you can join the waitlist here.

OpenAI DOES NOT allow the use and redistribution of any image for commercial purposes.

Here's the policy as of April 6, 2022.

Here are some images from Dall-E2’s webpage to show its art quality.

Several Reddit users reported receiving pricing surveys from OpenAI.

This suggests the company may bring out a subscription-based tier and a commercial license to sell images soon.

MidJourney

I like Midjourney's art generator. It makes great AI images. Here are some samples:

Standard Licenses are available for $10 per month.

Standard License allows you to use, copy, modify, merge, publish, distribute, and/or sell copies of the images, except for blockchain technologies.

If you utilize or distribute the Assets using blockchain technology, you must pay MidJourney 20% of revenue above $20,000 a month or engage in an alternative agreement.

Here's their copyright and trademark page.

Dream by Wombo

Dream is one of the first public AI art generators.

This AI program is free, easy to use, and Wombo gives a royalty-free license to copy or share artworks.

Users own all artworks generated by the tool. Including all related copyrights or intellectual property rights.

Here’s Wombos' intellectual property policy.

Final Reflections

AI is creating a new sort of art that's selling well. It’s becoming popular and valued, despite some skepticism.

Now that you know MidJourney and Wombo let you sell AI-generated art, you need to locate buyers. There are several ways to achieve this, but that’s for another story.