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Sam Bourgi

Sam Bourgi

3 years ago

DAOs are legal entities in Marshall Islands.

The Pacific island state recognizes decentralized autonomous organizations.

The Republic of the Marshall Islands has recognized decentralized autonomous organizations (DAOs) as legal entities, giving collectively owned and managed blockchain projects global recognition.

The Marshall Islands' amended the Non-Profit Entities Act 2021 that now recognizes DAOs, which are blockchain-based entities governed by self-organizing communities. Incorporating Admiralty LLC, the island country's first DAO, was made possible thanks to the amendement. MIDAO Directory Services Inc., a domestic organization established to assist DAOs in the Marshall Islands, assisted in the incorporation.

The new law currently allows any DAO to register and operate in the Marshall Islands.

“This is a unique moment to lead,” said Bobby Muller, former Marshall Islands chief secretary and co-founder of MIDAO. He believes DAOs will help create “more efficient and less hierarchical” organizations.

A global hub for DAOs, the Marshall Islands hopes to become a global hub for DAO registration, domicile, use cases, and mass adoption. He added:

"This includes low-cost incorporation, a supportive government with internationally recognized courts, and a technologically open environment."

According to the World Bank, the Marshall Islands is an independent island state in the Pacific Ocean near the Equator. To create a blockchain-based cryptocurrency that would be legal tender alongside the US dollar, the island state has been actively exploring use cases for digital assets since at least 2018.

In February 2018, the Marshall Islands approved the creation of a new cryptocurrency, Sovereign (SOV). As expected, the IMF has criticized the plan, citing concerns that a digital sovereign currency would jeopardize the state's financial stability. They have also criticized El Salvador, the first country to recognize Bitcoin (BTC) as legal tender.

Marshall Islands senator David Paul said the DAO legislation does not pose the same issues as a government-backed cryptocurrency. “A sovereign digital currency is financial and raises concerns about money laundering,” . This is more about giving DAOs legal recognition to make their case to regulators, investors, and consumers.

More on Web3 & Crypto

Dylan Smyth

Dylan Smyth

3 years ago

10 Ways to Make Money Online in 2022

As a tech-savvy person (and software engineer) or just a casual technology user, I'm sure you've had this same question countless times: How do I make money online? and how do I make money with my PC/Mac?
You're in luck! Today, I will list the top 5 easiest ways to make money online. Maybe a top ten in the future? Top 5 tips for 2022.

1. Using the gig economy

There are many websites on the internet that allow you to earn extra money using skills and equipment that you already own.
I'm referring to the gig economy. It's a great way to earn a steady passive income from the comfort of your own home. For some sites, premium subscriptions are available to increase sales and access features like bidding on more proposals.
Some of these are:

  • Freelancer
  • Upwork
  • Fiverr (⭐ my personal favorite)
  • TaskRabbit

2. Mineprize

MINEPRIZE is a great way to make money online. What's more, You need not do anything! You earn money by lending your idle CPU power to MINEPRIZE.
To register with MINEPRIZE, all you need is an email address and a password. Let MINEPRIZE use your resources, and watch the money roll in! You can earn up to $100 per month by letting your computer calculate. That's insane.

3. Writing

“O Romeo, Romeo, why art thou Romeo?” Okay, I admit that not all writing is Shakespearean. To be a copywriter, you'll need to be fluent in English. Thankfully, we don't have to use typewriters anymore.

Writing is a skill that can earn you a lot of money (claps for the rhyme).
Here are a few ways you can make money typing on your fancy keyboard:
Self-publish a book
Write scripts for video creators
Write for social media
Book-checking
Content marketing help
What a list within a list!

4. Coding

Yes, kids. You've probably coded before if you understand 
You've probably coded before if you understand 

print("hello world");

Computational thinking (or coding) is one of the most lucrative ways to earn extra money, or even as a main source of income.
Of course, there are hardcode coders (like me) who write everything line by line, binary di — okay, that last part is a bit exaggerated.
But you can also make money by writing websites or apps or creating low code or no code platforms.
But you can also make money by writing websites or apps or creating low code or no code platforms.
Some low-code platforms
Sheet : spreadsheets to apps :
Loading... We'll install your new app... No-Code Your team can create apps and automate tasks. Agile…
www.appsheet.com

Low-code platform | Business app creator - Zoho Creator
Work is going digital, and businesses of all sizes must adapt quickly. Zoho Creator is a...
www.zoho.com

Sell your data with TrueSource. NO CODE NEEDED
Upload data, configure your product, and earn in minutes.
www.truesource.io

Cool, huh?

5. Created Content

If we use the internet correctly, we can gain unfathomable wealth and extra money. But this one is a bit more difficult. Unlike some of the other items on this list, it takes a lot of time up front.
I'm referring to sites like YouTube and Medium. It's a great way to earn money both passively and actively. With the likes of Jake- and Logan Paul, PewDiePie (a.k.a. Felix Kjellberg) and others, it's never too late to become a millionaire on YouTube. YouTubers are always rising to the top with great content.

6. NFTs and Cryptocurrency

It is now possible to amass large sums of money by buying and selling digital assets on NFTs and cryptocurrency exchanges. Binance's Initial Game Offer rewards early investors who produce the best results.
One awesome game sold a piece of its plot for US$7.2 million! It's Axie Infinity. It's free and available on Google Play and Apple Store.

7. Affiliate Marketing

Affiliate marketing is a form of advertising where businesses pay others (like bloggers) to promote their goods and services. Here's an example. I write a blog (like this one) and post an affiliate link to an item I recommend buying — say, a camera — and if you buy the camera, I get a commission!
These programs pay well:

  • Elementor
  • AWeber
  • Sendinblue
  • ConvertKit\sLeadpages
  • GetResponse
  • SEMRush\sFiverr
  • Pabbly

8. Start a blog

Now, if you're a writer or just really passionate about something or a niche, blogging could potentially monetize that passion!
Create a blog about anything you can think of. It's okay to start right here on Medium, as I did.

9. Dropshipping

And I mean that in the best possible way — drop shopping is ridiculously easy to set up, but difficult to maintain for some.
Luckily, Shopify has made setting up an online store a breeze. Drop-shipping from Alibaba and DHGate is quite common. You've got a winner if you can find a local distributor willing to let you drop ship their product!

10. Set up an Online Course

If you have a skill and can articulate it, online education is for you.
Skillshare, Pluralsight, and Coursera have all made inroads in recent years, upskilling people with courses that YOU can create and earn from.

That's it for today! Please share if you liked this post. If not, well —

Percy Bolmér

Percy Bolmér

3 years ago

Ethereum No Longer Consumes A Medium-Sized Country's Electricity To Run

The Merge cut Ethereum's energy use by 99.5%.

Image by Percy Bolmér. Gopher by Takuya Ueda, Original Go Gopher by Renée French (CC BY 3.0)

The Crypto community celebrated on September 15, 2022. This day, Ethereum Merged. The entire blockchain successfully merged with the Beacon chain, and it was so smooth you barely noticed.

Many have waited, dreaded, and longed for this day.

Some investors feared the network would break down, while others envisioned a seamless merging.

Speculators predict a successful Merge will lead investors to Ethereum. This could boost Ethereum's popularity.

What Has Changed Since The Merge

The merging transitions Ethereum mainnet from PoW to PoS.

PoW sends a mathematical riddle to computers worldwide (miners). First miner to solve puzzle updates blockchain and is rewarded.

The puzzles sent are power-intensive to solve, so mining requires a lot of electricity. It's sent to every miner competing to solve it, requiring duplicate computation.

PoS allows investors to stake their coins to validate a new transaction. Instead of validating a whole block, you validate a transaction and get the fees.

You can validate instead of mine. A validator stakes 32 Ethereum. After staking, the validator can validate future blocks.

Once a validator validates a block, it's sent to a randomly selected group of other validators. This group verifies that a validator is not malicious and doesn't validate fake blocks.

This way, only one computer needs to solve or validate the transaction, instead of all miners. The validated block must be approved by a small group of validators, causing duplicate computation.

PoS is more secure because validating fake blocks results in slashing. You lose your bet tokens. If a validator signs a bad block or double-signs conflicting blocks, their ETH is burned.

Theoretically, Ethereum has one block every 12 seconds, so a validator forging a block risks burning 1 Ethereum for 12 seconds of transactions. This makes mistakes expensive and risky.

What Impact Does This Have On Energy Use?

Cryptocurrency is a natural calamity, sucking electricity and eating away at the earth one transaction at a time.

Many don't know the environmental impact of cryptocurrencies, yet it's tremendous.

A single Ethereum transaction used to use 200 kWh and leave a large carbon imprint. This update reduces global energy use by 0.2%.

Energy consumption PER transaction for Ethereum post-merge. Image from Digiconomist

Ethereum will submit a challenge to one validator, and that validator will forward it to randomly selected other validators who accept it.

This reduces the needed computing power.

They expect a 99.5% reduction, therefore a single transaction should cost 1 kWh.

Carbon footprint is 0.58 kgCO2, or 1,235 VISA transactions.

This is a big Ethereum blockchain update.

I love cryptocurrency and Mother Earth.

Nitin Sharma

Nitin Sharma

2 years ago

Web3 Terminology You Should Know

The easiest online explanation.

Photo by Hammer & Tusk on Unsplash

Web3 is growing. Crypto companies are growing.

Instagram, Adidas, and Stripe adopted cryptocurrency.

Source: Polygon

Bitcoin and other cryptocurrencies made web3 famous.

Most don't know where to start. Cryptocurrency, DeFi, etc. are investments.

Since we don't understand web3, I'll help you today.

Let’s go.

1. Web3

It is the third generation of the web, and it is built on the decentralization idea which means no one can control it.

There are static webpages that we can only read on the first generation of the web (i.e. Web 1.0).

Web 2.0 websites are interactive. Twitter, Medium, and YouTube.

Each generation controlled the website owner. Simply put, the owner can block us. However, data breaches and selling user data to other companies are issues.

They can influence the audience's mind since they have control.

Assume Twitter's CEO endorses Donald Trump. Result? Twitter would have promoted Donald Trump with tweets and graphics, enhancing his chances of winning.

We need a decentralized, uncontrollable system.

And then there’s Web3.0 to consider. As Bitcoin and Ethereum values climb, so has its popularity. Web3.0 is uncontrolled web evolution. It's good and bad.

Dapps, DeFi, and DAOs are here. It'll all be explained afterwards.

2. Cryptocurrencies:

No need to elaborate.

Bitcoin, Ethereum, Cardano, and Dogecoin are cryptocurrencies. It's digital money used for payments and other uses.

Programs must interact with cryptocurrencies.

3. Blockchain:

Blockchain facilitates bitcoin transactions, investments, and earnings.

This technology governs Web3. It underpins the web3 environment.

Let us delve much deeper.

Blockchain is simple. However, the name expresses the meaning.

Blockchain is a chain of blocks.

Let's use an image if you don't understand.

The graphic above explains blockchain. Think Blockchain. The block stores related data.

Here's more.

4. Smart contracts

Programmers and developers must write programs. Smart contracts are these blockchain apps.

That’s reasonable.

Decentralized web3.0 requires immutable smart contracts or programs.

5. NFTs

Blockchain art is NFT. Non-Fungible Tokens.

Explaining Non-Fungible Token may help.

Two sorts of tokens:

  1. These tokens are fungible, meaning they can be changed. Think of Bitcoin or cash. The token won't change if you sell one Bitcoin and acquire another.

  2. Non-Fungible Token: Since these tokens cannot be exchanged, they are exclusive. For instance, music, painting, and so forth.

Right now, Companies and even individuals are currently developing worthless NFTs.

The concept of NFTs is much improved when properly handled.

6. Dapp

Decentralized apps are Dapps. Instagram, Twitter, and Medium apps in the same way that there is a lot of decentralized blockchain app.

Curve, Yearn Finance, OpenSea, Axie Infinity, etc. are dapps.

7. DAOs

DAOs are member-owned and governed.

Consider it a company with a core group of contributors.

8. DeFi

We all utilize centrally regulated financial services. We fund these banks.

If you have $10,000 in your bank account, the bank can invest it and retain the majority of the profits.

We only get a penny back. Some banks offer poor returns. To secure a loan, we must trust the bank, divulge our information, and fill out lots of paperwork.

DeFi was built for such issues.

Decentralized banks are uncontrolled. Staking, liquidity, yield farming, and more can earn you money.

Web3 beginners should start with these resources.

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Amelia Winger-Bearskin

Amelia Winger-Bearskin

3 years ago

Hate NFTs? I must break some awful news to you...

If you think NFTs are awful, check out the art market.

The fervor around NFTs has subsided in recent months due to the crypto market crash and the media's short attention span. They were all anyone could talk about earlier this spring. Last semester, when passions were high and field luminaries were discussing "slurp juices," I asked my students and students from over 20 other universities what they thought of NFTs.

According to many, NFTs were either tasteless pyramid schemes or a new way for artists to make money. NFTs contributed to the climate crisis and harmed the environment, but so did air travel, fast fashion, and smartphones. Some students complained that NFTs were cheap, tasteless, algorithmically generated schlock, but others asked how this was different from other art.

a digital Billboard showed during the 4th annual NFT.NYC conference, a four-day event that featured 1,500 speakers from the crypto and NFT space and hosted 14,000 attendees | Getty Images, Noam Galai / Contributor June 20th, 2022 in New York City Times Square

I'm not sure what I expected, but the intensity of students' reactions surprised me. They had strong, emotional opinions about a technology I'd always considered administrative. NFTs address ownership and accounting, like most crypto/blockchain projects.

Art markets can be irrational, arbitrary, and subject to the same scams and schemes as any market. And maybe a few shenanigans that are unique to the art world.

The Fairness Question

Fairness, a deflating moral currency, was the general sentiment (the less of it in circulation, the more ardently we clamor for it.) These students, almost all of whom are artists, complained to the mismatch between the quality of the work in some notable NFT collections and the excessive amounts these items were fetching on the market. They can sketch a Bored Ape or Lazy Lion in their sleep. Why should they buy ramen with school loans while certain swindlers get rich?

Long Beach, California the sign for the Bored Ape Yacht Club NFT Themed Restaurant, Getty Images, Mario Tama / Staff April 9th 2022

I understand students. Art markets are unjust. They can be irrational, arbitrary, and governed by chance and circumstance, like any market. And art-world shenanigans.

Almost every mainstream critique leveled against NFTs applies just as easily to art markets

Over 50% of artworks in circulation are fake, say experts. Sincere art collectors and institutions are upset by the prevalence of fake goods on the market. Not everyone. Wealthy people and companies use art as investments. They can use cultural institutions like museums and galleries to increase the value of inherited art collections. People sometimes buy artworks and use family ties or connections to museums or other cultural taste-makers to hype the work in their collection, driving up the price and allowing them to sell for a profit. Money launderers can disguise capital flows by using market whims, hype, and fluctuating asset prices.

Almost every mainstream critique leveled against NFTs applies just as easily to art markets.

Art has always been this way. Edward Kienholz's 1989 print series satirized art markets. He stamped 395 identical pieces of paper from $1 to $395. Each piece was initially priced as indicated. Kienholz was joking about a strange feature of art markets: once the last print in a series sells for $395, all previous works are worth at least that much. The entire series is valued at its highest auction price. I don't know what a Kienholz print sells for today (inquire with the gallery), but it's more than $395.

I love Lee Lozano's 1969 "Real Money Piece." Lozano put cash in various denominations in a jar in her apartment and gave it to visitors. She wrote, "Offer guests coffee, diet pepsi, bourbon, half-and-half, ice water, grass, and money." "Offer real money as candy."

Lee Lozano kept track of who she gave money to, how much they took, if any, and how they reacted to the offer of free money without explanation. Diverse reactions. Some found it funny, others found it strange, and others didn't care. Lozano rarely says:

Apr 17 Keith Sonnier refused, later screws lid very tightly back on. Apr 27 Kaltenbach takes all the money out of the jar when I offer it, examines all the money & puts it all back in jar. Says he doesn’t need money now. Apr 28 David Parson refused, laughing. May 1 Warren C. Ingersoll refused. He got very upset about my “attitude towards money.” May 4 Keith Sonnier refused, but said he would take money if he needed it which he might in the near future. May 7 Dick Anderson barely glances at the money when I stick it under his nose and says “Oh no thanks, I intend to earn it on my own.” May 8 Billy Bryant Copley didn’t take any but then it was sort of spoiled because I had told him about this piece on the phone & he had time to think about it he said.

Smart Contracts (smart as in fair, not smart as in Blockchain)

Cornell University's Cheryl Finley has done a lot of research on secondary art markets. I first learned about her research when I met her at the University of Florida's Harn Museum, where she spoke about smart contracts (smart as in fair, not smart as in Blockchain) and new protocols that could help artists who are often left out of the economic benefits of their own work, including women and women of color.

Cheryl Finley on the right, with Hank Thomas and Dr. Deborah Willis attending the 2018 Aperture Gala at Ceder Lake on October 30th, 2018 in NYC, Photo by Patrick Mullan via Getty Images.

Her talk included findings from her ArtNet op-ed with Lauren van Haaften-Schick, Christian Reeder, and Amy Whitaker.

NFTs allow us to think about and hack on formal contractual relationships outside a system of laws that is currently not set up to service our community.

The ArtNet article The Recent Sale of Amy Sherald's ‘Welfare Queen' Symbolizes the Urgent Need for Resale Royalties and Economic Equity for Artists discussed Sherald's 2012 portrait of a regal woman in a purple dress wearing a sparkling crown and elegant set of pearls against a vibrant red background.

Amy Sherald sold "Welfare Queen" to Princeton professor Imani Perry. Sherald agreed to a payment plan to accommodate Perry's budget.

Amy Sherald rose to fame for her 2016 portrait of Michelle Obama and her full-length portrait of Breonna Taylor, one of the most famous works of the past decade.

As is common, Sherald's rising star drove up the price of her earlier works. Perry's "Welfare Queen" sold for $3.9 million in 2021.

Amy Sherald speaking about her work in front of her painting “Miss Everything (Unsuppressed Deliverance) | Getty Images
Raleigh News & Observer / Contributor May 2018

Imani Perry's early investment paid off big-time. Amy Sherald, whose work directly increased the painting's value and who was on an artist's shoestring budget when she agreed to sell "Welfare Queen" in 2012, did not see any of the 2021 auction money. Perry and the auction house got that money.

Sherald sold her Breonna Taylor portrait to the Smithsonian and Louisville's Speed Art Museum to fund a $1 million scholarship. This is a great example of what an artist can do for the community if they can amass wealth through their work.

NFTs haven't solved all of the art market's problems — fakes, money laundering, market manipulation — but they didn't create them. Blockchain and NFTs are credited with making these issues more transparent. More ideas emerge daily about what a smart contract should do for artists.

NFTs are a copyright solution. They allow us to hack formal contractual relationships outside a law system that doesn't serve our community.

Amy Sherald shows the good smart contracts can do (as in, well-considered, self-determined contracts, not necessarily blockchain contracts.) Giving back to our community, deciding where and how our work can be sold or displayed, and ensuring artists share in the equity of our work and the economy our labor creates.

Photo of Amy Sherald during New York Fashion Week attending Ulla Johnson at the Brooklyn Botanic Garden, Getty Images
Dominik Bindl / Stringer September 2021

Samer Buna

Samer Buna

2 years ago

The Errors I Committed As a Novice Programmer

Learn to identify them, make habits to avoid them

First, a clarification. This article is aimed to make new programmers aware of their mistakes, train them to detect them, and remind them to prevent them.

I learned from all these blunders. I'm glad I have coding habits to avoid them. Do too.

These mistakes are not ordered.

1) Writing code haphazardly

Writing good content is hard. It takes planning and investigation. Quality programs don't differ.

Think. Research. Plan. Write. Validate. Modify. Unfortunately, no good acronym exists. Create a habit of doing the proper quantity of these activities.

As a newbie programmer, my biggest error was writing code without thinking or researching. This works for small stand-alone apps but hurts larger ones.

Like saying anything you might regret, you should think before coding something you could regret. Coding expresses your thoughts.

When angry, count to 10 before you speak. If very angry, a hundred. — Thomas Jefferson.

My quote:

When reviewing code, count to 10 before you refactor a line. If the code does not have tests, a hundred. — Samer Buna

Programming is primarily about reviewing prior code, investigating what is needed and how it fits into the current system, and developing small, testable features. Only 10% of the process involves writing code.

Programming is not writing code. Programming need nurturing.

2) Making excessive plans prior to writing code

Yes. Planning before writing code is good, but too much of it is bad. Water poisons.

Avoid perfect plans. Programming does not have that. Find a good starting plan. Your plan will change, but it helped you structure your code for clarity. Overplanning wastes time.

Only planning small features. All-feature planning should be illegal! The Waterfall Approach is a step-by-step system. That strategy requires extensive planning. This is not planning. Most software projects fail with waterfall. Implementing anything sophisticated requires agile changes to reality.

Programming requires responsiveness. You'll add waterfall plan-unthinkable features. You will eliminate functionality for reasons you never considered in a waterfall plan. Fix bugs and adjust. Be agile.

Plan your future features, though. Do it cautiously since too little or too much planning can affect code quality, which you must risk.

3) Underestimating the Value of Good Code

Readability should be your code's exclusive goal. Unintelligible code stinks. Non-recyclable.

Never undervalue code quality. Coding communicates implementations. Coders must explicitly communicate solution implementations.

Programming quote I like:

Always code as if the guy who ends up maintaining your code will be a violent psychopath who knows where you live. — John Woods

John, great advice!

Small things matter. If your indentation and capitalization are inconsistent, you should lose your coding license.

Long queues are also simple. Readability decreases after 80 characters. To highlight an if-statement block, you might put a long condition on the same line. No. Just never exceed 80 characters.

Linting and formatting tools fix many basic issues like this. ESLint and Prettier work great together in JavaScript. Use them.

Code quality errors:

Multiple lines in a function or file. Break long code into manageable bits. My rule of thumb is that any function with more than 10 lines is excessively long.

Double-negatives. Don't.

Using double negatives is just very not not wrong

Short, generic, or type-based variable names. Name variables clearly.

There are only two hard things in Computer Science: cache invalidation and naming things. — Phil Karlton

Hard-coding primitive strings and numbers without descriptions. If your logic relies on a constant primitive string or numeric value, identify it.

Avoiding simple difficulties with sloppy shortcuts and workarounds. Avoid evasion. Take stock.

Considering lengthier code better. Shorter code is usually preferable. Only write lengthier versions if they improve code readability. For instance, don't utilize clever one-liners and nested ternary statements just to make the code shorter. In any application, removing unneeded code is better.

Measuring programming progress by lines of code is like measuring aircraft building progress by weight. — Bill Gates

Excessive conditional logic. Conditional logic is unnecessary for most tasks. Choose based on readability. Measure performance before optimizing. Avoid Yoda conditions and conditional assignments.

4) Selecting the First Approach

When I started programming, I would solve an issue and move on. I would apply my initial solution without considering its intricacies and probable shortcomings.

After questioning all the solutions, the best ones usually emerge. If you can't think of several answers, you don't grasp the problem.

Programmers do not solve problems. Find the easiest solution. The solution must work well and be easy to read, comprehend, and maintain.

There are two ways of constructing a software design. One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies. — C.A.R. Hoare

5) Not Giving Up

I generally stick with the original solution even though it may not be the best. The not-quitting mentality may explain this. This mindset is helpful for most things, but not programming. Program writers should fail early and often.

If you doubt a solution, toss it and rethink the situation. No matter how much you put in that solution. GIT lets you branch off and try various solutions. Use it.

Do not be attached to code because of how much effort you put into it. Bad code needs to be discarded.

6) Avoiding Google

I've wasted time solving problems when I should have researched them first.

Unless you're employing cutting-edge technology, someone else has probably solved your problem. Google It First.

Googling may discover that what you think is an issue isn't and that you should embrace it. Do not presume you know everything needed to choose a solution. Google surprises.

But Google carefully. Newbies also copy code without knowing it. Use only code you understand, even if it solves your problem.

Never assume you know how to code creatively.

The most dangerous thought that you can have as a creative person is to think that you know what you’re doing. — Bret Victor

7) Failing to Use Encapsulation

Not about object-oriented paradigm. Encapsulation is always useful. Unencapsulated systems are difficult to maintain.

An application should only handle a feature once. One object handles that. The application's other objects should only see what's essential. Reducing application dependencies is not about secrecy. Following these guidelines lets you safely update class, object, and function internals without breaking things.

Classify logic and state concepts. Class means blueprint template. Class or Function objects are possible. It could be a Module or Package.

Self-contained tasks need methods in a logic class. Methods should accomplish one thing well. Similar classes should share method names.

As a rookie programmer, I didn't always establish a new class for a conceptual unit or recognize self-contained units. Newbie code has a Util class full of unrelated code. Another symptom of novice code is when a small change cascades and requires numerous other adjustments.

Think before adding a method or new responsibilities to a method. Time's needed. Avoid skipping or refactoring. Start right.

High Cohesion and Low Coupling involves grouping relevant code in a class and reducing class dependencies.

8) Arranging for Uncertainty

Thinking beyond your solution is appealing. Every line of code will bring up what-ifs. This is excellent for edge cases but not for foreseeable needs.

Your what-ifs must fall into one of these two categories. Write only code you need today. Avoid future planning.

Writing a feature for future use is improper. No.

Write only the code you need today for your solution. Handle edge-cases, but don't introduce edge-features.

Growth for the sake of growth is the ideology of the cancer cell. — Edward Abbey

9) Making the incorrect data structure choices

Beginner programmers often overemphasize algorithms when preparing for interviews. Good algorithms should be identified and used when needed, but memorizing them won't make you a programming genius.

However, learning your language's data structures' strengths and shortcomings will make you a better developer.

The improper data structure shouts "newbie coding" here.

Let me give you a few instances of data structures without teaching you:

Managing records with arrays instead of maps (objects).

Most data structure mistakes include using lists instead of maps to manage records. Use a map to organize a list of records.

This list of records has an identifier to look up each entry. Lists for scalar values are OK and frequently superior, especially if the focus is pushing values to the list.

Arrays and objects are the most common JavaScript list and map structures, respectively (there is also a map structure in modern JavaScript).

Lists over maps for record management often fail. I recommend always using this point, even though it only applies to huge collections. This is crucial because maps are faster than lists in looking up records by identifier.

Stackless

Simple recursive functions are often tempting when writing recursive programming. In single-threaded settings, optimizing recursive code is difficult.

Recursive function returns determine code optimization. Optimizing a recursive function that returns two or more calls to itself is harder than optimizing a single call.

Beginners overlook the alternative to recursive functions. Use Stack. Push function calls to a stack and start popping them out to traverse them back.

10) Worsening the current code

Imagine this:

Add an item to that room. You might want to store that object anywhere as it's a mess. You can finish in seconds.

Not with messy code. Do not worsen! Keep the code cleaner than when you started.

Clean the room above to place the new object. If the item is clothing, clear a route to the closet. That's proper execution.

The following bad habits frequently make code worse:

  • code duplication You are merely duplicating code and creating more chaos if you copy/paste a code block and then alter just the line after that. This would be equivalent to adding another chair with a lower base rather than purchasing a new chair with a height-adjustable seat in the context of the aforementioned dirty room example. Always keep abstraction in mind, and use it when appropriate.

  • utilizing configuration files not at all. A configuration file should contain the value you need to utilize if it may differ in certain circumstances or at different times. A configuration file should contain a value if you need to use it across numerous lines of code. Every time you add a new value to the code, simply ask yourself: "Does this value belong in a configuration file?" The most likely response is "yes."

  • using temporary variables and pointless conditional statements. Every if-statement represents a logic branch that should at the very least be tested twice. When avoiding conditionals doesn't compromise readability, it should be done. The main issue with this is that branch logic is being used to extend an existing function rather than creating a new function. Are you altering the code at the appropriate level, or should you go think about the issue at a higher level every time you feel you need an if-statement or a new function variable?

This code illustrates superfluous if-statements:

function isOdd(number) {
  if (number % 2 === 1) {
    return true;
  } else {
    return false;
  }
}

Can you spot the biggest issue with the isOdd function above?

Unnecessary if-statement. Similar code:

function isOdd(number) {
  return (number % 2 === 1);
};

11) Making remarks on things that are obvious

I've learnt to avoid comments. Most code comments can be renamed.

instead of:

// This function sums only odd numbers in an array
const sum = (val) => {
  return val.reduce((a, b) => {
    if (b % 2 === 1) { // If the current number is odd
      a+=b;            // Add current number to accumulator
    }
    return a;          // The accumulator
  }, 0);
};

Commentless code looks like this:

const sumOddValues = (array) => {
  return array.reduce((accumulator, currentNumber) => {
    if (isOdd(currentNumber)) { 
      return accumulator + currentNumber;
    }
    return accumulator;
  }, 0);
};

Better function and argument names eliminate most comments. Remember that before commenting.

Sometimes you have to use comments to clarify the code. This is when your comments should answer WHY this code rather than WHAT it does.

Do not write a WHAT remark to clarify the code. Here are some unnecessary comments that clutter code:

// create a variable and initialize it to 0
let sum = 0;
// Loop over array
array.forEach(
  // For each number in the array
  (number) => {
    // Add the current number to the sum variable
    sum += number;
  }
);

Avoid that programmer. Reject that code. Remove such comments if necessary. Most importantly, teach programmers how awful these remarks are. Tell programmers who publish remarks like this that they may lose their jobs. That terrible.

12) Skipping tests

I'll simplify. If you develop code without tests because you think you're an excellent programmer, you're a rookie.

If you're not writing tests in code, you're probably testing manually. Every few lines of code in a web application will be refreshed and interacted with. Also. Manual code testing is fine. To learn how to automatically test your code, manually test it. After testing your application, return to your code editor and write code to automatically perform the same interaction the next time you add code.

Human. After each code update, you will forget to test all successful validations. Automate it!

Before writing code to fulfill validations, guess or design them. TDD is real. It improves your feature design thinking.

If you can use TDD, even partially, do so.

13) Making the assumption that if something is working, it must be right.

See this sumOddValues function. Is it flawed?

const sumOddValues = (array) => {
  return array.reduce((accumulator, currentNumber) => {
    if (currentNumber % 2 === 1) { 
      return accumulator + currentNumber;
    }
    return accumulator;
  });
};
 
 
console.assert(
  sumOddValues([1, 2, 3, 4, 5]) === 9
);

Verified. Good life. Correct?

Code above is incomplete. It handles some scenarios correctly, including the assumption used, but it has many other issues. I'll list some:

#1: No empty input handling. What happens when the function is called without arguments? That results in an error revealing the function's implementation:

TypeError: Cannot read property 'reduce' of undefined.

Two main factors indicate faulty code.

  • Your function's users shouldn't come across implementation-related information.

  • The user cannot benefit from the error. Simply said, they were unable to use your function. They would be aware that they misused the function if the error was more obvious about the usage issue. You might decide to make the function throw a custom exception, for instance:

TypeError: Cannot execute function for empty list.

Instead of returning an error, your method should disregard empty input and return a sum of 0. This case requires action.

Problem #2: No input validation. What happens if the function is invoked with a text, integer, or object instead of an array?

The function now throws:

sumOddValues(42);
TypeError: array.reduce is not a function

Unfortunately, array. cut's a function!

The function labels anything you call it with (42 in the example above) as array because we named the argument array. The error says 42.reduce is not a function.

See how that error confuses? An mistake like:

TypeError: 42 is not an array, dude.

Edge-cases are #1 and #2. These edge-cases are typical, but you should also consider less obvious ones. Negative numbers—what happens?

sumOddValues([1, 2, 3, 4, 5, -13]) // => still 9

-13's unusual. Is this the desired function behavior? Error? Should it sum negative numbers? Should it keep ignoring negative numbers? You may notice the function should have been titled sumPositiveOddNumbers.

This decision is simple. The more essential point is that if you don't write a test case to document your decision, future function maintainers won't know if you ignored negative values intentionally or accidentally.

It’s not a bug. It’s a feature. — Someone who forgot a test case

#3: Valid cases are not tested. Forget edge-cases, this function mishandles a straightforward case:

sumOddValues([2, 1, 3, 4, 5]) // => 11

The 2 above was wrongly included in sum.

The solution is simple: reduce accepts a second input to initialize the accumulator. Reduce will use the first value in the collection as the accumulator if that argument is not provided, like in the code above. The sum included the test case's first even value.

This test case should have been included in the tests along with many others, such as all-even numbers, a list with 0 in it, and an empty list.

Newbie code also has rudimentary tests that disregard edge-cases.

14) Adhering to Current Law

Unless you're a lone supercoder, you'll encounter stupid code. Beginners don't identify it and assume it's decent code because it works and has been in the codebase for a while.

Worse, if the terrible code uses bad practices, the newbie may be enticed to use them elsewhere in the codebase since they learnt them from good code.

A unique condition may have pushed the developer to write faulty code. This is a nice spot for a thorough note that informs newbies about that condition and why the code is written that way.

Beginners should presume that undocumented code they don't understand is bad. Ask. Enquire. Blame it!

If the code's author is dead or can't remember it, research and understand it. Only after understanding the code can you judge its quality. Before that, presume nothing.

15) Being fixated on best practices

Best practices damage. It suggests no further research. Best practice ever. No doubts!

No best practices. Today's programming language may have good practices.

Programming best practices are now considered bad practices.

Time will reveal better methods. Focus on your strengths, not best practices.

Do not do anything because you read a quote, saw someone else do it, or heard it is a recommended practice. This contains all my article advice! Ask questions, challenge theories, know your options, and make informed decisions.

16) Being preoccupied with performance

Premature optimization is the root of all evil (or at least most of it) in programming — Donald Knuth (1974)

I think Donald Knuth's advice is still relevant today, even though programming has changed.

Do not optimize code if you cannot measure the suspected performance problem.

Optimizing before code execution is likely premature. You may possibly be wasting time optimizing.

There are obvious optimizations to consider when writing new code. You must not flood the event loop or block the call stack in Node.js. Remember this early optimization. Will this code block the call stack?

Avoid non-obvious code optimization without measurements. If done, your performance boost may cause new issues.

Stop optimizing unmeasured performance issues.

17) Missing the End-User Experience as a Goal

How can an app add a feature easily? Look at it from your perspective or in the existing User Interface. Right? Add it to the form if the feature captures user input. Add it to your nested menu of links if it adds a link to a page.

Avoid that developer. Be a professional who empathizes with customers. They imagine this feature's consumers' needs and behavior. They focus on making the feature easy to find and use, not just adding it to the software.

18) Choosing the incorrect tool for the task

Every programmer has their preferred tools. Most tools are good for one thing and bad for others.

The worst tool for screwing in a screw is a hammer. Do not use your favorite hammer on a screw. Don't use Amazon's most popular hammer on a screw.

A true beginner relies on tool popularity rather than problem fit.

You may not know the best tools for a project. You may know the best tool. However, it wouldn't rank high. You must learn your tools and be open to new ones.

Some coders shun new tools. They like their tools and don't want to learn new ones. I can relate, but it's wrong.

You can build a house slowly with basic tools or rapidly with superior tools. You must learn and use new tools.

19) Failing to recognize that data issues are caused by code issues

Programs commonly manage data. The software will add, delete, and change records.

Even the simplest programming errors can make data unpredictable. Especially if the same defective application validates all data.

Code-data relationships may be confusing for beginners. They may employ broken code in production since feature X is not critical. Buggy coding may cause hidden data integrity issues.

Worse, deploying code that corrected flaws without fixing minor data problems caused by these defects will only collect more data problems that take the situation into the unrecoverable-level category.

How do you avoid these issues? Simply employ numerous data integrity validation levels. Use several interfaces. Front-end, back-end, network, and database validations. If not, apply database constraints.

Use all database constraints when adding columns and tables:

  • If a column has a NOT NULL constraint, null values will be rejected for that column. If your application expects that field has a value, your database should designate its source as not null.

  • If a column has a UNIQUE constraint, the entire table cannot include duplicate values for that column. This is ideal for a username or email field on a Users table, for instance.

  • For the data to be accepted, a CHECK constraint, or custom expression, must evaluate to true. For instance, you can apply a check constraint to ensure that the values of a normal % column must fall within the range of 0 and 100.

  • With a PRIMARY KEY constraint, the values of the columns must be both distinct and not null. This one is presumably what you're utilizing. To distinguish the records in each table, the database needs have a primary key.

  • A FOREIGN KEY constraint requires that the values in one database column, typically a primary key, match those in another table column.

Transaction apathy is another data integrity issue for newbies. If numerous actions affect the same data source and depend on each other, they must be wrapped in a transaction that can be rolled back if one fails.

20) Reinventing the Wheel

Tricky. Some programming wheels need reinvention. Programming is undefined. New requirements and changes happen faster than any team can handle.

Instead of modifying the wheel we all adore, maybe we should rethink it if you need a wheel that spins at varied speeds depending on the time of day. If you don't require a non-standard wheel, don't reinvent it. Use the darn wheel.

Wheel brands can be hard to choose from. Research and test before buying! Most software wheels are free and transparent. Internal design quality lets you evaluate coding wheels. Try open-source wheels. Debug and fix open-source software simply. They're easily replaceable. In-house support is also easy.

If you need a wheel, don't buy a new automobile and put your maintained car on top. Do not include a library to use a few functions. Lodash in JavaScript is the finest example. Import shuffle to shuffle an array. Don't import lodash.

21) Adopting the incorrect perspective on code reviews

Beginners often see code reviews as criticism. Dislike them. Not appreciated. Even fear them.

Incorrect. If so, modify your mindset immediately. Learn from every code review. Salute them. Observe. Most crucial, thank reviewers who teach you.

Always learning code. Accept it. Most code reviews teach something new. Use these for learning.

You may need to correct the reviewer. If your code didn't make that evident, it may need to be changed. If you must teach your reviewer, remember that teaching is one of the most enjoyable things a programmer can do.

22) Not Using Source Control

Newbies often underestimate Git's capabilities.

Source control is more than sharing your modifications. It's much bigger. Clear history is source control. The history of coding will assist address complex problems. Commit messages matter. They are another way to communicate your implementations, and utilizing them with modest commits helps future maintainers understand how the code got where it is.

Commit early and often with present-tense verbs. Summarize your messages but be detailed. If you need more than a few lines, your commit is too long. Rebase!

Avoid needless commit messages. Commit summaries should not list new, changed, or deleted files. Git commands can display that list from the commit object. The summary message would be noise. I think a big commit has many summaries per file altered.

Source control involves discoverability. You can discover the commit that introduced a function and see its context if you doubt its need or design. Commits can even pinpoint which code caused a bug. Git has a binary search within commits (bisect) to find the bug-causing commit.

Source control can be used before commits to great effect. Staging changes, patching selectively, resetting, stashing, editing, applying, diffing, reversing, and others enrich your coding flow. Know, use, and enjoy them.

I consider a Git rookie someone who knows less functionalities.

23) Excessive Use of Shared State

Again, this is not about functional programming vs. other paradigms. That's another article.

Shared state is problematic and should be avoided if feasible. If not, use shared state as little as possible.

As a new programmer, I didn't know that all variables represent shared states. All variables in the same scope can change its data. Global scope reduces shared state span. Keep new states in limited scopes and avoid upward leakage.

When numerous resources modify common state in the same event loop tick, the situation becomes severe (in event-loop-based environments). Races happen.

This shared state race condition problem may encourage a rookie to utilize a timer, especially if they have a data lock issue. Red flag. No. Never accept it.

24) Adopting the Wrong Mentality Toward Errors

Errors are good. Progress. They indicate a simple way to improve.

Expert programmers enjoy errors. Newbies detest them.

If these lovely red error warnings irritate you, modify your mindset. Consider them helpers. Handle them. Use them to advance.

Some errors need exceptions. Plan for user-defined exceptions. Ignore some mistakes. Crash and exit the app.

25) Ignoring rest periods

Humans require mental breaks. Take breaks. In the zone, you'll forget breaks. Another symptom of beginners. No compromises. Make breaks mandatory in your process. Take frequent pauses. Take a little walk to plan your next move. Reread the code.

This has been a long post. You deserve a break.

Daniel Vassallo

Daniel Vassallo

3 years ago

Why I quit a $500K job at Amazon to work for myself

I quit my 8-year Amazon job last week. I wasn't motivated to do another year despite promotions, pay, recognition, and praise.

In AWS, I built developer tools. I could have worked in that field forever.

I became an Amazon developer. Within 3.5 years, I was promoted twice to senior engineer and would have been promoted to principal engineer if I stayed. The company said I had great potential.

Over time, I became a reputed expert and leader within the company. I was respected.

First year I made $75K, last year $511K. If I stayed another two years, I could have made $1M.

Despite Amazon's reputation, my work–life balance was good. I no longer needed to prove myself and could do everything in 40 hours a week. My team worked from home once a week, and I rarely opened my laptop nights or weekends.

My coworkers were great. I had three generous, empathetic managers. I’m very grateful to everyone I worked with.

Everything was going well and getting better. My motivation to go to work each morning was declining despite my career and income growth.

Another promotion, pay raise, or big project wouldn't have boosted my motivation. Motivation was also waning. It was my freedom.

Demotivation

My motivation was high in the beginning. I worked with someone on an internal tool with little scrutiny. I had more freedom to choose how and what to work on than in recent years. Me and another person improved it, talked to users, released updates, and tested it. Whatever we wanted, we did. We did our best and were mostly self-directed.

In recent years, things have changed. My department's most important project had many stakeholders and complex goals. What I could do depended on my ability to convince others it was the best way to achieve our goals.

Amazon was always someone else's terms. The terms started out simple (keep fixing it), but became more complex over time (maximize all goals; satisfy all stakeholders). Working in a large organization imposed restrictions on how to do the work, what to do, what goals to set, and what business to pursue. This situation forced me to do things I didn't want to do.

Finding New Motivation

What would I do forever? Not something I did until I reached a milestone (an exit), but something I'd do until I'm 80. What could I do for the next 45 years that would make me excited to wake up and pay my bills? Is that too unambitious? Nope. Because I'm motivated by two things.

One is an external carrot or stick. I'm not forced to file my taxes every April, but I do because I don't want to go to jail. Or I may not like something but do it anyway because I need to pay the bills or want a nice car. Extrinsic motivation

One is internal. When there's no carrot or stick, this motivates me. This fuels hobbies. I wanted a job that was intrinsically motivated.

Is this too low-key? Extrinsic motivation isn't sustainable. Getting promoted felt good for a week, then it was over. When I hit $100K, I admired my W2 for a few days, but then it wore off. Same thing happened at $200K, $300K, $400K, and $500K. Earning $1M or $10M wouldn't change anything. I feel the same about every material reward or possession. Getting them feels good at first, but quickly fades.

Things I've done since I was a kid, when no one forced me to, don't wear off. Coding, selling my creations, charting my own path, and being honest. Why not always use my strengths and motivation? I'm lucky to live in a time when I can work independently in my field without large investments. So that’s what I’m doing.

What’s Next?

I'm going all-in on independence and will make a living from scratch. I won't do only what I like, but on my terms. My goal is to cover my family's expenses before my savings run out while doing something I enjoy. What more could I want from my work?

You can now follow me on Twitter as I continue to document my journey.


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