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.
This post is a summary. Read full article here
More on Personal Growth
Glorin Santhosh
3 years ago
In his final days, Steve Jobs sent an email to himself. What It Said Was This
An email capturing Steve Jobs's philosophy.
Steve Jobs may have been the most inspired and driven entrepreneur.
He worked on projects because he wanted to leave a legacy.
Steve Jobs' final email to himself encapsulated his philosophy.
After his death from pancreatic cancer in October 2011, Laurene Powell Jobs released the email. He was 56.
Read: Steve Jobs by Walter Isaacson (#BestSeller)
The Email:
September 2010 Steve Jobs email:
“I grow little of the food I eat, and of the little I do grow, I do not breed or perfect the seeds.” “I do not make my own clothing. I speak a language I did not invent or refine,” he continued. “I did not discover the mathematics I use… I am moved by music I did not create myself.”
Jobs ended his email by reflecting on how others created everything he uses.
He wrote:
“When I needed medical attention, I was helpless to help myself survive.”
The Apple co-founder concluded by praising humanity.
“I did not invent the transistor, the microprocessor, object-oriented programming, or most of the technology I work with. I love and admire my species, living and dead, and am totally dependent on them for my life and well-being,” he concluded.
The email was made public as a part of the Steve Jobs Archive, a website that was launched in tribute to his legacy.
Steve Jobs' widow founded the internet archive. Apple CEO Tim Cook and former design leader Jony Ive were prominent guests.
Steve Jobs has always inspired because he shows how even the best can be improved.
High expectations were always there, and they were consistently met.
We miss him because he was one of the few with lifelong enthusiasm and persona.
Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
Non-technical talents can benefit data scientists in addition to statistics and programming.
As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.
Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.
Ready? Let’s dive in.
Best books for data scientists
1. The Black Swan
Author: Nassim Taleb
First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.
Three characteristics define a black swan event:
It is erratic.
It has a significant impact.
Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.
People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.
Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.
Try multiple tactics and models because you may find the answer.
2. High Output Management
Author: Andrew Grove
Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.
That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.
Five lessons:
Every action is a procedure.
Meetings are a medium of work
Manage short-term goals in accordance with long-term strategies.
Mission-oriented teams accelerate while functional teams increase leverage.
Utilize performance evaluations to enhance output.
So — if the above captures your imagination, it’s well worth getting stuck in.
3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
Author: Ben Horowitz
Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.
Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.
It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.
Find suggestions on:
create software
Run a business.
Promote a product
Obtain resources
Smart investment
oversee daily operations
This book will help you cope with tough times.
4. Obviously Awesome: How to Nail Product Positioning
Author: April Dunford
Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.
How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.
You'll learn:
Select the ideal market for your products.
Connect an audience to the value of your goods right away.
Take use of three positioning philosophies.
Utilize market trends to aid purchasers
5. The Mom test
Author: Rob Fitzpatrick
The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.
Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.
6. Introduction to Machine Learning with Python: A Guide for Data Scientists
Authors: Andreas C. Müller, Sarah Guido
Now, technical documents.
This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.
Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.
If you know machine learning or artificial neural networks, skip this.
7. Python Data Science Handbook: Essential Tools for Working with Data
Author: Jake VanderPlas
Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.
Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.
The only thing missing is a way to apply your learnings.
8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Author: Wes McKinney
The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.
The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.
9. Data Science from Scratch
Author: Joel Grus
Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.
The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.
Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.
10. Machine Learning Yearning
Author: Andrew Ng
Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.
The book delivers knowledge and teaches how to apply it, so you'll know how to:
Determine the optimal course of action for your ML project.
Create software that is more effective than people.
Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.
Identifying machine learning system flaws
Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.
11. Deep Learning with PyTorch Step-by-Step
Author: Daniel Voigt Godoy
The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.
It comprises four parts:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)
We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.
Is every data scientist a humanist?
Even as a technological professional, you can't escape human interaction, especially with clients.
We hope these books will help you develop interpersonal skills.
Matthew Royse
3 years ago
7 ways to improve public speaking
How to overcome public speaking fear and give a killer presentation
"Public speaking is people's biggest fear, according to studies. Death's second. The average person is better off in the casket than delivering the eulogy." — American comedian, actor, writer, and producer Jerry Seinfeld
People fear public speaking, according to research. Public speaking can be intimidating.
Most professions require public speaking, whether to 5, 50, 500, or 5,000 people. Your career will require many presentations. In a small meeting, company update, or industry conference.
You can improve your public speaking skills. You can reduce your anxiety, improve your performance, and feel more comfortable speaking in public.
“If I returned to college, I'd focus on writing and public speaking. Effective communication is everything.” — 38th president Gerald R. Ford
You can deliver a great presentation despite your fear of public speaking. There are ways to stay calm while speaking and become a more effective public speaker.
Seven tips to improve your public speaking today. Let's help you overcome your fear (no pun intended).
Know your audience.
"You're not being judged; the audience is." — Entrepreneur, author, and speaker Seth Godin
Understand your audience before speaking publicly. Before preparing a presentation, know your audience. Learn what they care about and find useful.
Your presentation may depend on where you're speaking. A classroom is different from a company meeting.
Determine your audience before developing your main messages. Learn everything about them. Knowing your audience helps you choose the right words, information (thought leadership vs. technical), and motivational message.
2. Be Observant
Observe others' speeches to improve your own. Watching free TED Talks on education, business, science, technology, and creativity can teach you a lot about public speaking.
What worked and what didn't?
What would you change?
Their strengths
How interesting or dull was the topic?
Note their techniques to learn more. Studying the best public speakers will amaze you.
Learn how their stage presence helped them communicate and captivated their audience. Please note their pauses, humor, and pacing.
3. Practice
"A speaker should prepare based on what he wants to learn, not say." — Author, speaker, and pastor Tod Stocker
Practice makes perfect when it comes to public speaking. By repeating your presentation, you can find your comfort zone.
When you've practiced your presentation many times, you'll feel natural and confident giving it. Preparation helps overcome fear and anxiety. Review notes and important messages.
When you know the material well, you can explain it better. Your presentation preparation starts before you go on stage.
Keep a notebook or journal of ideas, quotes, and examples. More content means better audience-targeting.
4. Self-record
Videotape your speeches. Check yourself. Body language, hands, pacing, and vocabulary should be reviewed.
Best public speakers evaluate their performance to improve.
Write down what you did best, what you could improve and what you should stop doing after watching a recording of yourself. Seeing yourself can be unsettling. This is how you improve.
5. Remove text from slides
"Humans can't read and comprehend screen text while listening to a speaker. Therefore, lots of text and long, complete sentences are bad, bad, bad.” —Communications expert Garr Reynolds
Presentation slides shouldn't have too much text. 100-slide presentations bore the audience. Your slides should preview what you'll say to the audience.
Use slides to emphasize your main point visually.
If you add text, use at least 40-point font. Your slides shouldn't require squinting to read. You want people to watch you, not your slides.
6. Body language
"Body language is powerful." We had body language before speech, and 80% of a conversation is read through the body, not the words." — Dancer, writer, and broadcaster Deborah Bull
Nonverbal communication dominates. Our bodies speak louder than words. Don't fidget, rock, lean, or pace.
Relax your body to communicate clearly and without distraction through nonverbal cues. Public speaking anxiety can cause tense body language.
Maintain posture and eye contact. Don’t put your hand in your pockets, cross your arms, or stare at your notes. Make purposeful hand gestures that match what you're saying.
7. Beginning/ending Strong
Beginning and end are memorable. Your presentation must start strong and end strongly. To engage your audience, don't sound robotic.
Begin with a story, stat, or quote. Conclude with a summary of key points. Focus on how you will start and end your speech.
You should memorize your presentation's opening and closing. Memorize something naturally. Excellent presentations start and end strong because people won't remember the middle.
Bringing It All Together
Seven simple yet powerful ways to improve public speaking. Know your audience, study others, prepare and rehearse, record yourself, remove as much text as possible from slides, and start and end strong.
Follow these tips to improve your speaking and audience communication. Prepare, practice, and learn from great speakers to reduce your fear of public speaking.
"Speaking to one person or a thousand is public speaking." — Vocal coach Roger Love
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Sam Hickmann
3 years ago
Token taxonomy: Utility vs Security vs NFT
Let's examine the differences between the three main token types and their functions.
As Ethereum grew, the term "token" became a catch-all term for all assets built on the Ethereum blockchain. However, different tokens were grouped based on their applications and features, causing some confusion. Let's examine the modification of three main token types: security, utility, and non-fungible.
Utility tokens
They provide a specific utility benefit (or a number of such). A utility token is similar to a casino chip, a table game ticket, or a voucher. Depending on the terms of issuing, they can be earned and used in various ways. A utility token is a type of token that represents a tool or mechanism required to use the application in question. Like a service, a utility token's price is determined by supply and demand. Tokens can also be used as a bonus or reward mechanism in decentralized systems: for example, if you like someone's work, give them an upvote and they get a certain number of tokens. This is a way for authors or creators to earn money indirectly.
The most common way to use a utility token is to pay with them instead of cash for discounted goods or services.
Utility tokens are the most widely used by blockchain companies. Most cryptocurrency exchanges accept fees in native utility tokens.
Utility tokens can also be used as a reward. Companies tokenize their loyalty programs so that points can be bought and sold on blockchain exchanges. These tokens are widely used in decentralized companies as a bonus system. You can use utility tokens to reward creators for their contributions to a platform, for example. It also allows members to exchange tokens for specific bonuses and rewards on your site.
Unlike security tokens, which are subject to legal restrictions, utility tokens can be freely traded.
Security tokens
Security tokens are essentially traditional securities like shares, bonds, and investment fund units in a crypto token form.
The key distinction is that security tokens are typically issued by private firms (rather than public companies) that are not listed on stock exchanges and in which you can not invest right now. Banks and large venture funds used to be the only sources of funding. A person could only invest in private firms if they had millions of dollars in their bank account. Privately issued security tokens outperform traditional public stocks in terms of yield. Private markets grew 50% faster than public markets over the last decade, according to McKinsey Private Equity Research.
A security token is a crypto token whose value is derived from an external asset or company. So it is governed as security (read about the Howey test further in this article). That is, an ownership token derives its value from the company's valuation, assets on the balance sheet, or dividends paid to token holders.
Why are Security Tokens Important?
Cryptocurrency is a lucrative investment. Choosing from thousands of crypto assets can mean the difference between millionaire and bankrupt. Without security tokens, crypto investing becomes riskier and generating long-term profits becomes difficult. These tokens have lower risk than other cryptocurrencies because they are backed by real assets or business cash flows. So having them helps to diversify a portfolio and preserve the return on investment in riskier assets.
Security tokens open up new funding avenues for businesses. As a result, investors can invest in high-profit businesses that are not listed on the stock exchange.
The distinction between utility and security tokens isn't as clear as it seems. However, this increases the risk for token issuers, especially in the USA. The Howey test is the main pillar regulating judicial precedent in this area.
What is a Howey Test?
An "investment contract" is determined by the Howey Test, a lawsuit settled by the US Supreme Court. If it does, it's a security and must be disclosed and registered under the Securities Act of 1933 and the Securities Exchange Act of 1934.
If the SEC decides that a cryptocurrency token is a security, a slew of issues arise. In practice, this ensures that the SEC will decide when a token can be offered to US investors and if the project is required to file a registration statement with the SEC.
Due to the Howey test's extensive wording, most utility tokens will be classified as securities, even if not intended to be. Because of these restrictions, most ICOs are not available to US investors. When asked about ICOs in 2018, then-SEC Chairman Jay Clayton said they were securities. The given statement adds to the risk. If a company issues utility tokens without registering them as securities, the regulator may impose huge fines or even criminal charges.
What other documents regulate tokens?
Securities Act (1993) or Securities Exchange Act (1934) in the USA; MiFID directive and Prospectus Regulation in the EU. These laws require registering the placement of security tokens, limiting their transfer, but protecting investors.
Utility tokens have much less regulation. The Howey test determines whether a given utility token is a security. Tokens recognized as securities are now regulated as such. Having a legal opinion that your token isn't makes the implementation process much easier. Most countries don't have strict regulations regarding utility tokens except KYC (Know Your Client) and AML (Anti Money-Laundering).
As cryptocurrency and blockchain technologies evolve, more countries create UT regulations. If your company is based in the US, be aware of the Howey test and the Bank Secrecy Act. It classifies UTs and their issuance as money transmission services in most states, necessitating a license and strict regulations. Due to high regulatory demands, UT issuers try to avoid the United States as a whole. A new law separating utility tokens from bank secrecy act will be introduced in the near future, giving hope to American issuers.
The rest of the world has much simpler rules requiring issuers to create basic investor disclosures. For example, the latest European legislation (MiCA) allows businesses to issue utility tokens without regulator approval. They must also prepare a paper with all the necessary information for the investors.
A payment token is a utility token that is used to make a payment. They may be subject to electronic money laws.
Because non-fungible tokens are a new instrument, there is no regulating paper yet. However, if the NFT is fractionalized, the smaller tokens acquired may be seen as securities.
NFT Tokens
Collectible tokens are also known as non-fungible tokens. Their distinctive feature is that they denote unique items such as artwork, merch, or ranks. Unlike utility tokens, which are fungible, meaning that two of the same tokens are identical, NFTs represent a unit of possession that is strictly one of a kind. In a way, NFTs are like baseball cards, each one unique and valuable.
As for today, the most recognizable NFT function is to preserve the fact of possession. Owning an NFT with a particular gif, meme, or sketch does not transfer the intellectual right to the possessor, but is analogous to owning an original painting signed by the author.
Collectible tokens can also be used as digital souvenirs, so to say. Businesses can improve their brand image by issuing their own branded NFTs, which represent ranks or achievements within the corporate ecosystem. Gamifying business ecosystems would allow people to connect with a brand and feel part of a community.
Which type of tokens is right for you as a business to raise capital?
For most businesses, it's best to raise capital with security tokens by selling existing shares to global investors. Utility tokens aren't meant to increase in value over time, so leave them for gamification and community engagement. In a blockchain-based business, however, a utility token is often the lifeblood of the operation, and its appreciation potential is directly linked to the company's growth. You can issue multiple tokens at once, rather than just one type. It exposes you to various investors and maximizes the use of digital assets.
Which tokens should I buy?
There are no universally best tokens. Their volatility, industry, and risk-reward profile vary. This means evaluating tokens in relation to your overall portfolio and personal preferences: what industries do you understand best, what excites you, how do you approach taxes, and what is your planning horizon? To build a balanced portfolio, you need to know these factors.
Conclusion
The three most common types of tokens today are security, utility, and NFT. Security tokens represent stocks, mutual funds, and bonds. Utility tokens can be perceived as an inside-product "currency" or "ignition key" that grants you access to goods and services or empowers with other perks. NFTs are unique collectible units that identify you as the owner of something.
Yusuf Ibrahim
4 years ago
How to sell 10,000 NFTs on OpenSea for FREE (Puppeteer/NodeJS)
So you've finished your NFT collection and are ready to sell it. Except you can't figure out how to mint them! Not sure about smart contracts or want to avoid rising gas prices. You've tried and failed with apps like Mini mouse macro, and you're not familiar with Selenium/Python. Worry no more, NodeJS and Puppeteer have arrived!
Learn how to automatically post and sell all 1000 of my AI-generated word NFTs (Nakahana) on OpenSea for FREE!
My NFT project — Nakahana |
NOTE: Only NFTs on the Polygon blockchain can be sold for free; Ethereum requires an initiation charge. NFTs can still be bought with (wrapped) ETH.
If you want to go right into the code, here's the GitHub link: https://github.com/Yusu-f/nftuploader
Let's start with the knowledge and tools you'll need.
What you should know
You must be able to write and run simple NodeJS programs. You must also know how to utilize a Metamask wallet.
Tools needed
- NodeJS. You'll need NodeJs to run the script and NPM to install the dependencies.
- Puppeteer – Use Puppeteer to automate your browser and go to sleep while your computer works.
- Metamask – Create a crypto wallet and sign transactions using Metamask (free). You may learn how to utilize Metamask here.
- Chrome – Puppeteer supports Chrome.
Let's get started now!
Starting Out
Clone Github Repo to your local machine. Make sure that NodeJS, Chrome, and Metamask are all installed and working. Navigate to the project folder and execute npm install. This installs all requirements.
Replace the “extension path” variable with the Metamask chrome extension path. Read this tutorial to find the path.
Substitute an array containing your NFT names and metadata for the “arr” variable and the “collection_name” variable with your collection’s name.
Run the script.
After that, run node nftuploader.js.
Open a new chrome instance (not chromium) and Metamask in it. Import your Opensea wallet using your Secret Recovery Phrase or create a new one and link it. The script will be unable to continue after this but don’t worry, it’s all part of the plan.
Next steps
Open your terminal again and copy the route that starts with “ws”, e.g. “ws:/localhost:53634/devtools/browser/c07cb303-c84d-430d-af06-dd599cf2a94f”. Replace the path in the connect function of the nftuploader.js script.
const browser = await puppeteer.connect({ browserWSEndpoint: "ws://localhost:58533/devtools/browser/d09307b4-7a75-40f6-8dff-07a71bfff9b3", defaultViewport: null });
Rerun node nftuploader.js. A second tab should open in THE SAME chrome instance, navigating to your Opensea collection. Your NFTs should now start uploading one after the other! If any errors occur, the NFTs and errors are logged in an errors.log file.
Error Handling
The errors.log file should show the name of the NFTs and the error type. The script has been changed to allow you to simply check if an NFT has already been posted. Simply set the “searchBeforeUpload” setting to true.
We're done!
If you liked it, you can buy one of my NFTs! If you have any concerns or would need a feature added, please let me know.
Thank you to everyone who has read and liked. I never expected it to be so popular.
Caleb Naysmith
3 years ago
Ads Coming to Medium?
Could this happen?
Medium isn't like other social media giants. It wasn't a dot-com startup that became a multi-trillion-dollar social media firm. It launched in 2012 but didn't gain popularity until later. Now, it's one of the largest sites by web traffic, but it's still little compared to most. Most of Medium's traffic is external, but they don't run advertisements, so it's all about memberships.
Medium isn't profitable, but they don't disclose how terrible the problem is. Most of the $163 million they raised has been spent or used for acquisitions. If the money turns off, Medium can't stop paying its writers since the site dies. Writers must be paid, but they can't substantially slash payment without hurting the platform. The existing model needs scale to be viable and has a low ceiling. Facebook and other free social media platforms are struggling to retain users. Here, you must pay to appreciate it, and it's bad for writers AND readers. If I had the same Medium stats on YouTube, I'd make thousands of dollars a month.
Then what? Medium has tried to monetize by offering writers a cut of new members, but that's unsustainable. People-based growth is limited. Imagine recruiting non-Facebook users and getting them to pay to join. Some may, but I'd rather write.
Alternatives:
Donation buttons
Tiered subscriptions ($5, $10, $25, etc.)
Expanding content
and these may be short-term fixes, but they're not as profitable as allowing ads. Advertisements can pay several dollars per click and cents every view. If you get 40,000 views a month like me, that's several thousand instead of a few hundred. Also, Medium would have enough money to split ad revenue with writers, who would make more. I'm among the top 6% of Medium writers. Only 6% of Medium writers make more than $100, and I made $500 with 35,000 views last month. Compared to YouTube, the top 1% of Medium authors make a lot. Mr. Beast and PewDiePie make MILLIONS a month, yet top Medium writers make tens of thousands. Sure, paying 3 or 4 people a few grand, or perhaps tens of thousands, will keep them around. What if great authors leveraged their following to go huge on YouTube and abandoned Medium? If people use Medium to get successful on other platforms, Medium will be continuously cycling through authors and paying them to stay.
Ads might make writing on Medium more profitable than making videos on YouTube because they could preserve the present freemium model and pay users based on internal views. The $5 might be ad-free.
Consider: Would you accept Medium ads? A $5 ad-free version + pay-as-you-go, etc. What are your thoughts on this?
Original post available here