More on Productivity

Ethan Siegel
2 years ago
How you view the year will change after using this one-page calendar.
No other calendar is simpler, smaller, and reusable year after year. It works and is used here.
Most of us discard and replace our calendars annually. Each month, we move our calendar ahead another page, thus if we need to know which day of the week corresponds to a given day/month combination, we have to calculate it or flip forward/backward to the corresponding month. Questions like:
What day does this year's American Thanksgiving fall on?
Which months contain a Friday the thirteenth?
When is July 4th? What day of the week?
Alternatively, what day of the week is Christmas?
They're hard to figure out until you switch to the right month or look up all the months.
However, mathematically, the answers to these questions or any question that requires matching the day of the week with the day/month combination in a year are predictable, basic, and easy to work out. If you use this one-page calendar instead of a 12-month calendar, it lasts the whole year and is easy to alter for future years. Let me explain.
The 2023 one-page calendar is above. The days of the month are on the lower left, which works for all months if you know that:
There are 31 days in January, March, May, July, August, October, and December.
All of the months of April, June, September, and November have 30 days.
And depending on the year, February has either 28 days (in non-leap years) or 29 days (in leap years).
If you know this, this calendar makes it easy to match the day/month of the year to the weekday.
Here are some instances. American Thanksgiving is always on the fourth Thursday of November. You'll always know the month and day of the week, but the date—the day in November—changes each year.
On any other calendar, you'd have to flip to November to see when the fourth Thursday is. This one-page calendar only requires:
pick the month of November in the top-right corner to begin.
drag your finger down until Thursday appears,
then turn left and follow the monthly calendar until you reach the fourth Thursday.
It's obvious: 2023 is the 23rd American Thanksgiving. For every month and day-of-the-week combination, start at the month, drag your finger down to the desired day, and then move to the left to see which dates match.
What if you knew the day of the week and the date of the month, but not the month(s)?
A different method using the same one-page calendar gives the answer. Which months have Friday the 13th this year? Just:
begin on the 13th of the month, the day you know you desire,
then swipe right with your finger till Friday appears.
and then work your way up until you can determine which months the specific Friday the 13th falls under.
One Friday the 13th occurred in January 2023, and another will occur in October.
The most typical reason to consult a calendar is when you know the month/day combination but not the day of the week.
Compared to single-month calendars, the one-page calendar excels here. Take July 4th, for instance. Find the weekday here:
beginning on the left on the fourth of the month, as you are aware,
also begin with July, the month of the year you are most familiar with, at the upper right,
you should move your two fingers in the opposite directions till they meet: on a Tuesday in 2023.
That's how you find your selected day/month combination's weekday.
Another example: Christmas. Christmas Day is always December 25th, however unless your conventional calendar is open to December of your particular year, a question like "what day of the week is Christmas?" difficult to answer.
Unlike the one-page calendar!
Remember the left-hand day of the month. Top-right, you see the month. Put two fingers, one from each hand, on the date (25th) and the month (December). Slide the day hand to the right and the month hand downwards until they touch.
They meet on Monday—December 25, 2023.
For 2023, that's fine, but what happens in 2024? Even worse, what if we want to know the day-of-the-week/day/month combo many years from now?
I think the one-page calendar shines here.
Except for the blue months in the upper-right corner of the one-page calendar, everything is the same year after year. The months also change in a consistent fashion.
Each non-leap year has 365 days—one more than a full 52 weeks (which is 364). Since January 1, 2023 began on a Sunday and 2023 has 365 days, we immediately know that December 31, 2023 will conclude on a Sunday (which you can confirm using the one-page calendar) and that January 1, 2024 will begin on a Monday. Then, reorder the months for 2024, taking in mind that February will have 29 days in a leap year.
Please note the differences between 2023 and 2024 month placement. In 2023:
October and January began on the same day of the week.
On the following Monday of the week, May began.
August started on the next day,
then the next weekday marked the start of February, March, and November, respectively.
Unlike June, which starts the following weekday,
While September and December start on the following day of the week,
Lastly, April and July start one extra day later.
Since 2024 is a leap year, February has 29 days, disrupting the rhythm. Month placements change to:
The first day of the week in January, April, and July is the same.
October will begin the following day.
Possibly starting the next weekday,
February and August start on the next weekday,
beginning on the following day of the week between March and November,
beginning the following weekday in June,
and commencing one more day of the week after that, September and December.
Due to the 366-day leap year, 2025 will start two days later than 2024 on January 1st.
Now, looking at the 2025 calendar, you can see that the 2023 pattern of which months start on which days is repeated! The sole variation is a shift of three days-of-the-week ahead because 2023 had one more day (365) than 52 full weeks (364), and 2024 had two more days (366). Again,
On Wednesday this time, January and October begin on the same day of the week.
Although May begins on Thursday,
August begins this Friday.
March, November, and February all begin on a Saturday.
Beginning on a Sunday in June
Beginning on Monday are September and December,
and on Tuesday, April and July begin.
In 2026 and 2027, the year will commence on a Thursday and a Friday, respectively.
We must return to our leap year monthly arrangement in 2028. Yes, January 1, 2028 begins on a Saturday, but February, which begins on a Tuesday three days before January, will have 29 days. Thus:
Start dates for January, April, and July are all Saturdays.
Given that October began on Sunday,
Although May starts on a Monday,
beginning on a Tuesday in February and August,
Beginning on a Wednesday in March and November,
Beginning on Thursday, June
and Friday marks the start of September and December.
This is great because there are only 14 calendar configurations: one for each of the seven non-leap years where January 1st begins on each of the seven days of the week, and one for each of the seven leap years where it begins on each day of the week.
The 2023 calendar will function in 2034, 2045, 2051, 2062, 2073, 2079, 2090, 2102, 2113, and 2119. Except when passing over a non-leap year that ends in 00, like 2100, the repeat time always extends to 12 years or shortens to an extra 6 years.
The pattern is repeated in 2025's calendar in 2031, 2042, 2053, 2059, 2070, 2081, 2087, 2098, 2110, and 2121.
The extra 6-year repeat at the end of the century on the calendar for 2026 will occur in the years 2037, 2043, 2054, 2065, 2071, 2082, 2093, 2099, 2105, and 2122.
The 2027s calendar repeats in 2038, 2049, 2055, 2066, 2077, 2083, 2094, 2100, 2106, and 2117, almost exactly matching the 2026s pattern.
For leap years, the recurrence pattern is every 28 years when not passing a non-leap year ending in 00, or 12 or 40 years when we do. 2024's calendar repeats in 2052, 2080, 2120, 2148, 2176, and 2216; 2028's in 2056, 2084, 2124, 2152, 2180, and 2220.
Knowing January 1st and whether it's a leap year lets you construct a one-page calendar for any year. Try it—you might find it easier than any other alternative!

Recep İnanç
3 years ago
Effective Technical Book Reading Techniques
Technical books aren't like novels. We need a new approach to technical texts. I've spent years looking for a decent reading method. I tried numerous ways before finding one that worked. This post explains how I read technical books efficiently.
What Do I Mean When I Say Effective?
Effectiveness depends on the book. Effective implies I know where to find answers after reading a reference book. Effective implies I learned the book's knowledge after reading it.
I use reference books as tools in my toolkit. I won't carry all my tools; I'll merely need them. Non-reference books teach me techniques. I never have to make an effort to use them since I always have them.
Reference books I like:
Design Patterns: Elements of Reusable Object-Oriented Software
Refactoring: Improving the Design of Existing Code
You can also check My Top Takeaways from Refactoring here.
Non-reference books I like:
The Approach
Technical books might be overwhelming to read in one sitting. Especially when you have no idea what is coming next as you read. When you don't know how deep the rabbit hole goes, you feel lost as you read. This is my years-long method for overcoming this difficulty.
Whether you follow the step-by-step guide or not, remember these:
Understand the terminology. Make sure you get the meaning of any terms you come across more than once. The likelihood that a term will be significant increases as you encounter it more frequently.
Know when to stop. I've always believed that in order to truly comprehend something, I must delve as deeply as possible into it. That, however, is not usually very effective. There are moments when you have to draw the line and start putting theory into practice (if applicable).
Look over your notes. When reading technical books or documents, taking notes is a crucial habit to develop. Additionally, you must regularly examine your notes if you want to get the most out of them. This will assist you in internalizing the lessons you acquired from the book. And you'll see that the urge to review reduces with time.
Let's talk about how I read a technical book step by step.
0. Read the Foreword/Preface
These sections are crucial in technical books. They answer Who should read it, What each chapter discusses, and sometimes How to Read? This is helpful before reading the book. Who could know the ideal way to read the book better than the author, right?
1. Scanning
I scan the chapter. Fast scanning is needed.
I review the headings.
I scan the pictures quickly.
I assess the chapter's length to determine whether I might divide it into more manageable sections.
2. Skimming
Skimming is faster than reading but slower than scanning.
I focus more on the captions and subtitles for the photographs.
I read each paragraph's opening and closing sentences.
I examined the code samples.
I attempt to grasp each section's basic points without getting bogged down in the specifics.
Throughout the entire reading period, I make an effort to make mental notes of what may require additional attention and what may not. Because I don't want to spend time taking physical notes, kindly notice that I am using the term "mental" here. It is much simpler to recall. You may think that this is more significant than typing or writing “Pay attention to X.”
I move on quickly. This is something I considered crucial because, when trying to skim, it is simple to start reading the entire thing.
3. Complete reading
Previous steps pay off.
I finished reading the chapter.
I concentrate on the passages that I mentally underlined when skimming.
I put the book away and make my own notes. It is typically more difficult than it seems for me. But it's important to speak in your own words. You must choose the right words to adequately summarize what you have read. How do those words make you feel? Additionally, you must be able to summarize your notes while you are taking them. Sometimes as I'm writing my notes, I realize I have no words to convey what I'm thinking or, even worse, I start to doubt what I'm writing down. This is a good indication that I haven't internalized that idea thoroughly enough.
I jot my inquiries down. Normally, I read on while compiling my questions in the hopes that I will learn the answers as I read. I'll explore those issues more if I wasn't able to find the answers to my inquiries while reading the book.
Bonus!
Best part: If you take lovely notes like I do, you can publish them as a blog post with a few tweaks.
Conclusion
This is my learning journey. I wanted to show you. This post may help someone with a similar learning style. You can alter the principles above for any technical material.

Pen Magnet
3 years ago
Why Google Staff Doesn't Work
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.
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.
Plot the influence of each employee over time using the X and Y axes, respectively.
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).
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.
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CyberPunkMetalHead
2 years ago
Why Bitcoin NFTs Are Incomprehensible yet Likely Here to Stay
I'm trying to understand why Bitcoin NFTs aren't ready.
Ordinals, a new Bitcoin protocol, has been controversial. NFTs can be added to Bitcoin transactions using the protocol. They are not tokens or fungible. Bitcoin NFTs are transaction metadata. Yes. They're not owned.
In January, the Ordinals protocol allowed data like photos to be directly encoded onto sats, the smallest units of Bitcoin worth 0.00000001 BTC, on the Bitcoin blockchain. Ordinals does not need a sidechain or token like other techniques. The Ordinals protocol has encoded JPEG photos, digital art, new profile picture (PFP) projects, and even 1993 DOOM onto the Bitcoin network.
Ordinals inscriptions are permanent digital artifacts preserved on the Bitcoin blockchain. It differs from Ethereum, Solana, and Stacks NFT technologies that allow smart contract creators to change information. Ordinals store the whole image or content on the blockchain, not just a link to an external server, unlike centralized databases, which can change the linked image, description, category, or contract identifier.
So far, more than 50,000 ordinals have been produced on the Bitcoin blockchain, and some of them have already been sold for astronomical amounts. The Ethereum-based CryptoPunks NFT collection spawned Ordinal Punk. Inscription 620 sold for 9.5 BTC, or $218,000, the most.
Segwit and Taproot, two important Bitcoin blockchain updates, enabled this. These protocols store transaction metadata, unlike Ethereum, where the NFT is the token. Bitcoin's NFT is a sat's transaction details.
What effects do ordinary values and NFTs have on the Bitcoin blockchain?
Ordinals will likely have long-term effects on the Bitcoin Ecosystem since they store, transact, and compute more data.
Charges Ordinals introduce scalability challenges. The Bitcoin network has limited transaction throughput and increased fees during peak demand. NFTs could make network transactions harder and more expensive. Ordinals currently occupy over 50% of block space, according to Glassnode.
One of the protocols that supported Ordinals Taproot has also seen a huge uptick:
Taproot use increases block size and transaction costs.
This could cause network congestion but also support more L2s with Ordinals-specific use cases. Dune info here.
Storage Needs The Bitcoin blockchain would need to store more data to store NFT data directly. Since ordinals were introduced, blocksize has tripled from 0.7mb to over 2.2mb, which could increase storage costs and make it harder for nodes to join the network.
Use Case Diversity On the other hand, NFTs on the Bitcoin blockchain could broaden Bitcoin's use cases beyond storage and payment. This could expand Bitcoin's user base. This is two-sided. Bitcoin was designed to be trustless, decentralized, peer-to-peer money.
Chain to permanently store NFTs as ordinals will change everything.
Popularity rise This new use case will boost Bitcoin appeal, according to some. This argument fails since Bitcoin is the most popular cryptocurrency. Popularity doesn't require a new use case. Cryptocurrency adoption boosts Bitcoin. It need not compete with Ethereum or provide extra benefits to crypto investors. If there was a need for another chain that supports NFTs (there isn't), why would anyone choose the slowest and most expensive network? It appears contradictory and unproductive.
Nonetheless, holding an NFT on the Bitcoin blockchain is more secure than any other blockchain, but this has little utility.
Bitcoin NFTs are undoubtedly controversial. NFTs are strange and perhaps harmful to Bitcoin's mission. If Bitcoin NFTs are here to stay, I hope a sidechain or rollup solution will take over and leave the base chain alone.

Mircea Iosif
3 years ago
How To Start An Online Business That Will Be Profitable Without Investing A Lot Of Time
Don't know how to start an online business? Here's a guide. By following these recommendations, you can build a lucrative and profitable online business.
What Are Online Businesses Used For?
Most online businesses are websites. A self-created, self-managed website. You may sell things and services online.
To establish an internet business, you must locate a host and set up accounts with numerous companies. Once your accounts are set up, you may start publishing content and selling products or services.
How to Make Money from Your Online Business
Advertising and marketing are the best ways to make money online. You must develop strategies to contact new customers and generate leads. Make sure your website is search engine optimized so people can find you online.
Top 5 Online Business Tips for Startups:
1. Know your target audience's needs.
2. Make your website as appealing as possible.
3. Generate leads and sales with marketing.
4. Track your progress and learn from your mistakes to improve.
5. Be prepared to expand into new markets or regions.
How to Launch a Successful Online Business Without Putting in a Lot of Work
Build with a solid business model to start a profitable online business. By using these tips, you can start your online business without paying much.
First, develop a user-friendly website. You can use an internet marketing platform or create your own website. Once your website is live, optimize it for search engines and add relevant content.
Second, sell online. This can be done through ads or direct sales to website visitors. Finally, use social media to advertise your internet business. By accomplishing these things, you'll draw visitors to your website and make money.
When launching a business, invest long-term. This involves knowing your goals and how you'll pay for them. Volatility can have several effects on your business. If you offer things online, you may need to examine if the market is ready for them.
Invest wisely
Investing all your money in one endeavor can lead to too much risk and little ROI. Diversify your investments to take advantage of all available chances. So, your investments won't encounter unexpected price swings and you'll be immune to economic upheavals.
Financial news updates
When launching or running a thriving online business, financial news is crucial. By knowing current trends and upcoming developments, you can keep your business lucrative.
Keeping up with financial news can also help you avoid potential traps that could harm your bottom line. If you don't know about new legislation that could affect your industry, potential customers may choose another store when they learn about your business's problems.
Volatility ahead
You should expect volatility in the financial sector. Without a plan for coping with volatility, you could run into difficulty. If your organization relies on client input, you may not be able to exploit customer behavior shifts.
Your company could go bankrupt if you don't understand how fickle the stock market can be. By preparing for volatility, you can ensure your organization survives difficult times and market crashes.
Conclusion
Many internet businesses can be profitable. Start quickly with a few straightforward steps. Diversify your investments, follow financial news, and be prepared for volatility to develop a successful business.
Thanks for reading!

Vishal Chawla
3 years ago
5 Bored Apes borrowed to claim $1.1 million in APE tokens
Takeaway
Unknown user took advantage of the ApeCoin airdrop to earn $1.1 million.
He used a flash loan to borrow five BAYC NFTs, claim the airdrop, and repay the NFTs.
Yuga Labs, the creators of BAYC, airdropped ApeCoin (APE) to anyone who owns one of their NFTs yesterday.
For the Bored Ape Yacht Club and Mutant Ape Yacht Club collections, the team allocated 150 million tokens, or 15% of the total ApeCoin supply, worth over $800 million. Each BAYC holder received 10,094 tokens worth $80,000 to $200,000.
But someone managed to claim the airdrop using NFTs they didn't own. They used the airdrop's specific features to carry it out. And it worked, earning them $1.1 million in ApeCoin.
The trick was that the ApeCoin airdrop wasn't based on who owned which Bored Ape at a given time. Instead, anyone with a Bored Ape at the time of the airdrop could claim it. So if you gave someone your Bored Ape and you hadn't claimed your tokens, they could claim them.
The person only needed to get hold of some Bored Apes that hadn't had their tokens claimed to claim the airdrop. They could be returned immediately.
So, what happened?
The person found a vault with five Bored Ape NFTs that hadn't been used to claim the airdrop.
A vault tokenizes an NFT or a group of NFTs. You put a bunch of NFTs in a vault and make a token. This token can then be staked for rewards or sold (representing part of the value of the collection of NFTs). Anyone with enough tokens can exchange them for NFTs.
This vault uses the NFTX protocol. In total, it contained five Bored Apes: #7594, #8214, #9915, #8167, and #4755. Nobody had claimed the airdrop because the NFTs were locked up in the vault and not controlled by anyone.
The person wanted to unlock the NFTs to claim the airdrop but didn't want to buy them outright s o they used a flash loan, a common tool for large DeFi hacks. Flash loans are a low-cost way to borrow large amounts of crypto that are repaid in the same transaction and block (meaning that the funds are never at risk of not being repaid).
With a flash loan of under $300,000 they bought a Bored Ape on NFT marketplace OpenSea. A large amount of the vault's token was then purchased, allowing them to redeem the five NFTs. The NFTs were used to claim the airdrop, before being returned, the tokens sold back, and the loan repaid.
During this process, they claimed 60,564 ApeCoin airdrops. They then sold them on Uniswap for 399 ETH ($1.1 million). Then they returned the Bored Ape NFT used as collateral to the same NFTX vault.
Attack or arbitrage?
However, security firm BlockSecTeam disagreed with many social media commentators. A flaw in the airdrop-claiming mechanism was exploited, it said.
According to BlockSecTeam's analysis, the user took advantage of a "vulnerability" in the airdrop.
"We suspect a hack due to a flaw in the airdrop mechanism. The attacker exploited this vulnerability to profit from the airdrop claim" said BlockSecTeam.
For example, the airdrop could have taken into account how long a person owned the NFT before claiming the reward.
Because Yuga Labs didn't take a snapshot, anyone could buy the NFT in real time and claim it. This is probably why BAYC sales exploded so soon after the airdrop announcement.
