More on Entrepreneurship/Creators
Jim Siwek
3 years ago
In 2022, can a lone developer be able to successfully establish a SaaS product?
In the early 2000s, I began developing SaaS. I helped launch an internet fax service that delivered faxes to email inboxes. Back then, it saved consumers money and made the procedure easier.
Google AdWords was young then. Anyone might establish a new website, spend a few hundred dollars on keywords, and see dozens of new paying clients every day. That's how we launched our new SaaS, and these clients stayed for years. Our early ROI was sky-high.
Changing times
The situation changed dramatically after 15 years. Our paid advertising cost $200-$300 for every new customer. Paid advertising takes three to four years to repay.
Fortunately, we still had tens of thousands of loyal clients. Good organic rankings gave us new business. We needed less sponsored traffic to run a profitable SaaS firm.
Is it still possible?
Since selling our internet fax firm, I've dreamed about starting a SaaS company. One I could construct as a lone developer and progressively grow a dedicated customer base, as I did before in a small team.
It seemed impossible to me. Solo startups couldn't afford paid advertising. SEO was tough. Even the worst SaaS startup ideas attracted VC funding. How could I compete with startups that could hire great talent and didn't need to make money for years (or ever)?
The One and Only Way to Learn
After years of talking myself out of SaaS startup ideas, I decided to develop and launch one. I needed to know if a solitary developer may create a SaaS app in 2022.
Thus, I did. I invented webwriter.ai, an AI-powered writing tool for website content, from hero section headlines to blog posts, this year. I soft-launched an MVP in July.
Considering the Issue
Now that I've developed my own fully capable SaaS app for site builders and developers, I wonder if it's still possible. Can webwriter.ai be successful?
I know webwriter.ai's proposal is viable because Jasper.ai and Grammarly are also AI-powered writing tools. With competition comes validation.
To Win, Differentiate
To compete with well-funded established brands, distinguish to stand out to a portion of the market. So I can speak directly to a target user, unlike larger competition.
I created webwriter.ai to help web builders and designers produce web content rapidly. This may be enough differentiation for now.
Budget-Friendly Promotion
When paid search isn't an option, we get inventive. There are more tools than ever to promote a new website.
Organic Results
on social media (Twitter, Instagram, TikTok, LinkedIn)
Marketing with content that is compelling
Link Creation
Listings in directories
references made in blog articles and on other websites
Forum entries
The Beginning of the Journey
As I've labored to construct my software, I've pondered a new mantra. Not sure where that originated from, but I like it. I'll live by it and teach my kids:
“Do the work.”
Jayden Levitt
3 years ago
Billionaire who was disgraced lost his wealth more quickly than anyone in history
If you're not genuine, you'll be revealed.
Sam Bankman-Fried (SBF) was called the Cryptocurrency Warren Buffet.
No wonder.
SBF's trading expertise, Blockchain knowledge, and ability to construct FTX attracted mainstream investors.
He had a fantastic worldview, donating much of his riches to charity.
As the onion layers peel back, it's clear he wasn't the altruistic media figure he portrayed.
SBF's mistakes were disastrous.
Customer deposits were traded and borrowed by him.
With ten other employees, he shared a $40 million mansion where they all had polyamorous relationships.
Tone-deaf and wasteful marketing expenditures, such as the $200 million spent to change the name of the Miami Heat stadium to the FTX Arena
Democrats received a $40 million campaign gift.
And now there seems to be no regret.
FTX was a 32-billion-dollar cryptocurrency exchange.
It went bankrupt practically overnight.
SBF, FTX's creator, exploited client funds to leverage trade.
FTX had $1 billion in customer withdrawal reserves against $9 billion in liabilities in sister business Alameda Research.
Bloomberg Billionaire Index says it's the largest and fastest net worth loss in history.
It gets worse.
SBF's net worth is $900 Million, however he must still finalize FTX's bankruptcy.
SBF's arrest in the Bahamas and SEC inquiry followed news that his cryptocurrency exchange had crashed, losing billions in customer deposits.
A journalist contacted him on Twitter D.M., and their exchange is telling.
His ideas are revealed.
Kelsey Piper says they didn't expect him to answer because people under investigation don't comment.
Bankman-Fried wanted to communicate, and the interaction shows he has little remorse.
SBF talks honestly about FTX gaming customers' money and insults his competition.
Reporter Kelsey Piper was outraged by what he said and felt the mistakes SBF says plague him didn't evident in the messages.
Before FTX's crash, SBF was a poster child for Cryptocurrency regulation and avoided criticizing U.S. regulators.
He tells Piper that his lobbying is just excellent PR.
It shows his genuine views and supports cynics' opinions that his attempts to win over U.S. authorities were good for his image rather than Crypto.
SBF’s responses are in Grey, and Pipers are in Blue.
It's unclear if SBF cut corners for his gain. In their Twitter exchange, Piper revisits an interview question about ethics.
SBF says, "All the foolish sh*t I said"
SBF claims FTX has never invested customer monies.
Piper challenged him on Twitter.
While he insisted FTX didn't use customer deposits, he said sibling business Alameda borrowed too much from FTX's balance sheet.
He did, basically.
When consumers tried to withdraw money, FTX was short.
SBF thought Alameda had enough money to cover FTX customers' withdrawals, but life sneaks up on you.
SBF believes most exchanges have done something similar to FTX, but they haven't had a bank run (a bunch of people all wanting to get their deposits out at the same time).
SBF believes he shouldn't have consented to the bankruptcy and kept attempting to raise more money because withdrawals would be open in a month with clients whole.
If additional money came in, he needed $8 billion to bridge the creditors' deficit, and there aren't many corporations with $8 billion to spare.
Once clients feel protected, they will continue to leave their assets on the exchange, according to one idea.
Kevin OLeary, a world-renowned hedge fund manager, says not all investors will walk through the open gate once the company is safe, therefore the $8 Billion wasn't needed immediately.
SBF claims the bankruptcy was his biggest error because he could have accumulated more capital.
Final Reflections
Sam Bankman-Fried, 30, became the world's youngest billionaire in four years.
Never listen to what people say about investing; watch what they do.
SBF is a trader who gets wrecked occasionally.
Ten first-time entrepreneurs ran FTX, screwing each other with no risk management.
It prevents opposing or challenging perspectives and echo chamber highs.
Twitter D.M. conversation with a journalist is the final nail.
He lacks an experienced crew.
This event will surely speed up much-needed regulation.
It's also prompted cryptocurrency exchanges to offer proof of reserves to calm customers.
Simone Basso
3 years ago
How I set up my teams to be successful
After 10 years of working in scale-ups, I've embraced a few concepts for scaling Tech and Product teams.
First, cross-functionalize teams. Product Managers represent the business, Product Designers the consumer, and Engineers build.
I organize teams of 5-10 individuals, following AWS's two pizza teams guidelines, with a Product Trio guiding each.
If more individuals are needed to reach a goal, I group teams under a Product Trio.
With Engineering being the biggest group, Staff/Principal Engineers often support the Trio on cross-team technical decisions.
Product Managers, Engineering Managers, or Engineers in the team may manage projects (depending on the project or aim), but the trio is collectively responsible for the team's output and outcome.
Once the Product Trio model is created, roles, duties, team ceremonies, and cooperation models must be clarified.
Keep reporting lines by discipline. Line managers are accountable for each individual's advancement, thus it's crucial that they know the work in detail.
Cross-team collaboration becomes more important after 3 teams (15-30 people). Teams can easily diverge in how they write code, run ceremonies, and build products.
Establishing groups of people that are cross-team, but grouped by discipline and skills, sharing and agreeing on working practices becomes critical.
The “Spotify Guild” model has been where I’ve taken a lot of my inspiration from.
Last, establish a taxonomy for communication channels.
In Slack, I create one channel per team and one per guild (and one for me to have discussions with the team leads).
These are just some of the basic principles I follow to organize teams.
A book I particularly like about team types and how they interact with each other is https://teamtopologies.com/.
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Vitalik
3 years ago
Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.
Trevor Stark
3 years ago
Economics is complete nonsense.
Mainstream economics haven't noticed.
What come to mind when I say the word "economics"?
Probably GDP, unemployment, and inflation.
If you've ever watched the news or listened to an economist, they'll use data like these to defend a political goal.
The issue is that these statistics are total bunk.
I'm being provocative, but I mean it:
The economy is not measured by GDP.
How many people are unemployed is not counted in the unemployment rate.
Inflation is not measured by the CPI.
All orthodox economists' major economic statistics are either wrong or falsified.
Government institutions create all these stats. The administration wants to reassure citizens the economy is doing well.
GDP does not reflect economic expansion.
GDP measures a country's economic size and growth. It’s calculated by the BEA, a government agency.
The US has the world's largest (self-reported) GDP, growing 2-3% annually.
If GDP rises, the economy is healthy, say economists.
Why is the GDP flawed?
GDP measures a country's yearly spending.
The government may adjust this to make the economy look good.
GDP = C + G + I + NX
C = Consumer Spending
G = Government Spending
I = Investments (Equipment, inventories, housing, etc.)
NX = Exports minus Imports
GDP is a country's annual spending.
The government can print money to boost GDP. The government has a motive to increase and manage GDP.
Because government expenditure is part of GDP, printing money and spending it on anything will raise GDP.
They've done this. Since 1950, US government spending has grown 8% annually, faster than GDP.
In 2022, government spending accounted for 44% of GDP. It's the highest since WWII. In 1790-1910, it was 3% of GDP.
Who cares?
The economy isn't only spending. Focus on citizens' purchasing power or quality of life.
Since GDP just measures spending, the government can print money to boost GDP.
Even if Americans are poorer than last year, economists can say GDP is up and everything is fine.
How many people are unemployed is not counted in the unemployment rate.
The unemployment rate measures a country's labor market. If unemployment is high, people aren't doing well economically.
The BLS estimates the (self-reported) unemployment rate as 3-4%.
Why is the unemployment rate so high?
The US government surveys 100k persons to measure unemployment. They extrapolate this data for the country.
They come into 3 categories:
Employed
People with jobs are employed … duh.
Unemployed
People who are “jobless, looking for a job, and available for work” are unemployed
Not in the labor force
The “labor force” is the employed + the unemployed.
The unemployment rate is the percentage of unemployed workers.
Problem is unemployed definition. You must actively seek work to be considered unemployed.
You're no longer unemployed if you haven't interviewed in 4 weeks.
This shit makes no goddamn sense.
Why does this matter?
You can't interview if there are no positions available. You're no longer unemployed after 4 weeks.
In 1994, the BLS redefined "unemployed" to exclude discouraged workers.
If you haven't interviewed in 4 weeks, you're no longer counted in the unemployment rate.
If unemployment were measured by total unemployed, it would be 25%.
Because the government wants to keep the unemployment rate low, they modify the definition.
If every US resident was unemployed and had no job interviews, economists would declare 0% unemployment. Excellent!
Inflation is not measured by the CPI.
The BLS measures CPI. This month was the highest since 1981.
CPI measures the cost of a basket of products across time. Food, energy, shelter, and clothes are included.
A 9.1% CPI means the basket of items is 9.1% more expensive.
What is the CPI problem?
Here's a more detailed explanation of CPI's flaws.
In summary, CPI is manipulated to be understated.
Housing costs are understated to manipulate CPI. Housing accounts for 33% of the CPI because it's the biggest expense for most people.
This signifies it's the biggest CPI weight.
Rather than using actual house prices, the Bureau of Labor Statistics essentially makes shit up. You can read more about the process here.
Surprise! It’s bullshit
The BLS stated Shelter's price rose 5.5% this month.
House prices are up 11-21%. (Source 1, Source 2, Source 3)
Rents are up 14-26%. (Source 1, Source 2)
Why is this important?
If CPI included housing prices, it would be 12-15 percent this month, not 9.1 percent.
9% inflation is nuts. Your money's value halves every 7 years at 9% inflation.
Worse is 15% inflation. Your money halves every 4 years at 15% inflation.
If everyone realized they needed to double their wage every 4-5 years to stay wealthy, there would be riots.
Inflation drains our money's value so the government can keep printing it.
The Solution
Most individuals know the existing system doesn't work, but can't explain why.
People work hard yet lag behind. The government lies about the economy's data.
In reality:
GDP has been down since 2008
25% of Americans are unemployed
Inflation is actually 15%
People might join together to vote out kleptocratic politicians if they knew the reality.
Having reliable economic data is the first step.
People can't understand the situation without sufficient information. Instead of immigrants or billionaires, people would blame liar politicians.
Here’s the vision:
A decentralized, transparent, and global dashboard that tracks economic data like GDP, unemployment, and inflation for every country on Earth.
Government incentives influence economic statistics.
ShadowStats has already started this effort, but the calculations must be transparent, decentralized, and global to be effective.
If interested, email me at trevorstark02@gmail.com.
Here are some links to further your research:
Alexander Nguyen
3 years ago
A Comparison of Amazon, Microsoft, and Google's Compensation
Learn or earn
In 2020, I started software engineering. My base wage has progressed as follows:
Amazon (2020): $112,000
Microsoft (2021): $123,000
Google (2022): $169,000
I didn't major in math, but those jumps appear more than a 7% wage increase. Here's a deeper look at the three.
The Three Categories of Compensation
Most software engineering compensation packages at IT organizations follow this format.
Minimum Salary
Base salary is pre-tax income. Most organizations give a base pay. This is paid biweekly, twice monthly, or monthly.
Recruiting Bonus
Sign-On incentives are one-time rewards to new hires. Companies need an incentive to switch. If you leave early, you must pay back the whole cost or a pro-rated amount.
Equity
Equity is complex and requires its own post. A company will promise to give you a certain amount of company stock but when you get it depends on your offer. 25% per year for 4 years, then it's gone.
If a company gives you $100,000 and distributes 25% every year for 4 years, expect $25,000 worth of company stock in your stock brokerage on your 1 year work anniversary.
Performance Bonus
Tech offers may include yearly performance bonuses. Depends on performance and funding. I've only seen 0-20%.
Engineers' overall compensation usually includes:
Base Salary + Sign-On + (Total Equity)/4 + Average Performance Bonus
Amazon: (TC: 150k)
Base Pay System
Amazon pays Seattle employees monthly on the first work day. I'd rather have my money sooner than later, even if it saves processing and pay statements.
The company upped its base pay cap from $160,000 to $350,000 to compete with other tech companies.
Performance Bonus
Amazon has no performance bonus, so you can work as little or as much as you like and get paid the same. Amazon is savvy to avoid promising benefits it can't deliver.
Sign-On Bonus
Amazon gives two two-year sign-up bonuses. First-year workers could receive $20,000 and second-year workers $15,000. It's probably to make up for the company's strange equity structure.
If you leave during the first year, you'll owe the entire money and a prorated amount for the second year bonus.
Equity
Most organizations prefer a 25%, 25%, 25%, 25% equity structure. Amazon takes a different approach with end-heavy equity:
the first year, 5%
15% after one year.
20% then every six months
We thought it was constructed this way to keep staff longer.
Microsoft (TC: 185k)
Base Pay System
Microsoft paid biweekly.
Gainful Performance
My offer letter suggested a 0%-20% performance bonus. Everyone will be satisfied with a 10% raise at year's end.
But misleading press where the budget for the bonus is doubled can upset some employees because they won't earn double their expected bonus. Still barely 10% for 2022 average.
Sign-On Bonus
Microsoft's sign-on bonus is a one-time payout. The contract can require 2-year employment. You must negotiate 1 year. It's pro-rated, so that's fair.
Equity
Microsoft is one of those companies that has standard 25% equity structure. Except if you’re a new graduate.
In that case it’ll be
25% six months later
25% each year following that
New grads will acquire equity in 3.5 years, not 4. I'm guessing it's to keep new grads around longer.
Google (TC: 300k)
Base Pay Structure
Google pays biweekly.
Performance Bonus
Google's offer letter specifies a 15% bonus. It's wonderful there's no cap, but I might still get 0%. A little more than Microsoft’s 10% and a lot more than Amazon’s 0%.
Sign-On Bonus
Google gave a 1-year sign-up incentive. If the contract is only 1 year, I can move without any extra obligations.
Not as fantastic as Amazon's sign-up bonuses, but the remainder of the package might compensate.
Equity
We covered Amazon's tail-heavy compensation structure, so Google's front-heavy equity structure may surprise you.
Annual structure breakdown
33% Year 1
33% Year 2
22% Year 3
12% Year 4
The goal is to get them to Google and keep them there.
Final Thoughts
This post hopefully helped you understand the 3 firms' compensation arrangements.
There's always more to discuss, such as refreshers, 401k benefits, and business discounts, but I hope this shows a distinction between these 3 firms.