More on Entrepreneurship/Creators

Jared Heyman
2 years ago
The survival and demise of Y Combinator startups
I've written a lot about Y Combinator's success, but as any startup founder or investor knows, many startups fail.
Rebel Fund invests in the top 5-10% of new Y Combinator startups each year, so we focus on identifying and supporting the most promising technology startups in our ecosystem. Given the power law dynamic and asymmetric risk/return profile of venture capital, we worry more about our successes than our failures. Since the latter still counts, this essay will focus on the proportion of YC startups that fail.
Since YC's launch in 2005, the figure below shows the percentage of active, inactive, and public/acquired YC startups by batch.
As more startups finish, the blue bars (active) decrease significantly. By 12 years, 88% of startups have closed or exited. Only 7% of startups reach resolution each year.
YC startups by status after 12 years:
Half the startups have failed, over one-third have exited, and the rest are still operating.
In venture investing, it's said that failed investments show up before successful ones. This is true for YC startups, but only in their early years.
Below, we only present resolved companies from the first chart. Some companies fail soon after establishment, but after a few years, the inactive vs. public/acquired ratio stabilizes around 55:45. After a few years, a YC firm is roughly as likely to quit as fail, which is better than I imagined.
I prepared this post because Rebel investors regularly question me about YC startup failure rates and how long it takes for them to exit or shut down.
Early-stage venture investors can overlook it because 100x investments matter more than 0x investments.
YC founders can ignore it because it shouldn't matter if many of their peers succeed or fail ;)

Emils Uztics
3 years ago
This billionaire created a side business that brings around $90,000 per month.
Dharmesh Shah co-founded HubSpot. WordPlay reached $90,000 per month in revenue without utilizing any of his wealth.
His method:
Take Advantage Of An Established Trend
Remember Wordle? Dharmesh was instantly hooked. As was the tech world.
HubSpot's co-founder noted inefficiencies in a recent My First Million episode. He wanted to play daily. Dharmesh, a tinkerer and software engineer, decided to design a word game.
He's a billionaire. How could he?
Wordle had limitations in his opinion;
Dharmesh is fundamentally a developer. He desired to start something new and increase his programming knowledge;
This project may serve as an excellent illustration for his son, who had begun learning about software development.
Better It Up
Building a new Wordle wasn't successful.
WordPlay lets you play with friends and family. You could challenge them and compare the results. It is a built-in growth tool.
WordPlay features:
the capacity to follow sophisticated statistics after creating an account;
continuous feedback on your performance;
Outstanding domain name (wordplay.com).
Project Development
WordPlay has 9.5 million visitors and 45 million games played since February.
HubSpot co-founder credits tremendous growth to flywheel marketing, pushing the game through his own following.
Choosing an exploding specialty and making sharing easy also helped.
Shah enabled Google Ads on the website to test earning potential. Monthly revenue was $90,000.
That's just Google Ads. If monetization was the goal, a specialized ad network like Ezoic could double or triple the amount.
Wordle was a great buy for The New York Times at $1 million.

Ben Chino
3 years ago
100-day SaaS buildout.
We're opening up Maki through a series of Medium posts. We'll describe what Maki is building and how. We'll explain how we built a SaaS in 100 days. This isn't a step-by-step guide to starting a business, but a product philosophy to help you build quickly.
Focus on end-users.
This may seem obvious, but it's important to talk to users first. When we started thinking about Maki, we interviewed 100 HR directors from SMBs, Next40 scale-ups, and major Enterprises to understand their concerns. We initially thought about the future of employment, but most of their worries centered on Recruitment. We don't have a clear recruiting process, it's time-consuming, we recruit clones, we don't support diversity, etc. And as hiring managers, we couldn't help but agree.
Co-create your product with your end-users.
We went to the drawing board, read as many books as possible (here, here, and here), and when we started getting a sense for a solution, we questioned 100 more operational HR specialists to corroborate the idea and get a feel for our potential answer. This confirmed our direction to help hire more objectively and efficiently.
Back to the drawing board, we designed our first flows and screens. We organized sessions with certain survey respondents to show them our early work and get comments. We got great input that helped us build Maki, and we met some consumers. Obsess about users and execute alongside them.
Don’t shoot for the moon, yet. Make pragmatic choices first.
Once we were convinced, we began building. To launch a SaaS in 100 days, we needed an operating principle that allowed us to accelerate while still providing a reliable, secure, scalable experience. We focused on adding value and outsourced everything else. Example:
Concentrate on adding value. Reuse existing bricks.
When determining which technology to use, we looked at our strengths and the future to see what would last. Node.js for backend, React for frontend, both with typescript. We thought this technique would scale well since it would attract more talent and the surrounding mature ecosystem would help us go quicker.
We explored for ways to bootstrap services while setting down strong foundations that might support millions of users. We built our backend services on NestJS so we could extend into microservices later. Hasura, a GraphQL APIs engine, automates Postgres data exposing through a graphQL layer. MUI's ready-to-use components powered our design-system. We used well-maintained open-source projects to speed up certain tasks.
We outsourced important components of our platform (Auth0 for authentication, Stripe for billing, SendGrid for notifications) because, let's face it, we couldn't do better. We choose to host our complete infrastructure (SQL, Cloud run, Logs, Monitoring) on GCP to simplify our work between numerous providers.
Focus on your business, use existing bricks for the rest. For the curious, we'll shortly publish articles detailing each stage.
Most importantly, empower people and step back.
We couldn't have done this without the incredible people who have supported us from the start. Since Powership is one of our key values, we provided our staff the power to make autonomous decisions from day one. Because we believe our firm is its people, we hired smart builders and let them build.
Nicolas left Spendesk to create scalable interfaces using react-router, react-queries, and MUI. JD joined Swile and chose Hasura as our GraphQL engine. Jérôme chose NestJS to build our backend services. Since then, Justin, Ben, Anas, Yann, Benoit, and others have followed suit.
If you consider your team a collective brain, you should let them make decisions instead of directing them what to do. You'll make mistakes, but you'll go faster and learn faster overall.
Invest in great talent and develop a strong culture from the start. Here's how to establish a SaaS in 100 days.
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Marcus Lu
3 years ago
The Brand Structure of U.S. Electric Vehicle Production
Will Tesla be able to maintain its lead in the EV market for very long?
This is one of the most pressing issues in the American auto sector today. One positive aspect of Tesla is the company's devoted customer base and recognizable name recognition (similar to Apple). It also invests more in research and development per vehicle than its rivals and has a head start in EV production.
Conversely, established automakers like Volkswagen are actively plotting their strategy to surpass Tesla. As the current market leaders, they have decades of experience in the auto industry and are spending billions to catch up.
We've visualized data from the EPA's 2022 Automotive Trends Report to bring you up to speed on this developing story.
Info for the Model Year of 2021
The full production data used in this infographic is for the 2021 model year, but it comes from a report for 2022.
Combined EV and PHEV output is shown in the table below (plug-in hybrid electric vehicle).
It is important to note that Toyota and Stellantis, the two largest legacy automakers in this dataset, only produced PHEVs. Toyota's first electric vehicle, the bZ4X, won't hit the market until 2023.
Stellantis seems to be falling even further behind, despite having enormous unrealized potential in its Jeep and Ram brands. Stellantis CEO Carlos Tavares said in a recent interview that the firm has budgeted $36 billion for electrification and software.
Legacy Brands with the Most Momentum
In the race to develop electric vehicles, some long-standing manufacturers have gotten the jump on their rivals.
Volkswagen, one of these storied manufacturers, has made a significant investment in electric vehicles (EVs) in the wake of the Dieselgate scandal. The company plans to roll out multiple EV models, including the ID.3 hatchback, ID.4 SUV, and ID. Buzz, with the goal of producing 22 million EVs by 2028. (an electric revival of the classic Microbus).
Even Ford is keeping up, having just announced an EV investment of $22 billion between 2021 and 2025. In November of 2022, the company manufactured their 150,000th Mustang Mach-E, and by the end of 2023, they hoped to have 270,000 of them in circulation.
Additionally, over 200,000 F-150 Lightnings have been reserved since Ford announced the truck. The Lightning is scheduled to have a production run of 15,000 in 2022, 55,000 in 2023, and 80,000 in 2024. Ford's main competitor in the electric pickup truck segment, Rivian, is on track to sell 25,000 vehicles by 2022.

DC Palter
2 years ago
Why Are There So Few Startups in Japan?
Japan's startup challenge: 7 reasons
Every day, another Silicon Valley business is bought for a billion dollars, making its founders rich while growing the economy and improving consumers' lives.
Google, Amazon, Twitter, and Medium dominate our daily lives. Tesla automobiles and Moderna Covid vaccinations.
The startup movement started in Silicon Valley, California, but the rest of the world is catching up. Global startup buzz is rising. Except Japan.
644 of CB Insights' 1170 unicorns—successful firms valued at over $1 billion—are US-based. China follows with 302 and India third with 108.
Japan? 6!
1% of US startups succeed. The third-largest economy is tied with small Switzerland for startup success.
Mexico (8), Indonesia (12), and Brazil (12) have more successful startups than Japan (16). South Korea has 16. Yikes! Problem?
Why Don't Startups Exist in Japan More?
Not about money. Japanese firms invest in startups. To invest in startups, big Japanese firms create Silicon Valley offices instead of Tokyo.
Startups aren't the issue either. Local governments are competing to be Japan's Shirikon Tani, providing entrepreneurs financing, office space, and founder visas.
Startup accelerators like Plug and Play in Tokyo, Osaka, and Kyoto, the Startup Hub in Kobe, and Google for Startups are many.
Most of the companies I've encountered in Japan are either local offices of foreign firms aiming to expand into the Japanese market or small businesses offering local services rather than disrupting a staid industry with new ideas.
There must be a reason Japan can develop world-beating giant corporations like Toyota, Nintendo, Shiseido, and Suntory but not inventive startups.
Culture, obviously. Japanese culture excels in teamwork, craftsmanship, and quality, but it hates moving fast, making mistakes, and breaking things.
If you have a brilliant idea in Silicon Valley, quit your job, get money from friends and family, and build a prototype. To fund the business, you approach angel investors and VCs.
Most non-startup folks don't aware that venture capitalists don't want good, profitable enterprises. That's wonderful if you're developing a solid small business to consult, open shops, or make a specialty product. However, you must pay for it or borrow money. Venture capitalists want moon rockets. Silicon Valley is big or bust. Almost 90% will explode and crash. The few successes are remarkable enough to make up for the failures.
Silicon Valley's high-risk, high-reward attitude contrasts with Japan's incrementalism. Japan makes the best automobiles and cleanrooms, but it fails to produce new items that grow the economy.
Changeable? Absolutely. But, what makes huge manufacturing enterprises successful and what makes Japan a safe and comfortable place to live are inextricably connected with the lack of startups.
Barriers to Startup Development in Japan
These are the 7 biggest obstacles to Japanese startup success.
Unresponsive Employment Market
While the lifelong employment system in Japan is evolving, the average employee stays at their firm for 12 years (15 years for men at large organizations) compared to 4.3 years in the US. Seniority, not experience or aptitude, determines career routes, making it tough to quit a job to join a startup and then return to corporate work if it fails.
Conservative Buyers
Even if your product is buggy and undocumented, US customers will migrate to a cheaper, superior one. Japanese corporations demand perfection from their trusted suppliers and keep with them forever. Startups need income fast, yet product evaluation takes forever.
Failure intolerance
Japanese business failures harm lives. Failed forever. It hinders risk-taking. Silicon Valley embraces failure. Build another startup if your first fails. Build a third if that fails. Every setback is viewed as a learning opportunity for success.
4. No Corporate Purchases
Silicon Valley industrial giants will buy fast-growing startups for a lot of money. Many huge firms have stopped developing new goods and instead buy startups after the product is validated.
Japanese companies prefer in-house product development over startup acquisitions. No acquisitions mean no startup investment and no investor reward.
Startup investments can also be monetized through stock market listings. Public stock listings in Japan are risky because the Nikkei was stagnant for 35 years while the S&P rose 14x.
5. Social Unity Above Wealth
In Silicon Valley, everyone wants to be rich. That creates a competitive environment where everyone wants to succeed, but it also promotes fraud and societal problems.
Japan values communal harmony above individual success. Wealthy folks and overachievers are avoided. In Japan, renegades are nearly impossible.
6. Rote Learning Education System
Japanese high school graduates outperform most Americans. Nonetheless, Japanese education is known for its rote memorization. The American system, which fails too many kids, emphasizes creativity to create new products.
Immigration.
Immigrants start 55% of successful Silicon Valley firms. Some come for university, some to escape poverty and war, and some are recruited by Silicon Valley startups and stay to start their own.
Japan is difficult for immigrants to start a business due to language barriers, visa restrictions, and social isolation.
How Japan Can Promote Innovation
Patchwork solutions to deep-rooted cultural issues will not work. If customers don't buy things, immigration visas won't aid startups. Startups must have a chance of being acquired for a huge sum to attract investors. If risky startups fail, employees won't join.
Will Japan never have a startup culture?
Once a consensus is reached, Japan changes rapidly. A dwindling population and standard of living may lead to such consensus.
Toyota and Sony were firms with renowned founders who used technology to transform the world. Repeatable.
Silicon Valley is flawed too. Many people struggle due to wealth disparities, job churn and layoffs, and the tremendous ups and downs of the economy caused by stock market fluctuations.
The founders of the 10% successful startups are heroes. The 90% that fail and return to good-paying jobs with benefits are never mentioned.
Silicon Valley startup culture and Japanese corporate culture are opposites. Each have pros and cons. Big Japanese corporations make the most reliable, dependable, high-quality products yet move too slowly. That's good for creating cars, not social networking apps.
Can innovation and success be encouraged without eroding social cohesion? That can motivate software firms to move fast and break things while recognizing the beauty and precision of expert craftsmen? A hybrid culture where Japan can make the world's best and most original items. Hopefully.

Vitalik
3 years ago
An approximate introduction to how zk-SNARKs are possible (part 2)
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? But it turns out that there is a clever solution.
Polynomials
Polynomials are a special class of algebraic expressions of the form:
- x+5
- x^4
- x^3+3x^2+3x+1
- 628x^{271}+318x^{270}+530x^{269}+…+69x+381
i.e. they are a sum of any (finite!) number of terms of the form cx^k
There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: polynomials are a single mathematical object that can contain an unbounded amount of information (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.
Furthermore, a single equation between polynomials can represent an unbounded number of equations between numbers. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:
- A(0)+B(0)=C(0)
- A(1)+B(1)=C(1)
- A(2)+B(2)=C(2)
- A(3)+B(3)=C(3)
And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:
- 12+1=13
- 10+8=18
- 15+8=23
- 15+13=28
You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:
- A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
- B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
- C(x)=5x+13
Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.
Comparing a polynomial to itself
You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you also check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)
As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.
Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).
Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F actually satisfies this condition by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:
H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}
Where Z(x) = (x-0)*(x-1)*…*(x-98).
You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!
Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.
see part 3
