More on Entrepreneurship/Creators
Pat Vieljeux
3 years ago
The three-year business plan is obsolete for startups.
If asked, run.
An entrepreneur asked me about her pitch deck. A Platform as a Service (PaaS).
She told me she hadn't done her 5-year forecasts but would soon.
I said, Don't bother. I added "time-wasting."
“I've been asked”, she said.
“Who asked?”
“a VC”
“5-year forecast?”
“Yes”
“Get another VC. If he asks, it's because he doesn't understand your solution or to waste your time.”
Some VCs are lagging. They're still using steam engines.
10-years ago, 5-year forecasts were requested.
Since then, we've adopted a 3-year plan.
But It's outdated.
Max one year.
What has happened?
Revolutionary technology. NO-CODE.
Revolution's consequences?
Product viability tests are shorter. Hugely. SaaS and PaaS.
Let me explain:
Building a minimum viable product (MVP) that works only takes a few months.
1 to 2 months for practical testing.
Your company plan can be validated or rejected in 4 months as a consequence.
After validation, you can ask for VC money. Even while a prototype can generate revenue, you may not require any.
Good VCs won't ask for a 3-year business plan in that instance.
One-year, though.
If you want, establish a three-year plan, but realize that the second year will be different.
You may have changed your business model by then.
A VC isn't interested in a three-year business plan because your solution may change.
Your ability to create revenue will be key.
But also, to pivot.
They will be interested in your value proposition.
They will want to know what differentiates you from other competitors and why people will buy your product over another.
What will interest them is your resilience, your ability to bounce back.
Not to mention your mindset. The fact that you won’t get discouraged at the slightest setback.
The grit you have when facing adversity, as challenges will surely mark your journey.
The authenticity of your approach. They’ll want to know that you’re not just in it for the money, let alone to show off.
The fact that you put your guts into it and that you are passionate about it. Because entrepreneurship is a leap of faith, a leap into the void.
They’ll want to make sure you are prepared for it because it’s not going to be a walk in the park.
They’ll want to know your background and why you got into it.
They’ll also want to know your family history.
And what you’re like in real life.
So a 5-year plan…. You can bet they won’t give a damn. Like their first pair of shoes.
Matthew O'Riordan
3 years ago
Trends in SaaS Funding from 2016 to 2022
Christopher Janz of Point Nine Capital created the SaaS napkin in 2016. This post shows how founders have raised cash in the last 6 years. View raw data.
Round size
Unsurprisingly, round sizes have expanded and will taper down in 2022. In 2016, pre-seed rounds were $200k to $500k; currently, they're $1-$2m. Despite the macroeconomic scenario, Series A have expanded from $3m to $12m in 2016 to $6m and $18m in 2022.
Valuation
There are hints that valuations are rebounding this year. Pre-seed valuations in 2022 are $12m from $3m in 2016, and Series B prices are $270m from $100m in 2016.
Compared to public SaaS multiples, Series B valuations more closely reflect the market, but Seed and Series A prices seem to be inflated regardless of the market.
I'd like to know how each annual cohort performed for investors, based on the year they invested and the valuations. I can't access this information.
ARR
Seed firms' ARR forecasts have risen from $0 to $0.6m to $0 to $1m. 2016 expected $1.2m to $3m, 2021 $0.5m to $4m, and this year $0.5m to $2.5m, suggesting that Series A firms may raise with less ARR today. Series B minutes fell from $4.2m to $3m.
Capitalization Rate
2022 is the year that VCs start discussing capital efficiency in portfolio meetings. Given the economic shift in the markets and the stealthy VC meltdown, it's not surprising. Christopher Janz added capital efficiency to the SaaS Napkin as a new statistic for Series A (3.5x) and Series B. (2.5x). Your investors must live under a rock if they haven't asked about capital efficiency. If you're unsure:
The Capital Efficiency Ratio is the ratio of how much a company has spent growing revenue and how much they’re receiving in return. It is the broadest measure of company effectiveness in generating ARR
What next?
No one knows what's next, including me. All startup and growing enterprises around me are tightening their belts and extending their runways in anticipation of a difficult fundraising ride. If you're wanting to raise money but can wait, wait till the market is more stable and access to money is easier.
cdixon
3 years ago
2000s Toys, Secrets, and Cycles
During the dot-com bust, I started my internet career. People used the internet intermittently to check email, plan travel, and do research. The average internet user spent 30 minutes online a day, compared to 7 today. To use the internet, you had to "log on" (most people still used dial-up), unlike today's always-on, high-speed mobile internet. In 2001, Amazon's market cap was $2.2B, 1/500th of what it is today. A study asked Americans if they'd adopt broadband, and most said no. They didn't see a need to speed up email, the most popular internet use. The National Academy of Sciences ranked the internet 13th among the 100 greatest inventions, below radio and phones. The internet was a cool invention, but it had limited uses and wasn't a good place to build a business.
A small but growing movement of developers and founders believed the internet could be more than a read-only medium, allowing anyone to create and publish. This is web 2. The runner up name was read-write web. (These terms were used in prominent publications and conferences.)
Web 2 concepts included letting users publish whatever they want ("user generated content" was a buzzword), social graphs, APIs and mashups (what we call composability today), and tagging over hierarchical navigation. Technical innovations occurred. A seemingly simple but important one was dynamically updating web pages without reloading. This is now how people expect web apps to work. Mobile devices that could access the web were niche (I was an avid Sidekick user).
The contrast between what smart founders and engineers discussed over dinner and on weekends and what the mainstream tech world took seriously during the week was striking. Enterprise security appliances, essentially preloaded servers with security software, were a popular trend. Many of the same people would talk about "serious" products at work, then talk about consumer internet products and web 2. It was tech's biggest news. Web 2 products were seen as toys, not real businesses. They were hobbies, not work-related.
There's a strong correlation between rich product design spaces and what smart people find interesting, which took me some time to learn and led to blog posts like "The next big thing will start out looking like a toy" Web 2's novel product design possibilities sparked dinner and weekend conversations. Imagine combining these features. What if you used this pattern elsewhere? What new product ideas are next? This excited people. "Serious stuff" like security appliances seemed more limited.
The small and passionate web 2 community also stood out. I attended the first New York Tech meetup in 2004. Everyone fit in Meetup's small conference room. Late at night, people demoed their software and chatted. I have old friends. Sometimes I get asked how I first met old friends like Fred Wilson and Alexis Ohanian. These topics didn't interest many people, especially on the east coast. We were friends. Real community. Alex Rampell, who now works with me at a16z, is someone I met in 2003 when a friend said, "Hey, I met someone else interested in consumer internet." Rare. People were focused and enthusiastic. Revolution seemed imminent. We knew a secret nobody else did.
My web 2 startup was called SiteAdvisor. When my co-founders and I started developing the idea in 2003, web security was out of control. Phishing and spyware were common on Internet Explorer PCs. SiteAdvisor was designed to warn users about security threats like phishing and spyware, and then, using web 2 concepts like user-generated reviews, add more subjective judgments (similar to what TrustPilot seems to do today). This staged approach was common at the time; I called it "Come for the tool, stay for the network." We built APIs, encouraged mashups, and did SEO marketing.
Yahoo's 2005 acquisitions of Flickr and Delicious boosted web 2 in 2005. By today's standards, the amounts were small, around $30M each, but it was a signal. Web 2 was assumed to be a fun hobby, a way to build cool stuff, but not a business. Yahoo was a savvy company that said it would make web 2 a priority.
As I recall, that's when web 2 started becoming mainstream tech. Early web 2 founders transitioned successfully. Other entrepreneurs built on the early enthusiasts' work. Competition shifted from ideation to execution. You had to decide if you wanted to be an idealistic indie bar band or a pragmatic stadium band.
Web 2 was booming in 2007 Facebook passed 10M users, Twitter grew and got VC funding, and Google bought YouTube. The 2008 financial crisis tested entrepreneurs' resolve. Smart people predicted another great depression as tech funding dried up.
Many people struggled during the recession. 2008-2011 was a golden age for startups. By 2009, talented founders were flooding Apple's iPhone app store. Mobile apps were booming. Uber, Venmo, Snap, and Instagram were all founded between 2009 and 2011. Social media (which had replaced web 2), cloud computing (which enabled apps to scale server side), and smartphones converged. Even if social, cloud, and mobile improve linearly, the combination could improve exponentially.
This chart shows how I view product and financial cycles. Product and financial cycles evolve separately. The Nasdaq index is a proxy for the financial sentiment. Financial sentiment wildly fluctuates.
Next row shows iconic startup or product years. Bottom-row product cycles dictate timing. Product cycles are more predictable than financial cycles because they follow internal logic. In the incubation phase, enthusiasts build products for other enthusiasts on nights and weekends. When the right mix of technology, talent, and community knowledge arrives, products go mainstream. (I show the biggest tech cycles in the chart, but smaller ones happen, like web 2 in the 2000s and fintech and SaaS in the 2010s.)
Tech has changed since the 2000s. Few tech giants dominate the internet, exerting economic and cultural influence. In the 2000s, web 2 was ignored or dismissed as trivial. Entrenched interests respond aggressively to new movements that could threaten them. Creative patterns from the 2000s continue today, driven by enthusiasts who see possibilities where others don't. Know where to look. Crypto and web 3 are where I'd start.
Today's negative financial sentiment reminds me of 2008. If we face a prolonged downturn, we can learn from 2008 by preserving capital and focusing on the long term. Keep an eye on the product cycle. Smart people are interested in things with product potential. This becomes true. Toys become necessities. Hobbies become mainstream. Optimists build the future, not cynics.
Full article is available here
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xuanling11
3 years ago
Reddit NFT Achievement
Reddit's NFT market is alive and well.
NFT owners outnumber OpenSea on Reddit.
Reddit NFTs flip in OpenSea in days:
Fast-selling.
NFT sales will make Reddit's current communities more engaged.
I don't think NFTs will affect existing groups, but they will build hype for people to acquire them.
The first season of Collectibles is unique, but many missed the first season.
Second-season NFTs are less likely to be sold for a higher price than first-season ones.
If you use Reddit, it's fun to own NFTs.
Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
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? There is a clever solution.
see part 2
Jon Brosio
3 years ago
Every time I use this 6-part email sequence, I almost always make four figures.
(And you can have it for free)
Master email to sell anything.
Most novice creators don't know how to begin.
Many use online templates. These are usually fluff-filled and niche-specific.
They're robotic and "salesy."
I've attended 3 courses, read 10 books, and sent 600,000 emails in the past five years.
Outcome?
This *proven* email sequence assures me a month's salary every time I send it.
What you will discover in this article is that:
A full 6-part email sales cycle
The essential elements you must incorporate
placeholders and text-filled images
(Applies to any niche)
This can be a product introduction, holiday, or welcome sequence. This works for email-saleable products.
Let's start
Email 1: Describe your issue
This email is crucial.
How to? We introduce a subscriber or prospect's problem. Later, we'll frame our offer as the solution.
Label the:
Problem
Why it still hasn't been fixed
Resulting implications for the customer
This puts our new subscriber in solve mode and queues our offer:
Email 2: Amplify the consequences
We're still causing problems.
We've created the problem, but now we must employ emotion and storytelling to make it real. We also want to forecast life if nothing changes.
Let's feel:
What occurs if it is not resolved?
Why is it crucial to fix it immediately?
Tell a tale of a person who was in their position. To emphasize the effects, use a true account of another person (or of yourself):
Email 3: Share a transformation story
Selling stories.
Whether in an email, landing page, article, or video. Humanize stories. They give information meaning.
This is where "issue" becomes "solution."
Let's reveal:
A tale of success
A new existence and result
tools and tactics employed
Start by transforming yourself.
Email 4: Prove with testimonials
No one buys what you say.
Emotionally stirred people buy and act. They believe in the product. They feel that if they buy, it will work.
Social proof shows prospects that your solution will help them.
Add:
Earlier and Later
Testimonials
Reviews
Proof this deal works:
Email 5: Reveal your offer
It's showtime.
This is it. Until now, describing the offer and offering links to a landing page have been sparse in the email pictures.
We've been tense. Gaining steam. Building suspense. Email 5 reveals all.
In this email:
a description of the deal
A word about a promise
recapitulation of the transformation
and make a reference to the urgency Everything should be spelled out clearly:
Email no. 6: Instill urgency
When there are stakes, humans act.
Creating and marketing with haste raises the stakes. Urgency makes a prospect act because they'll miss out or gain immensely.
Urgency converts. Use:
short time
Screening
Scarcity
Urgency and conversions. Limited-time offers are easy.
TL;DR
Use this proven 6-part email sequence (that turns subscribers into profit):
Introduce a problem
Amplify it with emotions
Share transformation story
Prove it works with testimonials
Value-stack and present your offer
Drive urgency and entice the purchase