More on Entrepreneurship/Creators

Khoi Ho
3 years ago
After working at seven startups, here are the early-stage characteristics that contributed to profitability, unicorn status or successful acquisition.
I've worked in a People role at seven early-stage firms for over 15 years (I enjoy chasing a dream!). Few of the seven achieved profitability, including unicorn status or acquisition.
Did early-stage startups share anything? Was there a difference between winners and losers? YES.
I support founders and entrepreneurs building financially sustainable enterprises with a compelling cause. This isn't something everyone would do. A company's success demands more than guts. Founders drive startup success.
Six Qualities of Successful Startups
Successful startup founders either innately grasped the correlation between strong team engagement and a well-executed business model, or they knew how to ask and listen to others (executive coaches, other company leaders, the team itself) to learn about it.
Successful startups:
1. Co-founders agreed and got along personally.
Multi-founder startups are common. When co-founders agree on strategic decisions and are buddies, there's less friction and politics at work.
As a co-founder, ask your team if you're aligned. They'll explain.
I've seen C-level leaders harbor personal resentments over disagreements. A co-departure founder's caused volatile leadership and work disruptions that the team struggled to manage during and after.
2. Team stayed.
Successful startups have low turnover. Nobody is leaving. There may be a termination for performance, but other team members will have observed the issues and agreed with the decision.
You don't want organizational turnover of 30%+, with leaders citing performance issues but the team not believing them. This breeds suspicion.
Something is wrong if many employees leave voluntarily or involuntarily. You may hear about lack of empowerment, support, or toxic leadership in exit interviews and from the existing team. Intellectual capital loss and resource instability harm success.
3. Team momentum.
A successful startup's team is excited about its progress. Consistently achieving goals and having trackable performance metrics. Some describe this period of productivity as magical, with great talents joining the team and the right people in the right places. Increasing momentum.
I've also seen short-sighted decisions where only some departments, like sales and engineering, had goals. Lack of a unified goals system created silos and miscommunication. Some employees felt apathetic because they didn't know how they contributed to team goals.
4. Employees advanced in their careers.
Even if you haven't created career pathing or professional development programs, early-stage employees will grow and move into next-level roles. If you hire more experienced talent and leaders, expect them to mentor existing team members. Growing companies need good performers.
New talent shouldn't replace and discard existing talent. This creates animosity and makes existing employees feel unappreciated for their early contributions to the company.
5. The company lived its values.
Culture and identity are built on lived values. A company's values affect hiring, performance management, rewards, and other processes. Identify, practice, and believe in company values. Starting with team values instead of management or consultants helps achieve this. When a company's words and actions match, it builds trust.
When company values are beautifully displayed on a wall but few employees understand them, the opposite is true. If an employee can't name the company values, they're useless.
6. Communication was clear.
When necessary information is shared with the team, they feel included, trusted, and like owners. Transparency means employees have the needed information to do their jobs. Disclosure builds trust. The founders answer employees' questions honestly.
Information accessibility decreases office politics. Without transparency, even basic information is guarded and many decisions are made in secret. I've seen founders who don't share financial, board meeting, or compensation and equity information. The founders' lack of trust in the team wasn't surprising, so it was reciprocated.
The Choices
Finally. All six of the above traits (leadership alignment, minimal turnover, momentum, professional advancement, values, and transparency) were high in the profitable startups I've worked at, including unicorn status or acquisition.
I've seen these as the most common and constant signals of startup success or failure.
These characteristics are the product of founders' choices. These decisions lead to increased team engagement and business execution.
Here's something to consider for startup employees and want-to-bes. 90% of startups fail, despite the allure of building something new and gaining ownership. With the emotional and time investment in startup formation, look for startups with these traits to reduce your risk.
Both you and the startup will thrive in these workplaces.

SAHIL SAPRU
3 years ago
How I grew my business to a $5 million annual recurring revenue
Scaling your startup requires answering customer demands, not growth tricks.
I cofounded Freedo Rentals in 2019. I reached 50 lakh+ ARR in 6 months before quitting owing to the epidemic.
Freedo aimed to solve 2 customer pain points:
Users lacked a reliable last-mile transportation option.
The amount that Auto walas charge for unmetered services
Solution?
Effectively simple.
Build ports at high-demand spots (colleges, residential societies, metros). Electric ride-sharing can meet demand.
We had many problems scaling. I'll explain using the AARRR model.
Brand unfamiliarity or a novel product offering were the problems with awareness. Nobody knew what Freedo was or what it did.
Problem with awareness: Content and advertisements did a poor job of communicating the task at hand. The advertisements clashed with the white-collar part because they were too cheesy.
Retention Issue: We encountered issues, indicating that the product was insufficient. Problems with keyless entry, creating bills, stealing helmets, etc.
Retention/Revenue Issue: Costly compared to established rivals. Shared cars were 1/3 of our cost.
Referral Issue: Missing the opportunity to seize the AHA moment. After the ride, nobody remembered us.
Once you know where you're struggling with AARRR, iterative solutions are usually best.
Once you have nailed the AARRR model, most startups use paid channels to scale. This dependence, on paid channels, increases with scale unless you crack your organic/inbound game.
Over-index growth loops. Growth loops increase inflow and customers as you scale.
When considering growth, ask yourself:
Who is the solution's ICP (Ideal Customer Profile)? (To whom are you selling)
What are the most important messages I should convey to customers? (This is an A/B test.)
Which marketing channels ought I prioritize? (Conduct analysis based on the startup's maturity/stage.)
Choose the important metrics to monitor for your AARRR funnel (not all metrics are equal)
Identify the Flywheel effect's growth loops (inertia matters)
My biggest mistakes:
not paying attention to consumer comments or satisfaction. It is the main cause of problems with referrals, retention, and acquisition for startups. Beyond your NPS, you should consider second-order consequences.
The tasks at hand should be quite clear.
Here's my scaling equation:
Growth = A x B x C
A = Funnel top (Traffic)
B = Product Valuation (Solving a real pain point)
C = Aha! (Emotional response)
Freedo's A, B, and C created a unique offering.
Freedo’s ABC:
A — Working or Studying population in NCR
B — Electric Vehicles provide last-mile mobility as a clean and affordable solution
C — One click booking with a no-noise scooter
Final outcome:
FWe scaled Freedo to Rs. 50 lakh MRR and were growing 60% month on month till the pandemic ceased our growth story.
How we did it?
We tried ambassadors and coupons. WhatsApp was our most successful A/B test.
We grew widespread adoption through college and society WhatsApp groups. We requested users for referrals in community groups.
What worked for us won't work for others. This scale underwent many revisions.
Every firm is different, thus you must know your customers. Needs to determine which channel to prioritize and when.
Users desired a safe, time-bound means to get there.
This (not mine) growth framework helped me a lot. You should follow suit.

Alex Mathers
2 years ago
How to Produce Enough for People to Not Neglect You
Internet's fantastic, right?
We've never had a better way to share our creativity.
I can now draw on my iPad and tweet or Instagram it to thousands. I may get some likes.
With such a great, free tool, you're not alone.
Millions more bright-eyed artists are sharing their work online.
The issue is getting innovative work noticed, not sharing it.
In a world where creators want attention, attention is valuable.
We build for attention.
Attention helps us establish a following, make money, get notoriety, and make a difference.
Most of us require attention to stay sane while creating wonderful things.
I know how hard it is to work hard and receive little views.
How do we receive more attention, more often, in a sea of talent?
Advertising and celebrity endorsements are options. These may work temporarily.
To attract true, organic, and long-term attention, you must create in high quality, high volume, and consistency.
Adapting Steve Martin's Be so amazing, they can't ignore you (with a mention to Dan Norris in his great book Create or Hate for the reminder)
Create a lot.
Eventually, your effort will gain traction.
Traction shows your work's influence.
Traction is when your product sells more. Traction is exponential user growth. Your work is shared more.
No matter how good your work is, it will always have minimal impact on the world.
Your work can eventually dent or puncture. Daily, people work to dent.
To achieve this tipping point, you must consistently produce exceptional work.
Expect traction after hundreds of outputs.
Dilbert creator Scott Adams says repetition persuades. If you don't stop, you can persuade practically anyone with anything.
Volume lends believability. So make more.
I worked as an illustrator for at least a year and a half without any recognition. After 150 illustrations on iStockphoto, my work started selling.
With 350 illustrations on iStock, I started getting decent client commissions.
Producing often will improve your craft and draw attention.
It's the only way to succeed. More creation means better results and greater attention.
Austin Kleon says you can improve your skill in relative anonymity before you become famous. Before obtaining traction, generate a lot and become excellent.
Most artists, even excellent ones, don't create consistently enough to get traction.
It may hurt. For makers who don't love and flow with their work, it's extremely difficult.
Your work must bring you to life.
To generate so much that others can't ignore you, decide what you'll accomplish every day (or most days).
Commit and be patient.
Prepare for zero-traction.
Anticipating this will help you persevere and create.
My online guru Grant Cardone says: Anything worth doing is worth doing every day.
Do.
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Yucel F. Sahan
3 years ago
How I Created the Day's Top Product on Product Hunt
In this article, I'll describe a weekend project I started to make something. It was Product Hunt's #1 of the Day, #2 Weekly, and #4 Monthly product.
How did I make Landing Page Checklist so simple? Building and launching took 3 weeks. I worked 3 hours a day max. Weekends were busy.
It's sort of a long story, so scroll to the bottom of the page to see what tools I utilized to create Landing Page Checklist :x
As a matter of fact, it all started with the startups-investments blog; Startup Bulletin, that I started writing in 2018. No, don’t worry, I won’t be going that far behind. The twitter account where I shared the blog posts of this newsletter was inactive for a looong time. I was holding this Twitter account since 2009, I couldn’t bear to destroy it. At the same time, I was thinking how to evaluate this account.
So I looked for a weekend assignment.
Weekend undertaking: Generate business names
Barash and I established a weekend effort to stay current. Building things helped us learn faster.
Simple. Startup Name Generator The utility generated random startup names. After market research for SEO purposes, we dubbed it Business Name Generator.
Backend developer Barash dislikes frontend work. He told me to write frontend code. Chakra UI and Tailwind CSS were recommended.
It was the first time I have heard about Tailwind CSS.
Before this project, I made mobile-web app designs in Sketch and shared them via Zeplin. I can read HTML-CSS or React code, but not write it. I didn't believe myself but followed Barash's advice.
My home page wasn't responsive when I started. Here it was:)
And then... Product Hunt had something I needed. Me-only! A website builder that gives you clean Tailwind CSS code and pre-made web components (like Elementor). Incredible.
I bought it right away because it was so easy to use. Best part: It's not just index.html. It includes all needed files. Like
postcss.config.js
README.md
package.json
among other things, tailwind.config.js
This is for non-techies.
Tailwind.build; which is Shuffle now, allows you to create and export projects for free (with limited features). You can try it by visiting their website.
After downloading the project, you can edit the text and graphics in Visual Studio (or another text editor). This HTML file can be hosted whenever.
Github is an easy way to host a landing page.
your project via Shuffle for export
your website's content, edit
Create a Gitlab, Github, or Bitbucket account.
to Github, upload your project folder.
Integrate Vercel with your Github account (or another platform below)
Allow them to guide you in steps.
Finally. If you push your code to Github using Github Desktop, you'll do it quickly and easily.
Speaking of; here are some hosting and serverless backend services for web applications and static websites for you host your landing pages for FREE!
I host landingpage.fyi on Vercel but all is fine. You can choose any platform below with peace in mind.
Vercel
Render
Netlify
After connecting your project/repo to Vercel, you don’t have to do anything on Vercel. Vercel updates your live website when you update Github Desktop. Wow!
Tails came out while I was using tailwind.build. Although it's prettier, tailwind.build is more mobile-friendly. I couldn't resist their lovely parts. Tails :)
Tails have several well-designed parts. Some components looked awful on mobile, but this bug helped me understand Tailwind CSS.
Unlike Shuffle, Tails does not include files when you export such as config.js, main.js, README.md. It just gives you the HTML code. Suffle.dev is a bit ahead in this regard and with mobile-friendly blocks if you ask me. Of course, I took advantage of both.
creativebusinessnames.co is inactive, but I'll leave a deployment link :)
Adam Wathan's YouTube videos and Tailwind's official literature helped me, but I couldn't have done it without Tails and Shuffle. These tools helped me make landing pages. I shouldn't have started over.
So began my Tailwind CSS adventure. I didn't build landingpage. I didn't plan it to be this long; sorry.
I learnt a lot while I was playing around with Shuffle and Tails Builders.
Long story short I built landingpage.fyi with the help of these tools;
Learning, building, and distribution
Shuffle (Started with a Shuffle Template)
Tails (Used components from here)
Sketch (to handle icons, logos, and .svg’s)
metatags.io (Auto Generator Meta Tags)
Vercel (Hosting)
Github Desktop (Pushing code to Github -super easy-)
Visual Studio Code (Edit my code)
Mailerlite (Capture Emails)
Jarvis / Conversion.ai (%90 of the text on website written by AI 😇 )
CookieHub (Consent Management)
That's all. A few things:
The Outcome
.fyi Domain: Why?
I'm often asked this.
I don't know, but I wanted to include the landing page term. Popular TLDs are gone. I saw my alternatives. brief and catchy.
CSS Tailwind Resources
I'll share project resources like Tails and Shuffle.
Beginner Tailwind (I lately enrolled in this course but haven’t completed it yet.)
Thanks for reading my blog's first post. Please share if you like it.

Mickey Mellen
2 years ago
Shifting from Obsidian to Tana?
I relocated my notes database from Roam Research to Obsidian earlier this year expecting to stay there for a long. Obsidian is a terrific tool, and I explained my move in that post.
Moving everything to Tana faster than intended. Tana? Why?
Tana is just another note-taking app, but it does it differently. Three note-taking apps existed before Tana:
simple note-taking programs like Apple Notes and Google Keep.
Roam Research and Obsidian are two graph-style applications that assisted connect your notes.
You can create effective tables and charts with data-focused tools like Notion and Airtable.
Tana is the first great software I've encountered that combines graph and data notes. Google Keep will certainly remain my rapid notes app of preference. This Shu Omi video gives a good overview:
Tana handles everything I did in Obsidian with books, people, and blog entries, plus more. I can find book quotes, log my workouts, and connect my thoughts more easily. It should make writing blog entries notes easier, so we'll see.
Tana is now invite-only, but if you're interested, visit their site and sign up. As Shu noted in the video above, the product hasn't been published yet but seems quite polished.
Whether I stay with Tana or not, I'm excited to see where these apps are going and how they can benefit us all.

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
