More on Entrepreneurship/Creators
Carter Kilmann
3 years ago
I finally achieved a $100K freelance income. Here's what I wish I knew.
We love round numbers, don't we? $100,000 is a frequent freelancing milestone. You feel like six figures means you're doing something properly.
You've most likely already conquered initial freelancing challenges like finding clients, setting fair pricing, coping with criticism, getting through dry spells, managing funds, etc.
You think I must be doing well. Last month, my freelance income topped $100,000.
That may not sound impressive considering I've been freelancing for 2.75 years, but I made 30% of that in the previous four months, which is crazy.
Here are the things I wish I'd known during the early days of self-employment that would have helped me hit $100,000 faster.
1. The Volatility of Freelancing Will Stabilize.
Freelancing is risky. No surprise.
Here's an example.
October 2020 was my best month, earning $7,150. Between $4,004 in September and $1,730 in November. Unsteady.
Freelancing is regrettably like that. Moving clients. Content requirements change. Allocating so much time to personal pursuits wasn't smart, but yet.
Stabilizing income takes time. Consider my rolling three-month average income since I started freelancing. My three-month average monthly income. In February, this metric topped $5,000. Now, it's in the mid-$7,000s, but it took a while to get there.
Finding freelance gigs that provide high pay, high volume, and recurring revenue is difficult. But it's not impossible.
TLDR: Don't expect a steady income increase at first. Be patient.
2. You Have More Value Than You Realize.
Writing is difficult. Assembling words, communicating a message, and provoking action are a puzzle.
People are willing to pay you for it because they can't do what you do or don't have enough time.
Keeping that in mind can have huge commercial repercussions.
When talking to clients, don't tiptoe. You can ignore ridiculous deadlines. You don't have to take unmanageable work.
You solve an issue, so make sure you get rightly paid.
TLDR: Frame services as problem-solutions. This will let you charge more and set boundaries.
3. Increase Your Prices.
I studied hard before freelancing. I read articles and watched videos about writing businesses.
I didn't want to work for pennies. Despite this clarity, I had no real strategy to raise my rates.
I then luckily stumbled into higher-paying work. We discussed fees and hours with a friend who launched a consulting business. It's subjective and speculative because value isn't standardized. One company may laugh at your charges. If your solution helps them create a solid ROI, another client may pay $200 per hour.
When he told me he charged his first client $125 per hour, I thought, Why not?
A new-ish client wanted to discuss a huge forthcoming project, so I raised my rates. They knew my worth, so they didn't blink when I handed them my new number.
TLDR: Increase rates periodically (e.g., every 6 or 12 months). Writing skill develops with practice. You'll gain value over time.
4. Remember Your Limits.
If you can squeeze additional time into a day, let me know. I can't manipulate time yet.
We all have time and economic limits. You could theoretically keep boosting rates, but your prospect pool diminishes. Outsourcing and establishing extra revenue sources might boost monthly revenues.
I've devoted a lot of time to side projects (hopefully extra cash sources), but I've only just started outsourcing. I wish I'd tried this earlier.
If you can discover good freelancers, you can grow your firm without sacrificing time.
TLDR: Expand your writing network immediately. You'll meet freelancers who understand your daily grind and locate reference sources.
5. Every Action You Take Involves an Investment. Be Certain to Select Correctly.
Investing in stocks or crypto requires paying money, right?
In business, time is your currency (and maybe money too). Your daily habits define your future. If you spend time collecting software customers and compiling content in the space, you'll end up with both. So be sure.
I only spend around 50% of my time on client work, therefore it's taken me nearly three years to earn $100,000. I spend the remainder of my time on personal projects including a freelance book, an investment newsletter, and this blog.
Why? I don't want to rely on client work forever. So, I'm working on projects that could pay off later and help me live a more fulfilling life.
TLDR: Consider the long-term impact of your time commitments, and don't overextend. You can only make so many "investments" in a given time.
6. LinkedIn Is an Endless Mine of Gold. Use It.
Why didn't I use LinkedIn earlier?
I designed a LinkedIn inbound lead strategy that generates 12 leads a month and a few high-quality offers. As a result, I've turned down good gigs. Wish I'd begun earlier.
If you want to create a freelance business, prioritize LinkedIn. Too many freelancers ignore this site, missing out on high-paying clients. Build your profile, post often, and interact.
TLDR: Study LinkedIn's top creators. Once you understand their audiences, start posting and participating daily.
For 99% of People, Freelancing is Not a Get-Rich-Quick Scheme.
Here's a list of things I wish I'd known when I started freelancing.
Although it is erratic, freelancing eventually becomes stable.
You deserve respect and discretion over how you conduct business because you have solved an issue.
Increase your charges rather than undervaluing yourself. If necessary, add a reminder to your calendar. Your worth grows with time.
In order to grow your firm, outsource jobs. After that, you can work on the things that are most important to you.
Take into account how your present time commitments may affect the future. It will assist in putting things into perspective and determining whether what you are doing is indeed worthwhile.
Participate on LinkedIn. You'll get better jobs as a result.
If I could give my old self (and other freelancers) one bit of advice, it's this:
Despite appearances, you're making progress.
Each job. Tweets. Newsletters. Progress. It's simpler to see retroactively than in the moment.
Consistent, intentional work pays off. No good comes from doing nothing. You must set goals, divide them into time-based targets, and then optimize your calendar.
Then you'll understand you're doing well.
Want to learn more? I’ll teach you.
Maddie Wang
3 years ago
Easiest and fastest way to test your startup idea!
Here's the fastest way to validate company concepts.
I squandered a year after dropping out of Stanford designing a product nobody wanted.
But today, I’m at 100k!
Differences:
I was designing a consumer product when I dropped out.
I coded MVP, got 1k users, and got YC interview.
Nice, huh?
WRONG!
Still coding and getting users 12 months later
WOULD PEOPLE PAY FOR IT? was the riskiest assumption I hadn't tested.
When asked why I didn't verify payment, I said,
Not-ready products. Now, nobody cares. The website needs work. Include this. Increase usage…
I feared people would say no.
After 1 year of pushing it off, my team told me they were really worried about the Business Model. Then I asked my audience if they'd buy my product.
So?
No, overwhelmingly.
I felt like I wasted a year building a product no one would buy.
Founders Cafe was the opposite.
Before building anything, I requested payment.
40 founders were interviewed.
Then we emailed Stanford, YC, and other top founders, asking them to join our community.
BOOM! 10/12 paid!
Without building anything, in 1 day I validated my startup's riskiest assumption. NOT 1 year.
Asking people to pay is one of the scariest things.
I understand.
I asked Stanford queer women to pay before joining my gay sorority.
I was afraid I'd turn them off or no one would pay.
Gay women, like those founders, were in such excruciating pain that they were willing to pay me upfront to help.
You can ask for payment (before you build) to see if people have the burning pain. Then they'll pay!
Examples from Founders Cafe members:
😮 Using a fake landing page, a college dropout tested a product. Paying! He built it and made $3m!
😮 YC solo founder faked a Powerpoint demo. 5 Enterprise paid LOIs. $1.5m raised, built, and in YC!
😮 A Harvard founder can convert Figma to React. 1 day, 10 customers. Built a tool to automate Figma -> React after manually fulfilling requests. 1m+
Bad example:
😭 Stanford Dropout Spends 1 Year Building Product Without Payment Validation
Some people build for a year and then get paying customers.
What I'm sharing is my experience and what Founders Cafe members have told me about validating startup ideas.
Don't waste a year like I did.
After my first startup failed, I planned to re-enroll at Stanford/work at Facebook.
After people paid, I quit for good.
I've hit $100k!
Hope this inspires you to request upfront payment! It'll change your life
Athirah Syamimi
3 years ago
Here's How I Built A Business Offering Unlimited Design Services in Just One Weekend.
Weekend project: limitless design service. It was fun to see whether I could start a business quickly.
I use no-code apps to save time and resources.
TL;DR I started a business utilizing EditorX for my website, Notion for client project management, and a few favors to finish my portfolio.
First step: research (Day 1)
I got this concept from a Kimp Instagram ad. The Minimalist Hustler Daily newsletter mentioned a similar and cheaper service (Graphically).
I Googled other unlimited design companies. Many provide different costs and services. Some supplied solely graphic design, web development, or copywriting.
Step 2: Brainstorming (Day 1)
I did something simple.
What benefits and services to provide
Price to charge
Since it's a one-person performance (for now), I'm focusing on graphic design. I can charge less.
So I don't overwhelm myself and can accommodate budget-conscious clientele.
Step 3: Construction (Day 1 & 2)
This project includes a management tool, a website, and a team procedure.
I built a project management tool and flow first. Once I had the flow and a Notion board, I tested it with design volunteers. They fake-designed while I built the website.
Tool for Project Management
I modified a Notion template. My goal is to keep clients and designers happy.
Team Approach
My sister, my partner, and I kept this business lean. I tweaked the Notion board to make the process smooth. By the end of Sunday, I’d say it’s perfect!
Website
I created the website after they finished the fake design demands. EditorX's drag-and-drop builder attracted me. I didn't need to learn code, and there are templates.
I used a template wireframe.
This project's hardest aspect is developing the site. It's my first time using EditorX and I'm no developer.
People answer all your inquiries in a large community forum.
As a first-time user developing a site in two days, I think I performed OK. Here's the site for feedback.
4th step: testing (Day 2)
Testing is frustrating because it works or doesn't. My testing day was split in two.
testing the workflow from payment to onboarding to the website
the demand being tested
It's working so far. If someone gets the trial, they can request design work.
I've gotten a couple of inquiries about demand. I’ll be working with them as a start.
Completion
Finally! I built my side project in one weekend. It's too early to tell if this is successful. I liked that I didn't squander months of resources testing out an idea.
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Vitalik
3 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
Monroe Mayfield
2 years ago
CES 2023: A Third Look At Upcoming Trends
Las Vegas hosted CES 2023. This third and last look at CES 2023 previews upcoming consumer electronics trends that will be crucial for market share.
Definitely start with ICT. Qualcomm CEO Cristiano Amon spoke to CNBC from Las Vegas on China's crackdown and the company's automated driving systems for electric vehicles (EV). The business showed a concept car and its latest Snapdragon processor designs, which offer expanded digital interactions through SalesForce-partnered CRM platforms.
Electrification is reviving Michigan's automobile industry. Michigan Local News reports that $14 billion in EV and battery manufacturing investments will benefit the state. The report also revealed that the Strategic Outreach and Attraction Reserve (SOAR) fund had generated roughly $1 billion for the state's automotive sector.
Ars Technica is great for technology, society, and the future. After CES 2023, Jonathan M. Gitlin published How many electric car chargers are enough? Read about EV charging network issues and infrastructure spending. Politics aside, rapid technological advances enable EV charging network expansion in American cities and abroad.
Finally, the UNEP's The Future of Electric Vehicles and Material Resources: A Foresight Brief. Understanding how lithium-ion batteries will affect EV sales is crucial. Climate change affects EVs in various ways, but electrification and mining trends stand out because more EVs demand more energy-intensive metals and rare earths. Areas & Producers has been publishing my electrification and mining trends articles. Follow me if you wish to write for the publication.
The Weekend Brief (TWB) will routinely cover tech, industrials, and global commodities in global markets, including stock markets. Read more about the future of key areas and critical producers of the global economy in Areas & Producers.
Sam Warain
3 years ago
Sam Altman, CEO of Open AI, foresees the next trillion-dollar AI company
“I think if I had time to do something else, I would be so excited to go after this company right now.”
Sam Altman, CEO of Open AI, recently discussed AI's present and future.
Open AI is important. They're creating the cyberpunk and sci-fi worlds.
They use the most advanced algorithms and data sets.
GPT-3...sound familiar? Open AI built most copyrighting software. Peppertype, Jasper AI, Rytr. If you've used any, you'll be shocked by the quality.
Open AI isn't only GPT-3. They created DallE-2 and Whisper (a speech recognition software released last week).
What will they do next? What's the next great chance?
Sam Altman, CEO of Open AI, recently gave a lecture about the next trillion-dollar AI opportunity.
Who is the organization behind Open AI?
Open AI first. If you know, skip it.
Open AI is one of the earliest private AI startups. Elon Musk, Greg Brockman, and Rebekah Mercer established OpenAI in December 2015.
OpenAI has helped its citizens and AI since its birth.
They have scary-good algorithms.
Their GPT-3 natural language processing program is excellent.
The algorithm's exponential growth is astounding. GPT-2 came out in November 2019. May 2020 brought GPT-3.
Massive computation and datasets improved the technique in just a year. New York Times said GPT-3 could write like a human.
Same for Dall-E. Dall-E 2 was announced in April 2022. Dall-E 2 won a Colorado art contest.
Open AI's algorithms challenge jobs we thought required human innovation.
So what does Sam Altman think?
The Present Situation and AI's Limitations
During the interview, Sam states that we are still at the tip of the iceberg.
So I think so far, we’ve been in the realm where you can do an incredible copywriting business or you can do an education service or whatever. But I don’t think we’ve yet seen the people go after the trillion dollar take on Google.
He's right that AI can't generate net new human knowledge. It can train and synthesize vast amounts of knowledge, but it simply reproduces human work.
“It’s not going to cure cancer. It’s not going to add to the sum total of human scientific knowledge.”
But the key word is yet.
And that is what I think will turn out to be wrong that most surprises the current experts in the field.
Reinforcing his point that massive innovations are yet to come.
But where?
The Next $1 Trillion AI Company
Sam predicts a bio or genomic breakthrough.
There’s been some promising work in genomics, but stuff on a bench top hasn’t really impacted it. I think that’s going to change. And I think this is one of these areas where there will be these new $100 billion to $1 trillion companies started, and those areas are rare.
Avoid human trials since they take time. Bio-materials or simulators are suitable beginning points.
AI may have a breakthrough. DeepMind, an OpenAI competitor, has developed AlphaFold to predict protein 3D structures.
It could change how we see proteins and their function. AlphaFold could provide fresh understanding into how proteins work and diseases originate by revealing their structure. This could lead to Alzheimer's and cancer treatments. AlphaFold could speed up medication development by revealing how proteins interact with medicines.
Deep Mind offered 200 million protein structures for scientists to download (including sustainability, food insecurity, and neglected diseases).
Being in AI for 4+ years, I'm amazed at the progress. We're past the hype cycle, as evidenced by the collapse of AI startups like C3 AI, and have entered a productive phase.
We'll see innovative enterprises that could replace Google and other trillion-dollar companies.
What happens after AI adoption is scary and unpredictable. How will AGI (Artificial General Intelligence) affect us? Highly autonomous systems that exceed humans at valuable work (Open AI)
My guess is that the things that we’ll have to figure out are how we think about fairly distributing wealth, access to AGI systems, which will be the commodity of the realm, and governance, how we collectively decide what they can do, what they don’t do, things like that. And I think figuring out the answer to those questions is going to just be huge. — Sam Altman CEO