More on Entrepreneurship/Creators
Caleb Naysmith
3 years ago
Ads Coming to Medium?
Could this happen?
Medium isn't like other social media giants. It wasn't a dot-com startup that became a multi-trillion-dollar social media firm. It launched in 2012 but didn't gain popularity until later. Now, it's one of the largest sites by web traffic, but it's still little compared to most. Most of Medium's traffic is external, but they don't run advertisements, so it's all about memberships.
Medium isn't profitable, but they don't disclose how terrible the problem is. Most of the $163 million they raised has been spent or used for acquisitions. If the money turns off, Medium can't stop paying its writers since the site dies. Writers must be paid, but they can't substantially slash payment without hurting the platform. The existing model needs scale to be viable and has a low ceiling. Facebook and other free social media platforms are struggling to retain users. Here, you must pay to appreciate it, and it's bad for writers AND readers. If I had the same Medium stats on YouTube, I'd make thousands of dollars a month.
Then what? Medium has tried to monetize by offering writers a cut of new members, but that's unsustainable. People-based growth is limited. Imagine recruiting non-Facebook users and getting them to pay to join. Some may, but I'd rather write.
Alternatives:
Donation buttons
Tiered subscriptions ($5, $10, $25, etc.)
Expanding content
and these may be short-term fixes, but they're not as profitable as allowing ads. Advertisements can pay several dollars per click and cents every view. If you get 40,000 views a month like me, that's several thousand instead of a few hundred. Also, Medium would have enough money to split ad revenue with writers, who would make more. I'm among the top 6% of Medium writers. Only 6% of Medium writers make more than $100, and I made $500 with 35,000 views last month. Compared to YouTube, the top 1% of Medium authors make a lot. Mr. Beast and PewDiePie make MILLIONS a month, yet top Medium writers make tens of thousands. Sure, paying 3 or 4 people a few grand, or perhaps tens of thousands, will keep them around. What if great authors leveraged their following to go huge on YouTube and abandoned Medium? If people use Medium to get successful on other platforms, Medium will be continuously cycling through authors and paying them to stay.
Ads might make writing on Medium more profitable than making videos on YouTube because they could preserve the present freemium model and pay users based on internal views. The $5 might be ad-free.
Consider: Would you accept Medium ads? A $5 ad-free version + pay-as-you-go, etc. What are your thoughts on this?
Original post available here
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/.
SAHIL SAPRU
3 years ago
Growth tactics that grew businesses from 1 to 100
Everyone wants a scalable startup.
Innovation helps launch a startup. The secret to a scalable business is growth trials (from 1 to 100).
Growth marketing combines marketing and product development for long-term growth.
Today, I'll explain growth hacking strategies popular startups used to scale.
1/ A Facebook user's social value is proportional to their friends.
Facebook built its user base using content marketing and paid ads. Mark and his investors feared in 2007 when Facebook's growth stalled at 90 million users.
Chamath Palihapitiya was brought in by Mark.
The team tested SEO keywords and MAU chasing. The growth team introduced “people you may know”
This feature reunited long-lost friends and family. Casual users became power users as the retention curve flattened.
Growth Hack Insights: With social network effect the value of your product or platform increases exponentially if you have users you know or can relate with.
2/ Airbnb - Focus on your value propositions
Airbnb nearly failed in 2009. The company's weekly revenue was $200 and they had less than 2 months of runway.
Enter Paul Graham. The team noticed a pattern in 40 listings. Their website's property photos sucked.
Why?
Because these photos were taken with regular smartphones. Users didn't like the first impression.
Graham suggested traveling to New York to rent a camera, meet with property owners, and replace amateur photos with high-resolution ones.
A week later, the team's weekly revenue doubled to $400, indicating they were on track.
Growth Hack Insights: When selling an “online experience” ensure that your value proposition is aesthetic enough for users to enjoy being associated with them.
3/ Zomato - A company's smartphone push ensured growth.
Zomato delivers food. User retention was a challenge for the founders. Indian food customers are notorious for switching brands at the drop of a hat.
Zomato wanted users to order food online and repeat orders throughout the week.
Zomato created an attractive website with “near me” keywords for SEO indexing.
Zomato gambled to increase repeat orders. They only allowed mobile app food orders.
Zomato thought mobile apps were stickier. Product innovations in search/discovery/ordering or marketing campaigns like discounts/in-app notifications/nudges can improve user experience.
Zomato went public in 2021 after users kept ordering food online.
Growth Hack Insights: To improve user retention try to build platforms that build user stickiness. Your product and marketing team will do the rest for them.
4/ Hotmail - Signaling helps build premium users.
Ever sent or received an email or tweet with a sign — sent from iPhone?
Hotmail did it first! One investor suggested Hotmail add a signature to every email.
Overnight, thousands joined the company. Six months later, the company had 1 million users.
When serving an existing customer, improve their social standing. Signaling keeps the top 1%.
5/ Dropbox - Respect loyal customers
Dropbox is a company that puts people over profits. The company prioritized existing users.
Dropbox rewarded loyal users by offering 250 MB of free storage to anyone who referred a friend. The referral hack helped Dropbox get millions of downloads in its first few months.
Growth Hack Insights: Think of ways to improve the social positioning of your end-user when you are serving an existing customer. Signaling goes a long way in attracting the top 1% to stay.
These experiments weren’t hacks. Hundreds of failed experiments and user research drove these experiments. Scaling up experiments is difficult.
Contact me if you want to grow your startup's user base.
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Katharine Valentino
3 years ago
A Gun-toting Teacher Is Like a Cook With Rat Poison
Pink or blue AR-15s?
A teacher teaches; a gun kills. Killing isn't teaching. Killing is opposite of teaching.
Without 27 school shootings this year, we wouldn't be talking about arming teachers. Gun makers, distributors, and the NRA cause most school shootings. Gun makers, distributors, and the NRA wouldn't be huge business if weapons weren't profitable.
Guns, ammo, body armor, holsters, concealed carriers, bore sights, cleaner kits, spare magazines and speed loaders, gun safes, and ear protection are sold. And more guns.
And lots more profit.
Guns aren't bread. You eat a loaf of bread in a week or so and then must buy more. Bread makers will make money. Winchester 94.30–30 1899 Lever Action Rifle from 1894 still kills. (For safety, I won't link to the ad.) Gun makers don't object if you collect antique weapons, but they need you to buy the latest, in-style killing machine. The youngster who killed 19 students and 2 teachers at Robb Elementary School in Uvalde, Texas, used an AR-15. Better yet, two.
Salvador Ramos, the Robb Elementary shooter, is a "killing influencer" He pushes consumers to buy items, which benefits manufacturers and distributors. Like every previous AR-15 influencer, he profits Colt, the rifle's manufacturer, and 52,779 gun dealers in the U.S. Ramos and other AR-15 influences make us fear for our safety and our children's. Fearing for our safety, we acquire 20 million firearms a year and live in a gun culture.
So now at school, we want to arm teachers.
Consider. Which of your teachers would you have preferred in body armor with a gun drawn?
Miss Summers? Remember her bringing daisies from her yard to second grade? She handed each student a beautiful flower. Miss Summers loved everyone, even those with AR-15s. She can't shoot.
Frasier? Mr. Frasier turned a youngster over down to explain "invert." Mr. Frasier's hands shook when he wasn't flipping fifth-graders and fractions. He may have shot wrong.
Mrs. Barkley barked in high school English class when anyone started an essay with "But." Mrs. Barkley dubbed Abie a "Jewboy" and gave him terrible grades. Arming Miss Barkley is like poisoning the chef.
Think back. Do you remember a teacher with a gun? No. Arming teachers so the gun industry can make more money is the craziest idea ever.
Or maybe you agree with Ted Cruz, the gun lobby-bought senator, that more guns reduce gun violence. After the next school shooting, you'll undoubtedly talk about arming teachers and pupils. Colt will likely develop a backpack-sized, lighter version of its popular killing machine in pink and blue for kids and boys. The MAR-15? (M for mini).
This post is a summary. Read the full one here.
Ray Dalio
3 years ago
The latest “bubble indicator” readings.
As you know, I like to turn my intuition into decision rules (principles) that can be back-tested and automated to create a portfolio of alpha bets. I use one for bubbles. Having seen many bubbles in my 50+ years of investing, I described what makes a bubble and how to identify them in markets—not just stocks.
A bubble market has a high degree of the following:
- High prices compared to traditional values (e.g., by taking the present value of their cash flows for the duration of the asset and comparing it with their interest rates).
- Conditons incompatible with long-term growth (e.g., extrapolating past revenue and earnings growth rates late in the cycle).
- Many new and inexperienced buyers were drawn in by the perceived hot market.
- Broad bullish sentiment.
- Debt financing a large portion of purchases.
- Lots of forward and speculative purchases to profit from price rises (e.g., inventories that are more than needed, contracted forward purchases, etc.).
I use these criteria to assess all markets for bubbles. I have periodically shown you these for stocks and the stock market.
What Was Shown in January Versus Now
I will first describe the picture in words, then show it in charts, and compare it to the last update in January.
As of January, the bubble indicator showed that a) the US equity market was in a moderate bubble, but not an extreme one (ie., 70 percent of way toward the highest bubble, which occurred in the late 1990s and late 1920s), and b) the emerging tech companies (ie. As well, the unprecedented flood of liquidity post-COVID financed other bubbly behavior (e.g. SPACs, IPO boom, big pickup in options activity), making things bubbly. I showed which stocks were in bubbles and created an index of those stocks, which I call “bubble stocks.”
Those bubble stocks have popped. They fell by a third last year, while the S&P 500 remained flat. In light of these and other market developments, it is not necessarily true that now is a good time to buy emerging tech stocks.
The fact that they aren't at a bubble extreme doesn't mean they are safe or that it's a good time to get long. Our metrics still show that US stocks are overvalued. Once popped, bubbles tend to overcorrect to the downside rather than settle at “normal” prices.
The following charts paint the picture. The first shows the US equity market bubble gauge/indicator going back to 1900, currently at the 40% percentile. The charts also zoom in on the gauge in recent years, as well as the late 1920s and late 1990s bubbles (during both of these cases the gauge reached 100 percent ).
The chart below depicts the average bubble gauge for the most bubbly companies in 2020. Those readings are down significantly.
The charts below compare the performance of a basket of emerging tech bubble stocks to the S&P 500. Prices have fallen noticeably, giving up most of their post-COVID gains.
The following charts show the price action of the bubble slice today and in the 1920s and 1990s. These charts show the same market dynamics and two key indicators. These are just two examples of how a lot of debt financing stock ownership coupled with a tightening typically leads to a bubble popping.
Everything driving the bubbles in this market segment is classic—the same drivers that drove the 1920s bubble and the 1990s bubble. For instance, in the last couple months, it was how tightening can act to prick the bubble. Review this case study of the 1920s stock bubble (starting on page 49) from my book Principles for Navigating Big Debt Crises to grasp these dynamics.
The following charts show the components of the US stock market bubble gauge. Since this is a proprietary indicator, I will only show you some of the sub-aggregate readings and some indicators.
Each of these six influences is measured using a number of stats. This is how I approach the stock market. These gauges are combined into aggregate indices by security and then for the market as a whole. The table below shows the current readings of these US equity market indicators. It compares current conditions for US equities to historical conditions. These readings suggest that we’re out of a bubble.
1. How High Are Prices Relatively?
This price gauge for US equities is currently around the 50th percentile.
2. Is price reduction unsustainable?
This measure calculates the earnings growth rate required to outperform bonds. This is calculated by adding up the readings of individual securities. This indicator is currently near the 60th percentile for the overall market, higher than some of our other readings. Profit growth discounted in stocks remains high.
Even more so in the US software sector. Analysts' earnings growth expectations for this sector have slowed, but remain high historically. P/Es have reversed COVID gains but remain high historical.
3. How many new buyers (i.e., non-existing buyers) entered the market?
Expansion of new entrants is often indicative of a bubble. According to historical accounts, this was true in the 1990s equity bubble and the 1929 bubble (though our data for this and other gauges doesn't go back that far). A flood of new retail investors into popular stocks, which by other measures appeared to be in a bubble, pushed this gauge above the 90% mark in 2020. The pace of retail activity in the markets has recently slowed to pre-COVID levels.
4. How Broadly Bullish Is Sentiment?
The more people who have invested, the less resources they have to keep investing, and the more likely they are to sell. Market sentiment is now significantly negative.
5. Are Purchases Being Financed by High Leverage?
Leveraged purchases weaken the buying foundation and expose it to forced selling in a downturn. The leverage gauge, which considers option positions as a form of leverage, is now around the 50% mark.
6. To What Extent Have Buyers Made Exceptionally Extended Forward Purchases?
Looking at future purchases can help assess whether expectations have become overly optimistic. This indicator is particularly useful in commodity and real estate markets, where forward purchases are most obvious. In the equity markets, I look at indicators like capital expenditure, or how much businesses (and governments) invest in infrastructure, factories, etc. It reflects whether businesses are projecting future demand growth. Like other gauges, this one is at the 40th percentile.
What one does with it is a tactical choice. While the reversal has been significant, future earnings discounting remains high historically. In either case, bubbles tend to overcorrect (sell off more than the fundamentals suggest) rather than simply deflate. But I wanted to share these updated readings with you in light of recent market activity.
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