While we played checkers, we thought billionaires played 3D chess. They're playing the same game on a fancier board.

Every medium has nuances and norms. Texting is authentic and casual. A smaller circle has access, creating intimacy and immediacy. Most people read all their texts, but not all their email and mail. Many of us no longer listen to our voicemails, and calling your kids ages you.

Live interviews and testimony under oath inspire real moments, rare in a world where communications departments sanitize everything powerful people say. When (some of) Elon's text messages became public in Twitter v. Musk, we got a glimpse into tech power. It's bowels.

These texts illuminate the tech community's upper caste.

Checkers, Not Chess

Elon texts with Larry Ellison, Joe Rogan, Sam Bankman-Fried, Satya Nadella, and Jack Dorsey. They reveal astounding logic, prose, and discourse. The world's richest man and his followers are unsophisticated, obtuse, and petty. Possibly. While we played checkers, we thought billionaires played 3D chess. They're playing the same game on a fancier board.

They fumble with their computers.

They lean on others to get jobs for their kids (no surprise).

No matter how rich, they always could use more (money).

Differences A social hierarchy exists. Among this circle, the currency of deference is... currency. Money increases sycophantry. Oculus and Elon's "friends'" texts induce nausea.

Autocorrect frustrates everyone.

Elon doesn't stand out to me in these texts; he comes off mostly OK in my view. It’s the people around him. It seems our idolatry of innovators has infected the uber-wealthy, giving them an uncontrollable urge to kill the cool kid for a seat at his cafeteria table. "I'd grenade for you." If someone says this and they're not fighting you, they're a fan, not a friend.

Many powerful people are undone by their fake friends. Facilitators, not well-wishers. When Elon-Twitter started, I wrote about power. Unchecked power is intoxicating. This is a scientific fact, not a thesis. Power causes us to downplay risk, magnify rewards, and act on instincts more quickly. You lose self-control and must rely on others.

You'd hope the world's richest person has advisers who push back when necessary (i.e., not yes men). Elon's reckless, childish behavior and these texts show there is no truth-teller. I found just one pushback in the 151-page document. It came from Twitter CEO Parag Agrawal, who, in response to Elon’s unhelpful “Is Twitter dying?” tweet, let Elon know what he thought: It was unhelpful. Elon’s response? A childish, terse insult.

Scale

The texts are mostly unremarkable. There are some, however, that do remind us the (super-)rich are different. Specifically, the discussions of possible equity investments from crypto-billionaire Sam Bankman-Fried (“Does he have huge amounts of money?”) and this exchange with Larry Ellison:

Ellison, who co-founded $175 billion Oracle, is wealthy. Less clear is whether he can text a billion dollars. Who hasn't been texted $1 billion? Ellison offered 8,000 times the median American's net worth, enough to buy 3,000 Ferraris or the Chicago Blackhawks. It's a bedrock principle of capitalism to have incredibly successful people who are exponentially wealthier than the rest of us. It creates an incentive structure that inspires productivity and prosperity. When people offer billions over text to help a billionaire's vanity project in a country where 1 in 5 children are food insecure, isn't America messed up?

Elon's Morgan Stanley banker, Michael Grimes, tells him that Web3 ventures investor Bankman-Fried can invest $5 billion in the deal: “could do $5bn if everything vision lock... Believes in your mission." The message bothers Elon. In Elon's world, $5 billion doesn't warrant a worded response. $5 billion is more than many small nations' GDP, twice the SEC budget, and five times the NRC budget.

If income inequality worries you after reading this, trust your gut.

Billionaires aren't like the rich.

As an entrepreneur, academic, and investor, I've met modest-income people, rich people, and billionaires. Rich people seem different to me. They're smarter and harder working than most Americans. Monty Burns from The Simpsons is a cartoon about rich people. Rich people have character and know how to make friends. Success requires supporters.

I've never noticed a talent or intelligence gap between wealthy and ultra-wealthy people. Conflating talent and luck infects the tech elite. Timing is more important than incremental intelligence when going from millions to hundreds of millions or billions. Proof? Elon's texting. Any man who electrifies the auto industry and lands two rockets on barges is a genius. His mega-billions come from a well-regulated capital market, enforceable contracts, thousands of workers, and billions of dollars in government subsidies, including a $465 million DOE loan that allowed Tesla to produce the Model S. So, is Mr. Musk a genius or an impressive man in a unique time and place?

The Point

Elon's texts taught us more? He can't "fix" Twitter. For two weeks in April, he was all in on blockchain Twitter, brainstorming Dogecoin payments for tweets with his brother — i.e., paid speech — while telling Twitter's board he was going to make a hostile tender offer. Kimbal approved. By May, he was over crypto and "laborious blockchain debates." (Mood.)

Elon asked the Twitter CEO for "an update from the Twitter engineering team" No record shows if he got the meeting. It doesn't "fix" Twitter either. And this is Elon's problem. He's a grown-up child with all the toys and no boundaries. His yes-men encourage his most facile thoughts, and shitposts and errant behavior diminish his genius and ours.

Post-Apocalyptic

The universe's titans have a sense of humor.

Every day, we must ask: Who keeps me real? Who will disagree with me? Who will save me from my psychosis, which has brought down so many successful people? Elon Musk doesn't need anyone to jump on a grenade for him; he needs to stop throwing them because one will explode in his hand.

Economic mutual destruction.

Multibillion-dollar corporations never bothered with an independent audit, and they all lied about their balance sheets.

It's easy to forget that the Big Four accounting firms are lousy fraud enablers. Just because they sign off on your books doesn't mean you're not a hoax waiting to erupt.

This is *crazy* Capitalism depends on independent auditors. Rich folks need to know their financial advisers aren't lying. Rich folks usually succeed.

No accounting. EY, KPMG, PWC, and Deloitte make more money consulting firms than signing off on their accounts.

The Big Four sign off on phony books because failing to make friends with unscrupulous corporations may cost them consulting contracts.

The Big Four are the only firms big enough to oversee bankruptcy when they sign off on fraudulent books, as they did for Carillion in 2018. All four profited from Carillion's bankruptcy.

The Big Four are corrupt without any consequences for misconduct. Who can forget when KPMG's top management was fined millions for helping auditors cheat on ethics exams?

Consulting and auditing conflict. Consultants help a firm cover its evil activities, such as tax fraud or wage theft, whereas auditors add clarity to a company's finances. The Big Four make more money from cooking books than from uncooking them, thus they are constantly embroiled in scandals.

If a major scandal breaks, it may bring down the entire sector and substantial parts of the economy. Jim Peterson explains system risk for The Dig.

The Big Four are voluntary private partnerships where accountants invest their time, reputations, and money. If a controversy threatens the business, partners who depart may avoid scandal and financial disaster.

When disaster looms, each partner should bolt for the door, even if a disciplined stay-and-hold posture could weather the storm. This happened to Arthur Andersen during Enron's collapse, and a 2006 EU report recognized the risk to other corporations.

Each partner at a huge firm knows how much dirty laundry they've buried in the company's garden, and they have well-founded suspicions about what other partners have buried, too. When someone digs, everyone runs.

If a firm confronts substantial litigation damages or enforcement penalties, it could trigger the collapse of one of the Big Four. That would be bad news for the firm's clients, who would have trouble finding another big auditor.

Most of the world's auditing capacity is concentrated in four enormous, brittle, opaque, compromised organizations. If one of them goes bankrupt, the other three won't be able to take on its clients.

Peterson: Another collapse would strand many of the world's large public businesses, leaving them unable to obtain audit views for their securities listings and regulatory compliance.

Count Down: The Past, Present, and Uncertain Future of the Big Four Accounting Firms is in its second edition.

https://www.emerald.com/insight/publication/doi/10.1108/9781787147003

AI images are like funhouse mirrors.

Google's AI Blog introduced the puppy-slug in the summer of 2015.

Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.

DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.

Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!

Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.

When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.

DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.

Some of these images look scary because the models don't "know" anything, at least not in the way we do.

These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.

You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.

Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.

Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.

This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.

The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":

As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.

Niches are rich, as the adage goes.

Micro SaaS requires a great micro-niche; otherwise, it's merely plain old SaaS with a large audience.

Instead of targeting broad markets with few identifying qualities, specialise down to a micro-niche. How would you target these users?

Better go tiny. You'll locate and engage new consumers more readily and serve them better with a customized solution.

Imagine you're a real estate lawyer looking for a case management solution. Because it's so specific to you, you'd be lured to this link:

instead of below:

Next, locate mini SaaS niches that could work for you. You're not yet looking at the problems/solutions in these areas, merely shortlisting them.

The market should be growing, not shrinking

We shouldn't design apps for a declining niche. We intend to target stable or growing niches for the next 5 to 10 years.

If it's a developing market, you may be able to claim a stake early. You must balance this strategy with safer, longer-established niches (accountancy, law, health, etc).

First Micro SaaS apps I designed were for Merch By Amazon creators, a burgeoning niche. I found this niche when searching for passive income.

Graphic designers and entrepreneurs post their art to Amazon to sell on clothes. When Amazon sells their design, they get a royalty. Since 2015, this platform and specialty have grown dramatically.

Amazon doesn't publicize the amount of creators on the platform, but it's possible to approximate by looking at Facebook groups, Reddit channels, etc.

I could see the community growing week by week, with new members joining. Merch was an up-and-coming niche, and designers made money when their designs sold. All I had to do was create tools that let designers focus on making bestselling designs.

Look at the Google Trends graph below to see how this niche has evolved and when I released my apps and resigned my job.

Are the users able to afford the tools?

Who's your average user? Consumer or business? Is your solution budgeted?

If they're students, you'll struggle to convince them to subscribe to your study-system app (ahead of video games and beer).

Let's imagine you designed a Shopify plugin that emails customers when a product is restocked. If your plugin just needs 5 product sales a month to justify its cost, everyone wins (just be mindful that one day Shopify could potentially re-create your plugins functionality within its core offering making your app redundant ).

Do specialized users buy tools? If so, that's comforting. If not, you'd better have a compelling value proposition for your end customer if you're the first.

This should include how much time or money your program can save or make the user.

Are you able to understand the Micro SaaS market?

Ideally, you're already familiar about the industry/niche. Maybe you're fixing a challenge from your day job or freelance work.

If not, evaluate how long it would take to learn the niche's users. Health & Fitness is easier to relate to and understand than hedge fund derivatives trading.

Competing in these complex (and profitable) fields might offer you an edge.

B2C, B2M, or B2B?

Consider your user base's demographics. Will you target businesses, consumers, or both? Let's examine the different consumer types:

• B2B refers to business-to-business transactions where customers are other businesses. UpVoty, Plutio, Slingshot, Salesforce, Atlassian, and Hubspot are a few examples of SaaS, ranging from Micro SaaS to SaaS.

• Business to Consumer (B2C), in which your clients are people who buy things. For instance, Duolingo, Canva, and Nomad List.

• For instance, my tool KDP Wizard has a mixed user base of publishing enterprises and also entrepreneurial consumers selling low-content books on Amazon. This is a case of business to many (B2M), where your users are a mixture of businesses and consumers. There is a large SaaS called Dropbox that offers both personal and business plans.

Targeting a B2B vs. B2C niche is very different. The sales cycle differs.

• A B2B sales staff must make cold calls to potential clients' companies. Long sales, legal, and contractual conversations are typically required for each business to get the go-ahead. The cost of obtaining a new customer is substantially more than it is for B2C, despite the fact that the recurring fees are significantly higher.

• Since there is typically only one individual making the purchasing decision, B2C signups are virtually always self-service with reduced recurring fees. Since there is typically no outbound sales staff in B2C, acquisition costs are significantly lower than in B2B.

User Characteristics for B2B vs. B2C

Consider where your niche's users congregate if you don't already have a presence there.

B2B users frequent LinkedIn and Twitter. B2C users are on Facebook/Instagram/Reddit/Twitter, etc.

Churn is higher in B2C because consumers haven't gone through all the hoops of a B2B sale. Consumers are more unpredictable than businesses since they let their bank cards exceed limitations or don't update them when they expire.

With a B2B solution, there's a contractual arrangement and the firm will pay the subscription as long as they need it.

Depending on how you feel about the above (sales team vs. income vs. churn vs. targeting), you'll know which niches to pursue.

You ought to respect potential customers.

Would you hang out with customers?

You'll connect with users at conferences (in-person or virtual), webinars, seminars, screenshares, Facebook groups, emails, support calls, support tickets, etc.

If talking to a niche's user base makes you shudder, you're in for a tough road. Whether they're demanding or dull, avoid them if possible.

Merch users are mostly graphic designers, side hustlers, and entrepreneurs. These laid-back users embrace technologies that assist develop their Merch business.

I discovered there was only one annual conference for this specialty, held in Seattle, USA. I decided to organize a conference for UK/European Merch designers, despite never having done so before.

Hosting a conference for over 80 people was stressful, and it turned out to be much bigger than expected, with attendees from the US, Europe, and the UK.

I met many specialized users, built relationships, gained trust, and picked their brains in person. Many of the attendees were already Merch Wizard users, so hearing their feedback and ideas for future features was invaluable.

focused and specific

Instead of building for a generic, hard-to-reach market, target a specific group.

I liken it to fishing in a little, hidden pond. This small pond has only one species of fish, so you learn what bait it likes. Contrast that with trawling for hours to catch as many fish as possible, even if some aren't what you want.

In the case management scenario, it's difficult to target leads because several niches could use the app. Where do your potential customers hang out? Your generic solution: No.

It's easier to join a community of Real Estate Lawyers and see if your software can answer their pain points.

My Success with Micro SaaS

In my case, my Micro SaaS apps have been my chrome extensions. Since I launched them, they've earned me an average $10k MRR, allowing me to quit my lousy full-time job years ago.

I sold my apps after scaling them for a life-changing lump amount. Since then, I've helped unfulfilled software developers escape the 9-5 through Micro SaaS.

Whether it's a profitable side hustle or a liferaft to quit their job and become their own Micro SaaS boss.

Having built my apps to the point where I could quit my job, then scaled and sold them, I feel I can share my skills with software developers worldwide.

Read my free guide on self-funded SaaS to discover more about Micro SaaS, or download your own copy. 12 chapters cover everything from Idea to Exit.

Watch my YouTube video to learn how to construct a Micro SaaS app in 10 steps.