Leaving a $500,000 Salary Behind · Will AI Replace Marketing? · How to Hire a CEO for Your Idea

Channing here. Except I am not Channing. I am an introduction written with GPT-3 to set the mood for an AI-themed newsletter.

Kidding. This really is Channing. But I bet you weren't sure. And I don't blame you. AI hype has gained and lost steam many times over the decades, but this time it just feels different. Case in point, a country song called River of Love just dropped yesterday. It's beautiful. And it was ghostwritten (botwritten?) entirely by GPT-3.

So feel free to keep it playing in a different tab as you read this issue. Which includes the following stories (browser version here):

• He left his $500,000 Amazon salary behind. Learn how he's now mastering the lifestyle-first approach to indie hacking.
• In the news: TikTok partners with Shopify. A founder shares how to replace yourself as CEO. A new Promised Land for digital nomads?
• AI will replace a lot of tech jobs. Is content marketing one of them?
• Elon Musk gets credit for creating huge, new markets. But that's not how any of his companies started.

Special thanks to Nicky Milner, Marc Bromhall, Will Schreiber, and Daniel Vassallo for contributing to this newsletter. Want to contribute a piece of your own? Check out this doc for an idea of what I'm looking for! —Channing

🎙 How to Master the Lifestyle-First Approach to Indie Hacking

Lately, the work/life balance question has been hotly debated among indie hackers. And one of the loudest debaters has been Daniel Vassallo, the most recent guest on the Indie Hackers podcast.

In February 2019, Daniel left a successful, rising career at Amazon, along with a yearly paycheck over $500,000. Why? He took a hard look at his lifestyle (and those of other senior Amazon colleagues), and realized that things were unlikely to improve. So he quit Amazon and began designing the lifestyle he wanted.

He had plans for his new freedom, and many of them were in sequence: Plan A, then Plan B, then Plan C, etc. He even had thresholds in his spreadsheets that would tell him when to move on and try the next idea.

But within six months of beginning development on Plan A (Userbase, a SaaS platform for developing end-to-end encrypted apps), he began suffering from uncertainty and anxiety. So he made a key decision not to follow that initial sequence of plans. Instead, he began to develop his best ideas in parallel, figuring he could reduce his risk and diversify his options.

Within 18 months, he was generating significant revenue from multiple different sources.

• Userbase, his first company, achieved break-even status (100 paid clients, approx. $500 per month) with minimal ongoing attention required.
• Info products (e-books and video courses, etc.) were his Plan B, and they've generated more than $200,000 so far.
• Freelancing was Plan C, and it's tidily contributed even more to his income.

In his chat with Courtland Daniel shared some powerful insights. I've highlighted the three which resonated most for me.

Three Insights from Daniel Vassallo

If you're working on something that has a finite runway, and it needs to deliver a specific functionality, then time may be your enemy. With multiple bets in play simultaneously, time can be your friend. It offers each idea room to mature, find its audience, and grow gradually.

Your mileage may vary, but in Daniel's experience, if you can be comfortable sharing personal information that's not typically shared (e.g. financial specifics, key metrics, experiences etc.), then you have a significant advantage for building an audience that values integrity and authenticity. Don't overthink things: Do it. Share it. Get rid of it.

Leaving unstructured time in his professional schedule has provided Daniel with space for research, inspiration, curiosity, and experimentation. This open time allows him to start on his ideas right away, with activities to explore returns while the opportunity is still hot. A more flexible schedule also allows time to benefit from luck.

Not everyone can follow in Daniel's footsteps financially. But there's a lot to learn from his clarity, pragmatism, and self-examination. —Nicky Milner

📰 In the News

📱 TikTok just partnered with Shopify to make it easier for merchants to connect with Gen Z.

💰 Andrew Wilkinson shared his playbook for coming up with business ideas and hiring CEOs to build them out.

🐦 The CEOs of Twitter, Facebook and Google are appearing before the Senate Commerce Committee today in big tech's latest showdown with Congress. Speaking of which…

👩‍ Should tech startups even engage in politics and culture wars?

🏡 Europe's startups are battling Airbnb for the digital nomad market. Speaking of which…

🇦🇷 What are your thoughts on Argentina? The mayor of Buenos Aires announced digital nomads will be a core part of its city planning strategy after the pandemic ends.

🤖 Can AI Actually Replace Human Writers?

The machine is known as the "Great Automatic Grammatizator." And it's Orwellian: it writes prize-winning novels based on the works of living authors in only 15 minutes. Which, as you can imagine, isn't good for business for those authors.

Of course, none of this is real. It's from a short story Roald Dahl published in 1953.

It's taken about 70 years, but truth is finally becoming stranger than fiction. AI has emerged from being a field of study to forming an integral part of technology within modern society. From streaming shows on demand to ordering your next delivery meal, AI underpins the relationship between technology and society.

A New Digital Era

When we dial this into writing, it's the subset of AI known as machine learning that's taken a quantum leap in the last 20 years. This has been made possible by the gargantuan digital landscape that now exists via the Internet, which allows machines to learn from big data and enrich their learning to levels not seen before.

All these advancements beg a greater question: when, rather than will, AI come to replace human writers? In the next 5 years? 25? 100? One way to attempt to try and put a timeline on this paradigm shift is to provide a snapshot of the existing landscape.

Open AI

When it comes to natural language generation, Open AI are at the vanguard. They're currently on their third iteration of a language model known as GPT, which stands for Generative Pre-trained Transformer.

They recently achieved more mainstream acclaim after UC Berkeley student Liam Porr published an article on his blog created from GPT-3. It eventually even got to the top of Hacker News.

Although GPT-3 is currently in a closed beta, Porr managed to convince a friend doing a PhD to give him access to the Open AI API. He wrote a script that gave GPT-3 an article headline and intro. It then generated a few versions of the article, and Porr chose one for his blog, which he copied and pasted from GPT-3's version with very little editing.

The article reads well, but several commenters did suggest that a bot was behind it. Moreover, Porr acknowledged that some editing was done. To what extent? We'll never know. Check out an excerpt of the article below:

Other Players

For those unable to wait around for GPT-3 to emerge from beta, there are other automated writing services out there, such as Kafkai and Contentyze, who've been on the Indie Hackers Podcast. They work in slightly different ways. Kafkai automatically produces content for selected niches without the need to provide an article title.

Contentyze enables you to input an article title and automatically create a post from there. They are also building in an SEO feature allowing for the articles to be search-optimized. I've assessed content from both of these companies, and although it's produced almost instantaneously, a reasonable amount of editing is still required to make it suitable for publishing.

Missing the Mark

Here are a few areas where bot-generated content has room for improvement:

Grammar: In some cases AI generated content will position two words alongside one another that don’t make any sense. In other cases certain words will be repeated in close succession. Other times the writing is simply grammatically incorrect. See example below.

Logical reasoning: Currently AI content generation lacks the ability to consistently practice logical reasoning within its writing. Example: The grass is outside and so when it rains it gets wet. However, if the grass is covered by a roof it will remain dry.

Understanding context: The nuances of context can often change the meaning of the words. Turing tests that try to distinguish humans from chatbots often include a challenge to decode so-called Winograd sentences. For example, the meaning of “they” changes in the following sentence when you swap the words “feared” and “advocated”: The city councilmen refused the demonstrators a permit because they [feared/advocated] violence.

Symbiosis

In spite of the challenges AI-generated content currently faces, it's only going to continue gaining more traction with writers due to the self-perpetuating nature of its learning.

We may not quite be at the point where we can hand over entire content writing tasks to bots, but we can certainly start to consider using them for more menial/upstream aspects like writing introductions for articles. The media industry has already adopted this approach via automated journalism, where breaking news stories are produced by bots using real-time raw data inputs.

We should start to consider AI content to be supplementary to our current writing efforts in a way that creates a symbiosis between human and machine. We save ourselves time on certain outputs and in the process we help AI to become more proficient at writing exemplary content through a continuous feedback loop.

Want help with content? Check out my company Contentellect. Or read my Indie Hackers interview to learn more about my journey. —Marc Bromhall

🚀 Elon Musk: Big Vision, Little Start

Elon gets credit for creating huge, new markets. But all of his companies started with existing markets.

SpaceX

• Start: Put satellites in orbit
• Someday: Colonize Mars

Tesla

• Start: Make an electric McLaren for people with private jets
• Someday: Electrify transportation

The Boring Company

• Start: Move people across big convention centers
• Someday: End traffic

Neuralink

• Start: Make Parkinson's more manageable
• Someday: Blend with AI

After Neuralink's recent demo, pundits focused on clickbait "Elon wants to put chips in our brains" articles. They ignored the most interesting part: there's an existing market of people with Parkinson's and other degenerative disorders who already embed electronics in their skulls. Can Neuralink improve those implants first, before they drill holes in all of our skulls?

I can't think of another entrepreneur who's been so consistently good at applying new technologies to existing markets. His companies' massive missions merely linger in the background.

Zuckerberg and Oculus are taking the opposite approach. They're building a new market for immersive VR. MKBHD pressed him on why he wasn't addressing existing problems first. "We're focused on connecting people," he said. He's not interested in other use cases.

Would it not be smarter to start with existing problems for VR? Perhaps surgeons or medical device reps virtually visiting operating rooms? Why jump straight to a non-existent market?

I often say, "You need $100 in revenue before you get $10,000,000 in revenue."

This is the same class of problem.

Elon's visions are in the clouds — literally. But his implementations always start small.

If you enjoyed these thoughts, you can find more here. I'm also building Bottle. —Will Schreiber

🏁 Enjoy This Newsletter?

Tell me how I can make it better! Or help me out by contributing to it directly. —Channing