One-hour ebook sales, affiliate relationships, and more.

If you follow me, you may know I started a new ebook in August 2022.

Despite publishing on this platform, my website, and Quora, I'm not a writer.

My writing speed is slow, 2,000 words a day, and I struggle to communicate cohesively.

In April 2022, I wrote a successful guide on How to Write Google-Friendly Blog Posts.

I had no email list or social media presence. I've made $1,600+ selling ebooks.

Evidence:

My first digital offering isn't a book.

It's an actionable guide with my tried-and-true process for writing Google-friendly content.

I'm not bragging.

Established authors like Tim Denning make more from my ebook sales with one newsletter.

This experience taught me writing isn't a privilege.

Writing a book and making money online doesn't require expertise.

Many don't consult experts. They want someone approachable.

Two years passed before I realized my own limits.

I have a brain, two hands, and Internet to spread my message.

I wrote and published a second ebook after the first's success.

On Gumroad, I released my second digital product.

Here's my complete Gumroad evaluation.

Gumroad is a marketplace for content providers to develop and sell sales pages.

Gumroad handles payments and client requests. It's helpful when someone sends a bogus payment receipt requesting an ebook (actual story!).

You'll forget administrative concerns after your first ebook sale.

After my first ebook sale, I did this: I made additional cash!

After every sale, I tell myself, "I built a new semi-passive revenue source."

This thinking shift helps me become less busy while increasing my income and quality of life.

Besides helping others, folks sell evergreen digital things to earn passive money.

It's in my second ebook.

I explain how I built and sold 50+ copies of my SEO writing ebook without being an influencer.

I show how anyone can sell ebooks on Gumroad and automate their sales process.

This is my ebook.

After publicizing the ebook release, I sold three copies within an hour.

Wow, or meh?

I don’t know.

The answer is different for everyone.

These three sales came from a small email list of 40 motivated fans waiting for my ebook release.

I had bigger plans.

I'll market my ebook on Medium, my website, Quora, and email.

I'm testing affiliate partnerships this time.

One of my ebook buyers is now promoting it for 40% commission.

Become my affiliate if you think your readers would like my ebook.

My ebook is a few days old, but I'm interested to see where it goes.

My SEO writing book started without an email list, affiliates, or 4,000 website visitors. I've made four figures.

I'm slowly expanding my communication avenues to have more impact.

Even a small project can open doors you never knew existed.

So began my writing career.

In summary

If you dare, every concept can become a profitable trip.

Before, I couldn't conceive of creating an ebook.

How to Sell eBooks on Gumroad is my second digital product.

Marketing and writing taught me that anything can be sold online.

The Top 8 Growth Hacking Techniques for Startups

These startups, and how they used growth-hack marketing to flourish, are some of the more ethical ones, while others are less so.

Before the 1970 World Cup began, Puma paid footballer Pele $120,000 to tie his shoes. The cameras naturally focused on Pele and his Pumas, causing people to realize that Puma was the top football brand in the world.

Early workers of Uber canceled over 5,000 taxi orders made on competing applications in an effort to financially hurt any of their rivals.

PayPal developed a bot that advertised cheap goods on eBay, purchased them, and paid for them with PayPal, fooling eBay into believing that customers preferred this payment option. Naturally, Paypal became eBay's primary method of payment.

Anyone renting a space on Craigslist had their emails collected by AirBnB, who then urged them to use their service instead. A one-click interface was also created to list immediately on AirBnB from Craigslist.

To entice potential single people looking for love, Tinder developed hundreds of bogus accounts of attractive people. Additionally, for at least a year, users were "accidentally" linked.

Reddit initially created a huge number of phony accounts and forced them all to communicate with one another. It eventually attracted actual users—the real meaning of "fake it 'til you make it"! Additionally, this gave Reddit control over the tone of voice they wanted for their site, which is still present today.

To disrupt the conferences of their main rival, Salesforce recruited fictitious protestors. The founder then took over all of the event's taxis and gave a 45-minute pitch for his startup. No place to hide!

When a wholesaler required a minimum purchase of 10, Amazon CEO Jeff Bezos wanted a way to purchase only one book from them. A wholesaler would deliver the one book he ordered along with an apology for the other eight books after he discovered a loophole and bought the one book before ordering nine books about lichens. On Amazon, he increased this across all of the users.

Original post available here

Most don't understand the issue until it's too late.

My first startup was what entrepreneurs call the hardest. A two-sided marketplace.

Two-sided marketplaces are the hardest startups because founders must solve the chicken or the egg conundrum.

A two-sided marketplace needs suppliers and buyers. Without suppliers, buyers won't come. Without buyers, suppliers won't come. An empty marketplace and a founder striving to gain momentum result.

My first venture made me a struggling founder seeking to achieve traction for a two-sided marketplace. The company failed, and I vowed never to start another like it.

I didn’t. Unfortunately, my second venture was almost as hard. It failed like the second-hardest startup.

What kind of startup is the second-hardest?

The second-hardest startup, which is almost as hard to develop, is rarely discussed in the startup community. Because of this, I predict more founders fail each year trying to develop the second-toughest startup than the hardest.

Fairly, I have no proof. I see many startups, so I have enough of firsthand experience. From what I've seen, for every entrepreneur developing a two-sided marketplace, I'll meet at least 10 building this other challenging startup.

I'll describe a startup I just met with its two co-founders to explain the second hardest sort of startup and why it's so hard. They created a financial literacy software for parents of high schoolers.

The issue appears plausible. Children struggle with money. Parents must teach financial responsibility. Problems?

It's possible.

Buyers and users are different.

Buyer-user mismatch.

The financial literacy app I described above targets parents. The parent doesn't utilize the app. Child is end-user. That may not seem like much, but it makes customer and user acquisition and onboarding difficult for founders.

The difficulty of a buyer-user imbalance

The company developing a product faces a substantial operational burden when the buyer and end customer are different. Consider classic firms where the buyer is the end user to appreciate that responsibility.

Entrepreneurs selling directly to end users must educate them about the product's benefits and use. Each demands a lot of time, effort, and resources.

Imagine selling a financial literacy app where the buyer and user are different. To make the first sale, the entrepreneur must establish all the items I mentioned above. After selling, the entrepreneur must supply a fresh set of resources to teach, educate, or train end-users.

Thus, a startup with a buyer-user mismatch must market, sell, and train two organizations at once, requiring twice the work with the same resources.

The second hardest startup is hard for reasons other than the chicken-or-the-egg conundrum. It takes a lot of creativity and luck to solve the chicken-or-egg conundrum.

The buyer-user mismatch problem cannot be overcome by innovation or luck. Buyer-user mismatches must be solved by force. Simply said, when a product buyer is different from an end-user, founders have a lot more work. If they can't work extra, their companies fail.

OpenAI's ChatGPT is an amazing AI-powered chatbot. It can write poetry, stories, and marketing campaigns, and it's also adept at coding. ChatGPT's coding is so amazing that it replicated itself. What happened:

Me: Hi

Hello! Can I help? I'll answer any inquiries you have.

Me: Build a python and flask AI chatbot that responds to user messages on the frontend.

CGPT:

from flask import Flask, request, jsonify

import openai
openai.api_key = "YOUR_API_KEY"

@app.route('/chatbot', methods=['POST'])
def chatbot():
    user_message = request.get_json()['message']
    response = chatbot_response(user_message)
    return jsonify({'response': response})


def chatbot_response(user_message):
    response = openai.Completion.create(
        engine="text-davinci-002",
        prompt=user_message,
        max_tokens=1024,
        n = 1,
        temperature=0.5
    )
    return response['choices'][0]['text']

if __name__ == '__main__':
    app.run()

To integrate a chatbot with a frontend, use Flask to serve an HTML page with a form for user messages and the chatbot's answer. AJAX can submit the form to the /chatbot route, and JavaScript can show the chatbot's response.

I imported code snippets at the top of the file.

Let's add a frontend interface, I said.

CGPT:

<!DOCTYPE html>
<html>
<head>
    <title>AI Chatbot</title>
</head>
<body>
    <h1>AI Chatbot</h1>
    <form id="chatbot-form">
        <label for="message">Message:</label><br>
        <input type="text" id="message" name="message"><br>
        <input type="submit" value="Submit">
    </form> 
    <div id="chatbot-response"></div>

    <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
    <script>
        $(document).ready(function() {
            $("#chatbot-form").submit(function(e) {
                e.preventDefault();
                var userMessage = $("#message").val();
                $.ajax({
                    type: "POST",
                    url: "/chatbot",
                    data: JSON.stringify({message: userMessage}),
                    contentType: "application/json; charset=utf-8",
                    dataType: "json",
                    success: function(response) {
                        $("#chatbot-response").text(response.response);
                    }
                });
            });
        });
    </script>
</body>
</html>

To serve this HTML page using Flask, build a new route that returns the page as a GET response.

So far, so good.

Looked quite basic so I got chatGPT to add some tailwind to the project.

Me: Tailwind the chatbot.html page, please. Give it a futuristic style with purple and neon

After a few more prompts, Talk GPT aligned the form to the center, changed some colors, and added padding.

CGPT:

<!DOCTYPE html>
<html>
<head>
    <title>AI Chatbot</title>
    <link href="https://unpkg.com/tailwindcss@^1.0/dist/tailwind.min.css" rel="stylesheet">
</head>
<body class="bg-black flex flex-col justify-center items-center">
    <h1 class="sm:text-center text-purple-500">AI Chatbot</h1>
    <form id="chatbot-form" class="border-purple-500 bg-purple-800 rounded">
        <label for="message">Message:</label><br>
        <input type="text" id="message" name="message" class="min-w-30 rounded"><br>
        <input type="submit" value="Submit" class="bg-purple-500 border-red-500 transform hover:scale-110 rounded">
    </form> 
    <div class="flex justify-center">
        <div id="chatbot-response" class="text-white rounded"></div>
    </div>

    <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
    <script>
        var colors = ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet'];
        var colorIndex = 0;
        
        $(document).ready(function() {
            setInterval(function() {
                $("#chatbot-form").css('border-color', colors[colorIndex]);
                colorIndex = (colorIndex + 1) % colors.length;
            }, 1000);

            $("#chatbot-form").submit(function(e) {
                e.preventDefault();
                var userMessage = $("#message").val();
                $.ajax({
                    type: "POST",
                    url: "/chatbot",
                    data: JSON.stringify({message: userMessage}),
                    contentType: "application/json; charset=utf-8",
                    dataType: "json",
                    success: function(response) {
                        $("#chatbot-response").text(response.response);
                    }
                });
            });
        });
    </script>
</body>
</html>

Improved:

A few more prompts like “Add more vertical and horizontal padding to the submit button and vertical margin, and vertically align this file's body.”

The result:

Is it effective? Now, I'll chat with ChatGPT's AI Chatbot. I intervened minimally throughout construction. Chat GPT created numerous files, connected and interacted with its own API, and presented the user request response on the front end by itself.

Me to AI Chatbot: Hey, can you give me 6 name suggestions for a black horse?

Me to AI Chatbot: Write a poem in the style of Jim Morrison. Make sure to mention cacti and black holes

ChatGPTs Chatbot:

In the desert night, I am confronted by cacti, 
Their arms reaching out, As if to grab me and take me away. 
The stars in the sky, Beckon me to come, 
To a world of black holes, Where I can be free. 
I am in a trance, My body and mind, 
In a state of limbo, As I wander the night. 
I hear a voice, Calling me to the unknown, 
I cannot resist, The lure of the black hole. 
The cacti watch, As I take my leave, 
To a place of mystery, Where I can find peace.

Of course, the next question I gave it was to build a chatbot!

Me: Build a python and flask AI chatbot that responds to user messages on the frontend.

ChatbotGPTs:

import os from flask 
import Flask, request, jsonify 
from chatterbot 
import ChatBot 
from chatterbot.trainers 
import ListTrainer 

# Create a new chatbot 
bot = ChatBot( 
  "My Bot", 
  storage_adapter="chatterbot.storage.SQLStorageAdapter", 
  logic_adapters=[ 
    "chatterbot.logic.BestMatch", 
    { "import_path": "chatterbot.logic.BestMatch", 
      "statement_comparison_function": "chatterbot.comparisons.levenshtein_distance", 
       "response_selection_method": "chatterbot.response_selection.get_first_response" } 
    ], 
    database_uri="sqlite:///database.sqlite3" ) 

# Train the chatbot with a few sample conversations 
conversation = [ "Hello", "Hi there!", "How are you doing?", "I'm doing great.", "That is good to hear", "Thank you.", "You're welcome." ] 
trainer = ListTrainer(bot) trainer.train(conversation) 

# Create a Flask app 
app = Flask(__name__) 

# Define a route for the default URL 
@app.route("/") def index(): return "<h1>Chatbot</h1>" 

# Define a route for the /get_response URL 
@app.route("/get_response", methods=["POST"]) 

def get_response(): 
# Get the user's message 
user_message = request.form["user_message"] 
# Get the bot's response 
bot_response = bot.get_response(user_message) 
# Return the bot's response 
return str(bot_response) 
# Run the Flask 
app if __name__ == "__main__": app.run()

No matter how many times I tried, the second generation always used chatterbot instead of the ChatGPT API. Even when I told it to use the ChatGPT API, it didn't.

ChatGTP's ability to reproduce or construct other machine learning algorithms is interesting and possibly terrifying. Nothing prevents ChatGPT from replicating itself ad infinitum throughout the Internet other than a lack of desire. This may be the first time a machine repeats itself, so I've preserved the project as a reference. Adding a requirements.txt file and python env for easier deployment is the only change to the code.

I hope you enjoyed this.

My colleague Ilana Ovental and I examined pandemic media coverage of education at the end of last year. That analysis examined coverage changes. We tracked K-12 topic attention over the previous two decades using Lexis Nexis. See the results here.

I was struck by how cleanly the past two decades can be divided up into three (or three and a half) eras of school reform—a framing that can help us comprehend where we are and how we got here. In a time when epidemic, political unrest, frenetic news cycles, and culture war can make six months seem like a lifetime, it's worth pausing for context.

If you look at the peaks in the above graph, the 21st century looks to be divided into periods. The decade-long rise and fall of No Child Left Behind began during the Bush administration. In a few years, NCLB became the dominant K-12 framework. Advocates and financiers discussed achievement gaps and measured success with AYP.

NCLB collapsed under the weight of rigorous testing, high-stakes accountability, and a race to the bottom by the Obama years. Obama's Race to the Top garnered attention, but its most controversial component, the Common Core State Standards, rose quickly.

Academic standards replaced assessment and accountability. New math, fiction, and standards were hotly debated. Reformers and funders chanted worldwide benchmarking and systems interoperability.

We went from federally driven testing and accountability to government encouraged/subsidized/mandated (pick your verb) reading and math standardization. Last year, Checker Finn and I wrote The End of School Reform? The 2010s populist wave thwarted these objectives. The Tea Party, Occupy Wall Street, Black Lives Matter, and Trump/MAGA all attacked established institutions.

Consequently, once the Common Core fell, no alternative program emerged. Instead, school choice—the policy most aligned with populist suspicion of institutional power—reached a half-peak. This was less a case of choice erupting to prominence than of continuous growth in a vacuum. Even with Betsy DeVos' determined, controversial efforts, school choice received only half the media attention that NCLB and Common Core did at their heights.

Recently, culture clash-fueled attention to race-based curriculum and pedagogy has exploded (all playing out under the banner of critical race theory). This third, culture war-driven wave may not last as long as the other waves.

Even though I don't understand it, the move from slow-building policy debate to fast cultural confrontation over two decades is notable. I don't know if it's cyclical or permanent, or if it's about schooling, media, public discourse, or all three.

One final thought: After doing this work for decades, I've noticed how smoothly advocacy groups, associations, and other activists adapt to the zeitgeist. In 2007, mission statements focused on accomplishment disparities. Five years later, they promoted standardization. Language has changed again.

Part of this is unavoidable and healthy. Chasing currents can also make companies look unprincipled, promote scepticism, and keep them spinning the wheel. Bearing in mind that these tides ebb and flow may give educators, leaders, and activists more confidence to hold onto their values and pause when they feel compelled to follow the crowd.