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

There’s a funny part of ‘Steve Jobs’ by Walter Isaacson where Jobs says that Bill Gates was more a copier than an innovator:

“Bill is basically unimaginative and has never invented anything, which is why I think he’s more comfortable now in philanthropy than technology. He just shamelessly ripped off other people’s ideas….He’d be a broader guy if he had dropped acid once or gone off to an ashram when he was younger.”

Gates lacked flavor. Nobody ever got excited about a Microsoft launch, despite their good products. Jobs had the world's best product taste. Apple vs. Microsoft.

A CEO's core job functions are all driven by taste: recruiting, vision, and company culture all require good taste. Depending on the type of company you want to build, know where you stand between Microsoft and Apple.

How can you improve your product judgment? How to acquire taste?

Test and refine

Product development follows two parallel paths: the ‘customer obsession’ path and the ‘taste and iterate’ path.

The customer obsession path involves solving customer problems. Lean Startup frameworks show you what to build at each step.

Taste-and-iterate doesn't involve the customer. You iterate internally and rely on product leaders' taste and judgment.

Creative Selection by Ken Kocienda explains this method. In Creative Selection, demos are iterated and presented to product leaders. Your boss presents to their boss, and so on up to Steve Jobs. If you have good product taste, you can be a panelist.

The iPhone follows this path. Before seeing an iPhone, consumers couldn't want one. Customer obsession wouldn't have gotten you far because iPhone buyers didn't know they wanted one.

In The Hard Thing About Hard Things, Ben Horowitz writes:

“It turns out that is exactly what product strategy is all about — figuring out the right product is the innovator’s job, not the customer’s job. The customer only knows what she thinks she wants based on her experience with the current product. The innovator can take into account everything that’s possible, but often must go against what she knows to be true. As a result, innovation requires a combination of knowledge, skill, and courage.“

One path solves a problem the customer knows they have, and the other doesn't. Instead of asking a person what they want, observe them and give them something they didn't know they needed.

It's much harder. Apple is the world's most valuable company because it's more valuable. It changes industries permanently.

If you want to build superior products, use the iPhone of your industry.

How to Improve Your Taste

I. Work for a company that has taste.

People with the best taste in products, markets, and people are rewarded for building great companies. Tasteful people know quality even when they can't describe it. Taste isn't writable. It's feel-based.

Moving into a community that's already doing what you want to do may be the best way to develop entrepreneurial taste. Most company-building knowledge is tacit.

Joining a company you want to emulate allows you to learn its inner workings. It reveals internal patterns intuitively. Many successful founders come from successful companies.

Consumption determines taste. Excellence will refine you. This is why restauranteurs visit the world's best restaurants and serious painters visit Paris or New York. Joining a company with good taste is beneficial.

2. Possess a wide range of interests

“Edwin Land of Polaroid talked about the intersection of the humanities and science. I like that intersection. There’s something magical about that place… The reason Apple resonates with people is that there’s a deep current of humanity in our innovation. I think great artists and great engineers are similar, in that they both have a desire to express themselves.” — Steve Jobs

I recently discovered Edwin Land. Jobs modeled much of his career after Land's. It makes sense that Apple was inspired by Land.

A Triumph of Genius: Edwin Land, Polaroid, and the Kodak Patent War notes:

“Land was introverted in person, but supremely confident when he came to his ideas… Alongside his scientific passions, lay knowledge of art, music, and literature. He was a cultured person growing even more so as he got older, and his interests filtered into the ethos of Polaroid.”

Founders' philosophies shape companies. Jobs and Land were invested. It showed in the products their companies made. Different. His obsession was spreading Microsoft software worldwide. Microsoft's success is why their products are bland and boring.

Experience is important. It's probably why startups are built by generalists and scaled by specialists.

Jobs combined design, typography, storytelling, and product taste at Apple. Some of the best original Mac developers were poets and musicians. Edwin Land liked broad-minded people, according to his biography. Physicist-musicians or physicist-photographers.

Da Vinci was a master of art, engineering, architecture, anatomy, and more. He wrote and drew at the same desk. His genius is remembered centuries after his death. Da Vinci's statue would stand at the intersection of humanities and science.

We find incredibly creative people here. Superhumans. Designers, creators, and world-improvers. These are the people we need to navigate technology and lead world-changing companies. Generalists lead.

SaaS spending is 40/40/20. 40% of operating expenses should be R&D, 40% sales and marketing, and 20% G&A. We wanted to see the statistics behind the rules of thumb. Since October 2017, 73 SaaS startups have gone public. Perhaps the rule of thumb should be 30/50/20. The data is below.

30/50/20. R&D accounts for 26% of opex, sales and marketing 48%, and G&A 22%. We think R&D/S&M/G&A should be 30/50/20.

There are outliers. There are exceptions to rules of thumb. Dropbox spent 45% on R&D whereas Zoom spent 13%. Zoom spent 73% on S&M, Dropbox 37%, and Bill.com 28%. Snowflake spent 130% of revenue on S&M, while their EBITDA margin is -192%.

G&A shouldn't stand out. Minimize G&A spending. Priorities should be product development and sales. Cloudflare, Sendgrid, Snowflake, and Palantir spend 36%, 34%, 37%, and 43% on G&A.

Another myth is that COGS is 20% of revenue. Median and averages are 29%.

Where is the profitability? Data-driven operating income calculations were simplified (Revenue COGS R&D S&M G&A). 20 of 73 IPO businesses reported operational income. Median and average operating income margins are -21% and -27%.

As long as you're growing fast, have outstanding retention, and marquee clients, you can burn cash since recurring income that doesn't churn is a valuable annuity.

The data was compelling overall. 30/50/20 is the new 40/40/20 for more established SaaS enterprises, unprofitability is alright as long as your business is expanding, and COGS can be somewhat more than 20% of revenue.

I'm trying to understand why Bitcoin NFTs aren't ready.

Ordinals, a new Bitcoin protocol, has been controversial. NFTs can be added to Bitcoin transactions using the protocol. They are not tokens or fungible. Bitcoin NFTs are transaction metadata. Yes. They're not owned.

In January, the Ordinals protocol allowed data like photos to be directly encoded onto sats, the smallest units of Bitcoin worth 0.00000001 BTC, on the Bitcoin blockchain. Ordinals does not need a sidechain or token like other techniques. The Ordinals protocol has encoded JPEG photos, digital art, new profile picture (PFP) projects, and even 1993 DOOM onto the Bitcoin network.

Ordinals inscriptions are permanent digital artifacts preserved on the Bitcoin blockchain. It differs from Ethereum, Solana, and Stacks NFT technologies that allow smart contract creators to change information. Ordinals store the whole image or content on the blockchain, not just a link to an external server, unlike centralized databases, which can change the linked image, description, category, or contract identifier.

So far, more than 50,000 ordinals have been produced on the Bitcoin blockchain, and some of them have already been sold for astronomical amounts. The Ethereum-based CryptoPunks NFT collection spawned Ordinal Punk. Inscription 620 sold for 9.5 BTC, or $218,000, the most.

Segwit and Taproot, two important Bitcoin blockchain updates, enabled this. These protocols store transaction metadata, unlike Ethereum, where the NFT is the token. Bitcoin's NFT is a sat's transaction details.

What effects do ordinary values and NFTs have on the Bitcoin blockchain?

Ordinals will likely have long-term effects on the Bitcoin Ecosystem since they store, transact, and compute more data.

Charges Ordinals introduce scalability challenges. The Bitcoin network has limited transaction throughput and increased fees during peak demand. NFTs could make network transactions harder and more expensive. Ordinals currently occupy over 50% of block space, according to Glassnode.

One of the protocols that supported Ordinals Taproot has also seen a huge uptick:

Taproot use increases block size and transaction costs.

This could cause network congestion but also support more L2s with Ordinals-specific use cases. Dune info here.

Storage Needs The Bitcoin blockchain would need to store more data to store NFT data directly. Since ordinals were introduced, blocksize has tripled from 0.7mb to over 2.2mb, which could increase storage costs and make it harder for nodes to join the network.

Use Case Diversity On the other hand, NFTs on the Bitcoin blockchain could broaden Bitcoin's use cases beyond storage and payment. This could expand Bitcoin's user base. This is two-sided. Bitcoin was designed to be trustless, decentralized, peer-to-peer money.

Chain to permanently store NFTs as ordinals will change everything.

Popularity rise This new use case will boost Bitcoin appeal, according to some. This argument fails since Bitcoin is the most popular cryptocurrency. Popularity doesn't require a new use case. Cryptocurrency adoption boosts Bitcoin. It need not compete with Ethereum or provide extra benefits to crypto investors. If there was a need for another chain that supports NFTs (there isn't), why would anyone choose the slowest and most expensive network? It appears contradictory and unproductive.

Nonetheless, holding an NFT on the Bitcoin blockchain is more secure than any other blockchain, but this has little utility.

Bitcoin NFTs are undoubtedly controversial. NFTs are strange and perhaps harmful to Bitcoin's mission. If Bitcoin NFTs are here to stay, I hope a sidechain or rollup solution will take over and leave the base chain alone.

Traditional sales organizations used the concept of a sales “funnel” to describe the process through which potential customers move, ending up with sales at the end. Winners today have abandoned that way of thinking in favor of building flywheels — business models in which every element reinforces every other.

Ah, the marketing funnel…

Prospective clients go through a predictable set of experiences, students learn in business school marketing classes. It looks like this:

Understanding the funnel helps evaluate sales success indicators. Gail Goodwin, former CEO of small business direct mail provider Constant Contact, said managing the pipeline was key to escaping the sluggish SaaS ramp of death.

Like the funnel concept. To predict how well your business will do, measure how many potential clients are aware of it (awareness) and how many take the next step. If 1,000 people heard about your offering and 10% showed interest, you'd have 100 at that point. If 50% of these people made buyer-like noises, you'd know how many were, etc. It helped model buying trends.

TV, magazine, and radio advertising are pricey for B2C enterprises. Traditional B2B marketing involved armies of sales reps, which was expensive and a barrier to entry.

Cracks in the funnel model

Digital has exposed the funnel's limitations. Hubspot was born at a time when buyers and sellers had huge knowledge asymmetries, according to co-founder Brian Halligan. Those selling a product could use the buyer's lack of information to become a trusted partner.

As the world went digital, getting information and comparing offerings became faster, easier, and cheaper. Buyers didn't need a seller to move through a funnel. Interactions replaced transactions, and the relationship didn't end with a sale.

Instead, buyers and sellers interacted in a constant flow. In many modern models, the sale is midway through the process (particularly true with subscription and software-as-a-service models). Example:

You're creating a winding journey with many touch points, not a funnel (and lots of opportunities for customers to get lost).

From winding journey to flywheel

Beyond this revised view of an interactive customer journey, a company can create what Jim Collins famously called a flywheel. Imagine rolling a heavy disc on its axis. The first few times you roll it, you put in a lot of effort for a small response. The same effort yields faster turns as it gains speed. Over time, the flywheel gains momentum and turns without your help.

Modern digital organizations have created flywheel business models, in which any additional force multiplies throughout the business. The flywheel becomes a force multiplier, according to Collins.

Amazon is a famous flywheel example. Collins explained the concept to Amazon CEO Jeff Bezos at a corporate retreat in 2001. In The Everything Store, Brad Stone describes in his book The Everything Store how he immediately understood Amazon's levers.

The result (drawn on a napkin):

Low prices and a large selection of products attracted customers, while a focus on customer service kept them coming back, increasing traffic. Third-party sellers then increased selection. Low-cost structure supports low-price commitment. It's brilliant! Every wheel turn creates acceleration.

Where from here?

Flywheel over sales funnel! Consider these business terms.

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.