Sometimes doing everything correctly isn't enough.

In 2020, I could fix my life.

After failing to start a business, I owed $40,000 and had no work.

A $1.2 billion startup on the cusp of going public pulled me up.

Ironically, it was getting ready for an epic fall — with the world watching.

Life sometimes helps. Without a base, even the strongest fall. A corporation that did everything right failed 3 months after going public.

First-row view.

Apple is the creator of Adore.

Out of respect, I've altered the company and employees' names in this account, despite their failure.

Although being a publicly traded company, it may become obvious.

We’ll call it “Adore” — a revolutionary concept in retail shopping.

Two Apple execs established Adore in 2014 with a focus on people-first purchasing.

Jon and Tim:

• The concept for the stylish Apple retail locations you see today was developed by retail expert Jon Swanson, who collaborated closely with Steve Jobs.

• Tim Cruiter is a graphic designer who produced the recognizable bouncing lamp video that appears at the start of every Pixar film.

The dynamic duo realized their vision.

“What if you could combine the convenience of online shopping with the confidence of the conventional brick-and-mortar store experience.”

Adore's mobile store concept combined traditional retail with online shopping.

Adore brought joy to 70+ cities and 4 countries over 7 years, including the US, Canada, and the UK.

Being employed on the ground floor, with world dominance and IPO on the horizon, was exciting.

I started as an Adore Expert.

I delivered cell phones, helped consumers set them up, and sold add-ons.

As the company grew, I became a Virtual Learning Facilitator and trained new employees across North America using Zoom.

In this capacity, I gained corporate insider knowledge. I worked with the creative team and Jon and Tim.

It's where I saw company foundation fissures. Despite appearances, investors were concerned.

The business strategy was ground-breaking.

Even after seeing my employee stocks fall from a home down payment to $0 (when Adore filed for bankruptcy), it's hard to pinpoint what went wrong.

Solid business model, well-executed.

Jon and Tim's chase for public funding ended in glory.

Here’s the business model in a nutshell:

Buying cell phones is cumbersome. You have two choices:

1. Online purchase: not knowing what plan you require or how to operate your device.

2. Enter a store, which can be troublesome and stressful.

Apple, AT&T, and Rogers offered Adore as a free delivery add-on. Customers could:

• Have their phone delivered by UPS or Canada Post in 1-2 weeks.

• Alternately, arrange for a person to visit them the same day (or sometimes even the same hour) to assist them set up their phone and demonstrate how to use it (transferring contacts, switching the SIM card, etc.).

Each Adore Expert brought a van with extra devices and accessories to customers.

Happy customers.

Here’s how Adore and its partners made money:

Adores partners appreciated sending Experts to consumers' homes since they improved customer satisfaction, average sale, and gadget returns.

**Telecom enterprises have low customer satisfaction. The average NPS is 30/100. Adore's global NPS was 80.

Adore made money by:

• a set cost for each delivery

• commission on sold warranties and extras

Consumer product applications seemed infinite.

A proprietary scheduling system (“The Adore App”), allowed for same-day, even same-hour deliveries.

It differentiates Adore.

They treated staff generously by:

• Options on stock

• health advantages

• sales enticements

• high rates per hour

Four-day workweeks were set by experts.

Being hired early felt like joining Uber, Netflix, or Tesla. We hoped the company's stocks would rise.

Exciting times.

I smiled as I greeted more than 1,000 new staff.

I spent a decade in retail before joining Adore. I needed a change.

After a leap of faith, I needed a lifeline. So, I applied for retail sales jobs in the spring of 2019.

The universe typically offers you what you want after you accept what you need. I needed a job to settle my debt and reach $0 again.

And the universe listened.

After being hired as an Adore Expert, I became a Virtual Learning Facilitator. Enough said.

After weeks of economic damage from the pandemic.

This employment let me work from home during the pandemic. It taught me excellent business skills.

I was active in brainstorming, onboarding new personnel, and expanding communication as we grew.

This job gave me vital skills and a regular paycheck during the pandemic.

It wasn’t until January of 2022 that I left on my own accord to try to work for myself again — this time, it’s going much better.

Adore was perfect. We valued:

• Connection

• Discovery

• Empathy

Everything we did centered on compassion, and we held frequent Justice Calls to discuss diversity and work culture.

The last day of onboarding typically ended in tears as employees felt like they'd found a home, as I had.

Like all nice things, the wonderful vibes ended.

First indication of distress

My first day at the workplace was great.

Fun, intuitive, and they wanted creative individuals, not salesman.

While sales were important, the company's vision was more important.

“To deliver joy through life-changing mobile retail experiences.”

Thorough, forward-thinking training. We had a module on intuition. It gave us role ownership.

We were flown cross-country for training, gave feedback, and felt like we made a difference. Multiple contacts responded immediately and enthusiastically.

The atmosphere was genuine.

Making money was secondary, though. Incredible service was a priority.

Jon and Tim answered new hires' questions during Zoom calls during onboarding. CEOs seldom meet new hires this way, but they seemed to enjoy it.

All appeared well.

But in late 2021, things started changing.

Adore's leadership changed after its IPO. From basic values to sales maximization. We lost communication and were forced to fend for ourselves.

Removed the training wheels.

It got tougher to gain instructions from those above me, and new employees told me their roles weren't as advertised.

External money-focused managers were hired.

Instead of creative types, we hired salespeople.

With a new focus on numbers, Adore's uniqueness began to crumble.

Via Zoom, hundreds of workers were let go.

So.

Early in 2022, mass Zoom firings were trending. A CEO firing 900 workers over Zoom went viral.

Adore was special to me, but it became a headline.

30 June 2022, Vice Motherboard published Watch as Adore's CEO Fires Hundreds.

It described a leaked video of Jon Swanson laying off all staff in Canada and the UK.

They called it a “notice of redundancy”.

The corporation couldn't pay its employees.

I loved Adore's underlying ideals, among other things. We called clients Adorers and sold solutions, not add-ons.

But, like anything, a company is only as strong as its weakest link. And obviously, the people-first focus wasn’t making enough money.

There were signs. The expansion was presumably a race against time and money.

Adore finally declared bankruptcy.

Adore declared bankruptcy 3 months after going public. It happened in waves, like any large-scale fall.

• Initial key players to leave were

• Then, communication deteriorated.

• Lastly, the corporate culture disintegrated.

6 months after leaving Adore, I received a letter in the mail from a Law firm — it was about my stocks.

Adore filed Chapter 11. I had to sue to collect my worthless investments.

I hoped those stocks will be valuable someday. Nope. Nope.

Sad, I sighed.

$1.2 billion firm gone.

I left the workplace 3 months before starting a writing business. Despite being mediocre, I'm doing fine.

I got up as Adore fell.

Finally, can we scale kindness?

I trust my gut. Changes at Adore made me leave before it sank.

Adores' unceremonious slide from a top startup to bankruptcy is astonishing to me.

The company did everything perfectly, in my opinion.

• first to market,

• provided excellent service

• paid their staff handsomely.

• was responsible and attentive to criticism

The company wasn't led by an egotistical eccentric. The crew had centuries of cumulative space experience.

I'm optimistic about the future of work culture, but is compassion scalable?

If I could tell my younger self a few rules, they would boost my career.

1. Treat design like medicine; don't get attached.

If it doesn't help, you won't be angry, but you'll try to improve it. Designers blame others if they don't like the design, but the rule is the same: we solve users' problems. You're not your design, and neither are they. Be humble with your work because your assumptions will often be wrong and users will behave differently.

2. Consider your design flawed.

Disagree with yourself, then defend your ideas. Most designers forget to dig deeper into a pattern, screen, button, or copywriting. If someone asked, "Have you considered alternatives? How does this design stack up? Here's a functional UX checklist to help you make design decisions.

3. Codeable solutions.

If your design requires more developer time, consider whether it's worth spending more money to code something with a small UX impact. Overthinking problems and designing abstract patterns is easy. Sometimes you see something on dribbble or bechance and try to recreate it, but it's not worth it. Here's my article on it.

4. Communication changes careers

Designers often talk with users, clients, companies, developers, and other designers. How you talk and present yourself can land you a job. Like driving or swimming, practice it. Success requires being outgoing and friendly. If I hadn't said "hello" to a few people, I wouldn't be where I am now.

5. Ignorance of the law is not an excuse.

Copyright, taxation How often have you used an icon without checking its license? If you use someone else's work in your project, the owner can cause you a lot of problems — paying a lot of money isn't worth it. Spend a few hours reading about copyrights, client agreements, and taxes.

6. Always test your design

If nobody has seen or used my design, it's not finished. Ask friends about prototypes. Testing reveals how wrong your assumptions were. Steve Krug, one of the authorities on this topic will tell you more about how to do testing.

7. Run workshops

A UX designer's job involves talking to people and figuring out what they need, which is difficult because they usually don't know. Organizing teamwork sessions is a powerful skill, but you must also be a good listener. Your job is to help a quiet, introverted developer express his solution and control the group. AJ Smart has more on workshops here.

Non-technical talents can benefit data scientists in addition to statistics and programming.

As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.

Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.

Ready? Let’s dive in.

Best books for data scientists

1. The Black Swan

Author: Nassim Taleb

First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.

Three characteristics define a black swan event:

• It is erratic.

• It has a significant impact.

• Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.

People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.

Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.

Try multiple tactics and models because you may find the answer.

2. High Output Management

Author: Andrew Grove

Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.

That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.

Five lessons:

• Every action is a procedure.

• Meetings are a medium of work

• Manage short-term goals in accordance with long-term strategies.

• Mission-oriented teams accelerate while functional teams increase leverage.

• Utilize performance evaluations to enhance output.

So — if the above captures your imagination, it’s well worth getting stuck in.

3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers

Author: Ben Horowitz

Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.

Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.

It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.

Find suggestions on:

• create software

• Run a business.

• Promote a product

• Obtain resources

• Smart investment

• oversee daily operations

This book will help you cope with tough times.

4. Obviously Awesome: How to Nail Product Positioning

Author: April Dunford

Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.

How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.

You'll learn:

• Select the ideal market for your products.

• Connect an audience to the value of your goods right away.

• Take use of three positioning philosophies.

• Utilize market trends to aid purchasers

5. The Mom test

Author: Rob Fitzpatrick

The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.

Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.

6. Introduction to Machine Learning with Python: A Guide for Data Scientists

Authors: Andreas C. Müller, Sarah Guido

Now, technical documents.

This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.

Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.

If you know machine learning or artificial neural networks, skip this.

7. Python Data Science Handbook: Essential Tools for Working with Data

Author: Jake VanderPlas

Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.

Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.

The only thing missing is a way to apply your learnings.

8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Author: Wes McKinney

The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.

The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.

9. Data Science from Scratch

Author: Joel Grus

Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.

The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.

Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.

10. Machine Learning Yearning

Author: Andrew Ng

Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.

The book delivers knowledge and teaches how to apply it, so you'll know how to:

• Determine the optimal course of action for your ML project.

• Create software that is more effective than people.

• Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.

• Identifying machine learning system flaws

Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.

11. Deep Learning with PyTorch Step-by-Step

Author: Daniel Voigt Godoy

The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.

It comprises four parts:

1. Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)

2. Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)

3. Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)

4. Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)

We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.

Is every data scientist a humanist?

Even as a technological professional, you can't escape human interaction, especially with clients.

We hope these books will help you develop interpersonal skills.

In this article, I'll describe a weekend project I started to make something. It was Product Hunt's #1 of the Day, #2 Weekly, and #4 Monthly product.

How did I make Landing Page Checklist so simple? Building and launching took 3 weeks. I worked 3 hours a day max. Weekends were busy.

It's sort of a long story, so scroll to the bottom of the page to see what tools I utilized to create Landing Page Checklist :x ‍

As a matter of fact, it all started with the startups-investments blog; Startup Bulletin, that I started writing in 2018. No, don’t worry, I won’t be going that far behind. The twitter account where I shared the blog posts of this newsletter was inactive for a looong time. I was holding this Twitter account since 2009, I couldn’t bear to destroy it. At the same time, I was thinking how to evaluate this account.

So I looked for a weekend assignment.

Weekend undertaking: Generate business names

Barash and I established a weekend effort to stay current. Building things helped us learn faster.

Simple. Startup Name Generator The utility generated random startup names. After market research for SEO purposes, we dubbed it Business Name Generator.

Backend developer Barash dislikes frontend work. He told me to write frontend code. Chakra UI and Tailwind CSS were recommended.

It was the first time I have heard about Tailwind CSS.

Before this project, I made mobile-web app designs in Sketch and shared them via Zeplin. I can read HTML-CSS or React code, but not write it. I didn't believe myself but followed Barash's advice.

My home page wasn't responsive when I started. Here it was:)

And then... Product Hunt had something I needed. Me-only! A website builder that gives you clean Tailwind CSS code and pre-made web components (like Elementor). Incredible.

I bought it right away because it was so easy to use. Best part: It's not just index.html. It includes all needed files. Like

• postcss.config.js

• README.md

• package.json

• among other things, tailwind.config.js

This is for non-techies.

Tailwind.build; which is Shuffle now, allows you to create and export projects for free (with limited features). You can try it by visiting their website.

After downloading the project, you can edit the text and graphics in Visual Studio (or another text editor). This HTML file can be hosted whenever.

Github is an easy way to host a landing page.

1. your project via Shuffle for export

2. your website's content, edit

3. Create a Gitlab, Github, or Bitbucket account.

4. to Github, upload your project folder.

5. Integrate Vercel with your Github account (or another platform below)

6. Allow them to guide you in steps.

Finally. If you push your code to Github using Github Desktop, you'll do it quickly and easily.

Speaking of; here are some hosting and serverless backend services for web applications and static websites for you host your landing pages for FREE!

I host landingpage.fyi on Vercel but all is fine. You can choose any platform below with peace in mind.

• Vercel

• Render

• Netlify

After connecting your project/repo to Vercel, you don’t have to do anything on Vercel. Vercel updates your live website when you update Github Desktop. Wow!

Tails came out while I was using tailwind.build. Although it's prettier, tailwind.build is more mobile-friendly. I couldn't resist their lovely parts. Tails :)

Tails have several well-designed parts. Some components looked awful on mobile, but this bug helped me understand Tailwind CSS.

Unlike Shuffle, Tails does not include files when you export such as config.js, main.js, README.md. It just gives you the HTML code. Suffle.dev is a bit ahead in this regard and with mobile-friendly blocks if you ask me. Of course, I took advantage of both.

creativebusinessnames.co is inactive, but I'll leave a deployment link :)

Adam Wathan's YouTube videos and Tailwind's official literature helped me, but I couldn't have done it without Tails and Shuffle. These tools helped me make landing pages. I shouldn't have started over.

So began my Tailwind CSS adventure. I didn't build landingpage. I didn't plan it to be this long; sorry.

I learnt a lot while I was playing around with Shuffle and Tails Builders.

Long story short I built landingpage.fyi with the help of these tools;

Learning, building, and distribution

• tailwindcss.com/docs

• Shuffle (Started with a Shuffle Template)

• Tails (Used components from here)

• Sketch (to handle icons, logos, and .svg’s)

• metatags.io (Auto Generator Meta Tags)

• Vercel (Hosting)

• Github Desktop (Pushing code to Github -super easy-)

• Visual Studio Code (Edit my code)

• Mailerlite (Capture Emails)

• Google Analytics

• Jarvis / Conversion.ai (%90 of the text on website written by AI 😇 )

• CookieHub (Consent Management)

That's all. A few things:

The Outcome

.fyi Domain: Why?

I'm often asked this.

I don't know, but I wanted to include the landing page term. Popular TLDs are gone. I saw my alternatives. brief and catchy.

CSS Tailwind Resources

I'll share project resources like Tails and Shuffle.

• Wicked Templates

• TailwindCSS Buttons

• Blocks | Wicked Templates

• nine4

• TUK — Tailwind UI KIT

• HyperUI

• Lofi UI

• Beginner Tailwind (I lately enrolled in this course but haven’t completed it yet.)

Thanks for reading my blog's first post. Please share if you like it.

Overview

Ethereum blockchain is a network of nodes that validate transactions. Any network node can be queried for blockchain data for free. To write data as a transition requires processing and writing to each network node's storage. Fee is paid in ether and is also called as gas.

We'll examine how user-initiated transactions flow across the network and into the blockchain.

Flow of transactions

• A user wishes to move some ether from one external account to another. He utilizes a cryptocurrency wallet for this (like Metamask), which is a browser extension.

• The user enters the desired transfer amount and the external account's address. He has the option to choose the transaction cost he is ready to pay.

• Wallet makes use of this data, signs it with the user's private key, and writes it to an Ethereum node. Services such as Infura offer APIs that enable writing data to nodes. One of these services is used by Metamask. An example transaction is shown below. Notice the “to” address and value fields.

var rawTxn = {
    nonce: web3.toHex(txnCount),
    gasPrice: web3.toHex(100000000000),
    gasLimit: web3.toHex(140000),
    to: '0x633296baebc20f33ac2e1c1b105d7cd1f6a0718b',
    value: web3.toHex(0),
    data: '0xcc9ab24952616d6100000000000000000000000000000000000000000000000000000000'
};

• The transaction is written to the target Ethereum node's local TRANSACTION POOL. It informed surrounding nodes of the new transaction, and those nodes reciprocated. Eventually, this transaction is received by and written to each node's local TRANSACTION pool.

• The miner who finds the following block first adds pending transactions (with a higher gas cost) from the nearby TRANSACTION POOL to the block.

• The transactions written to the new block are verified by other network nodes.

• A block is added to the main blockchain after there is consensus and it is determined to be genuine. The local blockchain is updated with the new node by additional nodes as well.

• Block mining begins again next.

The image above shows how transactions go via the network and what's needed to submit them to the main block chain.

References

ethereum.org/transactions How Ethereum transactions function, their data structure, and how to send them via app. ethereum.org

You’ll be surprised; I sure was

Blogging and writing online as a side income has now been around for a significant amount of time. Nowadays, it is a continuously rising moneymaker for prospective writers, with several writing platforms existing online. At the top of the list are Medium, Vocal Media, Newsbreak, and the biggest one of them, Quora, with 300 million active users.

Quora, unlike Medium, is a question-and-answer format platform. On Medium you are permitted to write what you want, while on Quora, you answer questions on topics that you have expertise about. Quora, like Medium, now compensates its authors for the answers they provide in comparison to the previous, in which you had to be admitted to the partner program and were paid to ask questions.

Quora just recently went live with this new partner program, Quora Plus, and the way it works is that it is a subscription for $5 a month which provides you access to metered/monetized stories, in turn compensating the writers for part of that subscription for their answers.

I too on Quora have found a lot of success on the platform, gaining 23 Million Content Views, and 300,000 followers for my space, which is kind of the Quora equivalent of a Medium article. The way in which I was able to do this was entirely thanks to a hack that I uncovered to the Quora algorithm.

In this article, I plan on discussing how much money I received from 23 million content views on Quora, and I bet you’ll be shocked; I know I was.

A Brief Explanation of How I Got 23 Million Views and How You Can Do It Too

On Quora, everything in terms of obtaining views is about finding the proper question, which I only understood quite late into the game. I published my first response in 2019 but never actually wrote on Quora until the summer of 2020, and about a month into posting consistently I found out how to find the perfect question. Here’s how:

The Process

Go to your Home Page and start scrolling… While browsing, check for the following things…

1. Answers from people you follow or your followers.

2. Advertisements

These two things are the two things you want to ignore, you don’t want to answer those questions or look at the ads. You should now be left with a couple of recommended answers. To discover which recommended answer is the best to answer as well, look at these three important aspects.

1. Date of the answer: Was it in the past few days, preferably 2–3 days, even better, past 24 hours?

2. Views: Are they in the ten thousands or hundred thousands?

3. Upvotes: Are they in the hundreds or thousands?

Now, choose an answer to a question which you think you could answer as well that satisfies the requirements above. Once you click on it, as all answers on Quora works, it will redirect you to the page for that question, in which you will have to select once again if you should answer the question.

1. Amount of answers: How many responses are there to the given question? This tells you how much competition you have. My rule is beyond 25 answers, you shouldn’t answer, but you can change it anyway you’d like.

2. Answerers: Who did the answering for the question? If the question includes a bunch of renowned, extremely well-known people on Quora, there’s a good possibility your essay is going to get drowned out.

3. Views: Check for a constant quantity of high views on each answer for the question; this is what will guarantee that your answer gets a lot of views!

The Income Reveal! How Much I Made From 23 Million Content Views

DRUM ROLL, PLEASE!

8.97 USD. Yes, not even ten dollars, not even nine. Just eight dollars and ninety-seven cents.

Possible Reasons for My Low Earnings

• Quora Plus and the answering partner program are newer than my Quora views.

• Few people use Quora+, therefore revenues are low.

• I haven't been writing much on Quora, so I'm only making money from old answers and a handful since Quora Plus launched.

• Quora + pays poorly...

Should You Try Quora and Quora For Money?

My answer depends on your needs. I never got invited to Quora's question partner program due to my late start, but other writers have made hundreds. Due to Quora's new and competitive answering partner program, you may not make much money.

If you want a fun writing community, try Quora. Quora was fun when I only made money from my space. Quora +'s paywalls and new contributors eager to make money have made the platform less fun for me.

This article is a summary to save you time. You can read my full, more detailed article, here.