Framework to Evaluate Metaverse and Web3
Everywhere we turn, there's a new metaverse or Web3 debut. Microsoft recently announced a $68.7 BILLION cash purchase of Activision.
Like AI in 2013 and blockchain in 2014, NFT growth in 2021 feels like this year's metaverse and Web3 growth. We are all bombarded with information, conflicting signals, and a sensation of FOMO.
How can we evaluate the metaverse and Web3 in a noisy, new world? My framework for evaluating upcoming technologies and themes is shown below. I hope you will also find them helpful.
Understand the “pipes” in a new space.
Whatever people say, Metaverse and Web3 will have to coexist with the current Internet. Companies who host, move, and store data over the Internet have a lot of intriguing use cases in Metaverse and Web3, whether in infrastructure, data analytics, or compliance. Hence the following point.
## Understand the apps layer and their infrastructure.
Gaming, crypto exchanges, and NFT marketplaces would not exist today if not for technology that enables rapid app creation. Yes, according to Chainalysis and other research, 30–40% of Ethereum is self-hosted, with the rest hosted by large cloud providers. For Microsoft to acquire Activision makes strategic sense. It's not only about the games, but also the infrastructure that supports them.
Follow the money
Understanding how money and wealth flow in a complex and dynamic environment helps build clarity. Unless you are exceedingly wealthy, you have limited ability to significantly engage in the Web3 economy today. Few can just buy 10 ETH and spend it in one day. You must comprehend who benefits from the process, and how that 10 ETH circulates now and possibly tomorrow. Major holders and players control supply and liquidity in any market. Today, most Web3 apps are designed to increase capital inflow so existing significant holders can utilize it to create a nascent Web3 economy. When you see a new Metaverse or Web3 application, remember how money flows.
What is the use case?
What does the app do? If there is no clear use case with clear makers and consumers solving a real problem, then the euphoria soon fades, and the only stakeholders who remain enthused are those who have too much to lose.
Time is a major competition that is often overlooked.
We're only busier, but each day is still 24 hours. Using new apps may mean that time is lost doing other things. The user must be eager to learn. Metaverse and Web3 vs. our time? I don't think we know the answer yet (at least for working adults whose cost of time is higher).
I don't think we know the answer yet (at least for working adults whose cost of time is higher).
People and organizations need security and transparency.
For new technologies or apps to be widely used, they must be safe, transparent, and trustworthy. What does secure Metaverse and Web3 mean? This is an intriguing subject for both the business and public sectors. Cloud adoption grew in part due to improved security and data protection regulations.
The following frameworks can help analyze and understand new technologies and emerging technological topics, unless you are a significant investment fund with the financial ability to gamble on numerous initiatives and essentially form your own “index fund”.
I write on VC, startups, and leadership.
More on https://www.linkedin.com/in/joycejshen/ and https://joyceshen.substack.com/
This writing is my own opinion and does not represent investment advice.
More on Web3 & Crypto
Yogesh Rawal
3 years ago
Blockchain to solve growing privacy challenges
Most online activity is now public. Businesses collect, store, and use our personal data to improve sales and services.
In 2014, Uber executives and employees were accused of spying on customers using tools like maps. Another incident raised concerns about the use of ‘FaceApp'. The app was created by a small Russian company, and the photos can be used in unexpected ways. The Cambridge Analytica scandal exposed serious privacy issues. The whole incident raised questions about how governments and businesses should handle data. Modern technologies and practices also make it easier to link data to people.
As a result, governments and regulators have taken steps to protect user data. The General Data Protection Regulation (GDPR) was introduced by the EU to address data privacy issues. The law governs how businesses collect and process user data. The Data Protection Bill in India and the General Data Protection Law in Brazil are similar.
Despite the impact these regulations have made on data practices, a lot of distance is yet to cover.
Blockchain's solution
Blockchain may be able to address growing data privacy concerns. The technology protects our personal data by providing security and anonymity. The blockchain uses random strings of numbers called public and private keys to maintain privacy. These keys allow a person to be identified without revealing their identity. Blockchain may be able to ensure data privacy and security in this way. Let's dig deeper.
Financial transactions
Online payments require third-party services like PayPal or Google Pay. Using blockchain can eliminate the need to trust third parties. Users can send payments between peers using their public and private keys without providing personal information to a third-party application. Blockchain will also secure financial data.
Healthcare data
Blockchain technology can give patients more control over their data. There are benefits to doing so. Once the data is recorded on the ledger, patients can keep it secure and only allow authorized access. They can also only give the healthcare provider part of the information needed.
The major challenge
We tried to figure out how blockchain could help solve the growing data privacy issues. However, using blockchain to address privacy concerns has significant drawbacks. Blockchain is not designed for data privacy. A ‘distributed' ledger will be used to store the data. Another issue is the immutability of blockchain. Data entered into the ledger cannot be changed or deleted. It will be impossible to remove personal data from the ledger even if desired.
MIT's Enigma Project aims to solve this. Enigma's ‘Secret Network' allows nodes to process data without seeing it. Decentralized applications can use Secret Network to use encrypted data without revealing it.
Another startup, Oasis Labs, uses blockchain to address data privacy issues. They are working on a system that will allow businesses to protect their customers' data.
Conclusion
Blockchain technology is already being used. Several governments use blockchain to eliminate centralized servers and improve data security. In this information age, it is vital to safeguard our data. How blockchain can help us in this matter is still unknown as the world explores the technology.
Ashraful Islam
4 years ago
Clean API Call With React Hooks
| Photo by Juanjo Jaramillo on Unsplash |
Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.
When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.
The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.
In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.
I’m using a code sandbox for this blog which you can get here.
import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";
export default function App() {
const [posts, setPosts] = useState(null);
const [error, setError] = useState("");
const [loading, setLoading] = useState(false);
useEffect(() => {
handlePosts();
}, []);
const handlePosts = async () => {
setLoading(true);
try {
const result = await axios.get(
"https://jsonplaceholder.typicode.com/posts"
);
setPosts(result.data);
} catch (err) {
setError(err.message || "Unexpected Error!");
} finally {
setLoading(false);
}
};
return (
<div className="App">
<div>
<h1>Posts</h1>
{loading && <p>Posts are loading!</p>}
{error && <p>{error}</p>}
<ul>
{posts?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
</div>
);
}
I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.
Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.
If we try to call another API from the same component then how that would gonna look? Let’s see.
500: Internal Server Error
Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.
Let’s refactor to make the code more reusable with fewer repetitions.
Step 1: Create a Hook for the Redundant API Request Codes
Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?
The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.
500: Internal Server Error
Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.
With hooks in action, let’s change our old codes in App component, like this:
500: Internal Server Error
How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?
Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…
Step 2: One Component Should Take Just One Responsibility
Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.
We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:
import axios from "axios";
const apiClient = axios.create({
// Later read this URL from an environment variable
baseURL: "https://jsonplaceholder.typicode.com"
});
export default apiClient;
All API calls for comments resource will be in the following file:
import client from "./client";
const getComments = () => client.get("/comments");
export default {
getComments
};
All API calls for posts resource are placed in the following file:
import client from "./client";
const getPosts = () => client.get("/posts");
export default {
getPosts
};
Finally, the App component looks like the following:
import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";
export default function App() {
const getPostsApi = useApi(postsApi.getPosts);
const getCommentsApi = useApi(commentsApi.getComments);
useEffect(() => {
getPostsApi.request();
getCommentsApi.request();
}, []);
return (
<div className="App">
{/* Post List */}
<div>
<h1>Posts</h1>
{getPostsApi.loading && <p>Posts are loading!</p>}
{getPostsApi.error && <p>{getPostsApi.error}</p>}
<ul>
{getPostsApi.data?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
{/* Comment List */}
<div>
<h1>Comments</h1>
{getCommentsApi.loading && <p>Comments are loading!</p>}
{getCommentsApi.error && <p>{getCommentsApi.error}</p>}
<ul>
{getCommentsApi.data?.map((comment) => (
<li key={comment.id}>{comment.name}</li>
))}
</ul>
</div>
</div>
);
}
Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.
Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.
So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.
Final Thoughts
The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.
OnChain Wizard
3 years ago
How to make a >800 million dollars in crypto attacking the once 3rd largest stablecoin, Soros style
Everyone is talking about the $UST attack right now, including Janet Yellen. But no one is talking about how much money the attacker made (or how brilliant it was). Lets dig in.
Our story starts in late March, when the Luna Foundation Guard (or LFG) starts buying BTC to help back $UST. LFG started accumulating BTC on 3/22, and by March 26th had a $1bn+ BTC position. This is leg #1 that made this trade (or attack) brilliant.
The second leg comes in the form of the 4pool Frax announcement for $UST on April 1st. This added the second leg needed to help execute the strategy in a capital efficient way (liquidity will be lower and then the attack is on).
We don't know when the attacker borrowed 100k BTC to start the position, other than that it was sold into Kwon's buying (still speculation). LFG bought 15k BTC between March 27th and April 11th, so lets just take the average price between these dates ($42k).
So you have a ~$4.2bn short position built. Over the same time, the attacker builds a $1bn OTC position in $UST. The stage is now set to create a run on the bank and get paid on your BTC short. In anticipation of the 4pool, LFG initially removes $150mm from 3pool liquidity.
The liquidity was pulled on 5/8 and then the attacker uses $350mm of UST to drain curve liquidity (and LFG pulls another $100mm of liquidity).
But this only starts the de-pegging (down to 0.972 at the lows). LFG begins selling $BTC to defend the peg, causing downward pressure on BTC while the run on $UST was just getting started.
With the Curve liquidity drained, the attacker used the remainder of their $1b OTC $UST position ($650mm or so) to start offloading on Binance. As withdrawals from Anchor turned from concern into panic, this caused a real de-peg as people fled for the exits
So LFG is selling $BTC to restore the peg while the attacker is selling $UST on Binance. Eventually the chain gets congested and the CEXs suspend withdrawals of $UST, fueling the bank run panic. $UST de-pegs to 60c at the bottom, while $BTC bleeds out.
The crypto community panics as they wonder how much $BTC will be sold to keep the peg. There are liquidations across the board and LUNA pukes because of its redemption mechanism (the attacker very well could have shorted LUNA as well). BTC fell 25% from $42k on 4/11 to $31.3k
So how much did our attacker make? There aren't details on where they covered obviously, but if they are able to cover (or buy back) the entire position at ~$32k, that means they made $952mm on the short.
On the $350mm of $UST curve dumps I don't think they took much of a loss, lets assume 3% or just $11m. And lets assume that all the Binance dumps were done at 80c, thats another $125mm cost of doing business. For a grand total profit of $815mm (bf borrow cost).
BTC was the perfect playground for the trade, as the liquidity was there to pull it off. While having LFG involved in BTC, and foreseeing they would sell to keep the peg (and prevent LUNA from dying) was the kicker.
Lastly, the liquidity being low on 3pool in advance of 4pool allowed the attacker to drain it with only $350mm, causing the broader panic in both BTC and $UST. Any shorts on LUNA would've added a lot of P&L here as well, with it falling -65% since 5/7.
And for the reply guys, yes I know a lot of this involves some speculation & assumptions. But a lot of money was made here either way, and I thought it would be cool to dive into how they did it.
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Pat Vieljeux
3 years ago
Your entrepreneurial experience can either be a beautiful adventure or a living hell with just one decision.
Choose.
DNA makes us distinct.
We act alike. Most people follow the same road, ignoring differences. We remain quiet about our uniqueness for fear of exclusion (family, social background, religion). We live a more or less imposed life.
Off the beaten path, we stand out from the others. We obey without realizing we're sewing a shroud. We're told to do as everyone else and spend 40 years dreaming of a golden retirement and regretting not living.
“One of the greatest regrets in life is being what others would want you to be, rather than being yourself.” - Shannon L. Alder
Others dare. Again, few are creative; most follow the example of those who establish a business for the sake of entrepreneurship. To live.
They pick a potential market and model their MVP on an existing solution. Most mimic others, alter a few things, appear to be original, and end up with bland products, adding to an already crowded market.
SaaS, PaaS, etc. followed suit. It's reduced pricing, profitability, and product lifespan.
As competitors become more aggressive, their profitability diminishes, making life horrible for them and their employees. They fail to innovate, cut costs, and close their company.
Few of them look happy and fulfilled.
How did they do it?
The answer is unsettlingly simple.
They are themselves.
They start their company, propelled at first by a passion or maybe a calling.
Then, at their own pace, they create it with the intention of resolving a dilemma.
They assess what others are doing and consider how they might improve it.
In contrast to them, they respond to it in their own way by adding a unique personal touch. Therefore, it is obvious.
Originals, like their DNA, can't be copied. Or if they are, they're poorly printed. Originals are unmatched. Artist-like. True collectors only buy Picasso paintings by the master, not forgeries, no matter how good.
Imaginative people are constantly ahead. Copycats fall behind unless they innovate. They watch their competition continuously. Their solution or product isn't sexy. They hope to cash in on their copied product by flooding the market.
They're mostly pirates. They're short-sighted, unlike creators.
Creators see further ahead and have no rivals. They use copiers to confirm a necessity. To maintain their individuality, creators avoid copying others. They find copying boring. It's boring. They oppose plagiarism.
It's thrilling and inspiring.
It will also make them more able to withstand their opponents' tension. Not to mention roadblocks. For creators, impediments are games.
Others fear it. They race against the clock and fear threats that could interrupt their momentum since they lack inventiveness and their product has a short life cycle.
Creators have time on their side. They're dedicated. Clearly. Passionate booksellers will have their own bookstore. Their passion shows in their book choices. Only the ones they love.
The copier wants to display as many as possible, including mediocre authors, and will cut costs. All this to dominate the market. They're digging their own grave.
The bookseller is just one example. I could give you tons of them.
Closing remarks
Entrepreneurs might follow others or be themselves. They risk exhaustion trying to predict what their followers will do.
It's true.
Life offers choices.
Being oneself or doing as others do, with the possibility of regretting not expressing our uniqueness and not having lived.
“Be yourself; everyone else is already taken”. Oscar Wilde
The choice is yours.
Thomas Smith
3 years ago
ChatGPT Is Experiencing a Lightbulb Moment
Why breakthrough technologies must be accessible
ChatGPT has exploded. Over 1 million people have used the app, and coding sites like Stack Overflow have banned its answers. It's huge.
I wouldn't have called that as an AI researcher. ChatGPT uses the same GPT-3 technology that's been around for over two years.
More than impressive technology, ChatGPT 3 shows how access makes breakthroughs usable. OpenAI has finally made people realize the power of AI by packaging GPT-3 for normal users.
We think of Thomas Edison as the inventor of the lightbulb, not because he invented it, but because he popularized it.
Going forward, AI companies that make using AI easy will thrive.
Use-case importance
Most modern AI systems use massive language models. These language models are trained on 6,000+ years of human text.
GPT-3 ate 8 billion pages, almost every book, and Wikipedia. It created an AI that can write sea shanties and solve coding problems.
Nothing new. I began beta testing GPT-3 in 2020, but the system's basics date back further.
Tools like GPT-3 are hidden in many apps. Many of the AI writing assistants on this platform are just wrappers around GPT-3.
Lots of online utilitarian text, like restaurant menu summaries or city guides, is written by AI systems like GPT-3. You've probably read GPT-3 without knowing it.
Accessibility
Why is ChatGPT so popular if the technology is old?
ChatGPT makes the technology accessible. Free to use, people can sign up and text with the chatbot daily. ChatGPT isn't revolutionary. It does it in a way normal people can access and be amazed by.
Accessibility isn't easy. OpenAI's Sam Altman tweeted that opening ChatGPT to the public increased computing costs.
Each chat costs "low-digit cents" to process. OpenAI probably spends several hundred thousand dollars a day to keep ChatGPT running, with no immediate business case.
Academic researchers and others who developed GPT-3 couldn't afford it. Without resources to make technology accessible, it can't be used.
Retrospective
This dynamic is old. In the history of science, a researcher with a breakthrough idea was often overshadowed by an entrepreneur or visionary who made it accessible to the public.
We think of Thomas Edison as the inventor of the lightbulb. But really, Vasilij Petrov, Thomas Wright, and Joseph Swan invented the lightbulb. Edison made technology visible and accessible by electrifying public buildings, building power plants, and wiring.
Edison probably lost a ton of money on stunts like building a power plant to light JP Morgan's home, the NYSE, and several newspaper headquarters.
People wanted electric lights once they saw their benefits. By making the technology accessible and visible, Edison unlocked a hugely profitable market.
Similar things are happening in AI. ChatGPT shows that developing breakthrough technology in the lab or on B2B servers won't change the culture.
AI must engage people's imaginations to become mainstream. Before the tech impacts the world, people must play with it and see its revolutionary power.
As the field evolves, companies that make the technology widely available, even at great cost, will succeed.
OpenAI's compute fees are eye-watering. Revolutions are costly.
Hudson Rennie
3 years ago
My Work at a $1.2 Billion Startup That Failed
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:
Online purchase: not knowing what plan you require or how to operate your device.
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?