More on Personal Growth
Alex Mathers
3 years ago Draft
12 practices of the zenith individuals I know
Calmness is a vital life skill.
It aids communication. It boosts creativity and performance.
I've studied calm people's habits for years. Commonalities:
Have learned to laugh at themselves.
Those who have something to protect can’t help but make it a very serious business, which drains the energy out of the room.
They are fixated on positive pursuits like making cool things, building a strong physique, and having fun with others rather than on depressing influences like the news and gossip.
Every day, spend at least 20 minutes moving, whether it's walking, yoga, or lifting weights.
Discover ways to take pleasure in life's challenges.
Since perspective is malleable, they change their view.
Set your own needs first.
Stressed people neglect themselves and wonder why they struggle.
Prioritize self-care.
Don't ruin your life to please others.
Make something.
Calm people create more than react.
They love creating beautiful things—paintings, children, relationships, and projects.
Hold your breath, please.
If you're stressed or angry, you may be surprised how much time you spend holding your breath and tightening your belly.
Release, breathe, and relax to find calm.
Stopped rushing.
Rushing is disadvantageous.
Calm people handle life better.
Are attuned to their personal dietary needs.
They avoid junk food and eat foods that keep them healthy, happy, and calm.
Don’t take anything personally.
Stressed people control everything.
Self-conscious.
Calm people put others and their work first.
Keep their surroundings neat.
Maintaining an uplifting and clutter-free environment daily calms the mind.
Minimise negative people.
Calm people are ruthless with their boundaries and avoid negative and drama-prone people.
Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
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:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
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.
Tim Denning
3 years ago
I gave up climbing the corporate ladder once I realized how deeply unhappy everyone at the top was.
Restructuring and layoffs cause career reevaluation. Your career can benefit.
Once you become institutionalized, the corporate ladder is all you know.
You're bubbled. Extremists term it the corporate Matrix. I'm not so severe because the business world brainwashed me, too.
This boosted my corporate career.
Until I hit bottom.
15 months later, I view my corporate life differently. You may wish to advance professionally. Read this before you do.
Your happiness in the workplace may be deceptive.
I've been fortunate to spend time with corporate aces.
Working for 2.5 years in banking social media gave me some of these experiences. Earlier in my career, I recorded interviews with business leaders.
These people have titles like Chief General Manager and Head Of. New titles brought life-changing salaries.
They seemed happy.
I’d pass them in the hallway and they’d smile or shake my hand. I dreamt of having their life.
The ominous pattern
Unfiltered talks with some of them revealed a different world.
They acted well. They were skilled at smiling and saying the correct things. All had the same dark pattern, though.
Something felt off.
I found my conversations with them were generally for their benefit. They hoped my online antics as a writer/coach would shed light on their dilemma.
They'd tell me they wanted more. When you're one position away from CEO, it's hard not to wonder if this next move will matter.
What really displeased corporate ladder chasers
Before ascending further, consider these.
Zero autonomy
As you rise in a company, your days get busier.
Many people and initiatives need supervision. Everyone expects you to know business details. Weak when you don't. A poor leader is fired during the next restructuring and left to pursue their corporate ambition.
Full calendars leave no time for reflection. You can't have a coffee with a friend or waste a day.
You’re always on call. It’s a roll call kinda life.
Unable to express oneself freely
My 8 years of LinkedIn writing helped me meet these leaders.
I didn't think they'd care. Mistake.
Corporate leaders envied me because they wanted to talk freely again without corporate comms or a PR firm directing them what to say.
They couldn't share their flaws or inspiring experiences.
They wanted to.
Every day they were muzzled eroded by their business dream.
Limited family time
Top leaders had families.
They've climbed the corporate ladder. Nothing excellent happens overnight.
Corporate dreamers rarely saw their families.
Late meetings, customer functions, expos, training, leadership days, team days, town halls, and product demos regularly occurred after work.
Or they had to travel interstate or internationally for work events. They used bags and motel showers.
Initially, they said business class flights and hotels were nice. They'd get bored. 5-star hotels become monotonous.
No hotel beats home.
One leader said he hadn't seen his daughter much. They used to Facetime, but now that he's been gone so long, she rarely wants to talk to him.
So they iPad-parented.
You're miserable without your family.
Held captive by other job titles
Going up the business ladder seems like a battle.
Leaders compete for business gains and corporate advancement.
I saw shocking filthy tricks. Leaders would lie to seem nice.
Captives included top officials.
A different section every week. If they ran technology, the Head of Sales would argue their CRM cost millions. Or an Operations chief would battle a product team over support requests.
After one conflict, another began.
Corporate echelons are antagonistic. Huge pay and bonuses guarantee bad behavior.
Overly centered on revenue
As you rise, revenue becomes more prevalent. Most days, you'd believe revenue was everything. Here’s the problem…
Numbers drain us.
Unless you're a closet math nerd, contemplating and talking about numbers drains your creativity.
Revenue will never substitute impact.
Incapable of taking risks
Corporate success requires taking fewer risks.
Risks can cause dismissal. Risks can interrupt business. Keep things moving so you may keep getting paid your enormous salary and bonus.
Restructuring or layoffs are inevitable. All corporate climbers experience it.
On this fateful day, a small few realize the game they’ve been trapped in and escape. Most return to play for a new company, but it takes time.
Addiction keeps them trapped. You know nothing else. The rest is strange.
You start to think “I’m getting old” or “it’s nearly retirement.” So you settle yet again for the trappings of the corporate ladder game to nowhere.
Should you climb the corporate ladder?
Let me end on a surprising note.
Young people should ascend the corporate ladder. It teaches you business skills and helps support your side gig and (potential) online business.
Don't get trapped, shackled, or muzzled.
Your ideas and creativity become stifled after too much gaming play.
Corporate success won't bring happiness.
Find fulfilling employment that matters. That's it.
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Max Parasol
3 years ago
What the hell is Web3 anyway?
"Web 3.0" is a trendy buzzword with a vague definition. Everyone agrees it has to do with a blockchain-based internet evolution, but what is it?
Yet, the meaning and prospects for Web3 have become hot topics in crypto communities. Big corporations use the term to gain a foothold in the space while avoiding the negative connotations of “crypto.”
But it can't be evaluated without a definition.
Among those criticizing Web3's vagueness is Cobie:
“Despite the dominie's deluge of undistinguished think pieces, nobody really agrees on what Web3 is. Web3 is a scam, the future, tokenizing the world, VC exit liquidity, or just another name for crypto, depending on your tribe.
“Even the crypto community is split on whether Bitcoin is Web3,” he adds.
The phrase was coined by an early crypto thinker, and the community has had years to figure out what it means. Many ideologies and commercial realities have driven reverse engineering.
Web3 is becoming clearer as a concept. It contains ideas. It was probably coined by Ethereum co-founder Gavin Wood in 2014. His definition of Web3 included “trustless transactions” as part of its tech stack. Wood founded the Web3 Foundation and the Polkadot network, a Web3 alternative future.
The 2013 Ethereum white paper had previously allowed devotees to imagine a DAO, for example.
Web3 now has concepts like decentralized autonomous organizations, sovereign digital identity, censorship-free data storage, and data divided by multiple servers. They intertwine discussions about the “Web3” movement and its viability.
These ideas are linked by Cobie's initial Web3 definition. A key component of Web3 should be “ownership of value” for one's own content and data.
Noting that “late-stage capitalism greedcorps that make you buy a fractionalized micropayment NFT on Cardano to operate your electric toothbrush” may build the new web, he notes that “crypto founders are too rich to care anymore.”
Very Important
Many critics of Web3 claim it isn't practical or achievable. Web3 critics like Moxie Marlinspike (creator of sslstrip and Signal/TextSecure) can never see people running their own servers. Early in January, he argued that protocols are more difficult to create than platforms.
While this is true, some projects, like the file storage protocol IPFS, allow users to choose which jurisdictions their data is shared between.
But full decentralization is a difficult problem. Suhaza, replying to Moxie, said:
”People don't want to run servers... Companies are now offering API access to an Ethereum node as a service... Almost all DApps interact with the blockchain using Infura or Alchemy. In fact, when a DApp uses a wallet like MetaMask to interact with the blockchain, MetaMask is just calling Infura!
So, here are the questions: Web3: Is it a go? Is it truly decentralized?
Web3 history is shaped by Web2 failure.
This is the story of how the Internet was turned upside down...
Then came the vision. Everyone can create content for free. Decentralized open-source believers like Tim Berners-Lee popularized it.
Real-world data trade-offs for content creation and pricing.
A giant Wikipedia page married to a giant Craig's List. No ads, no logins, and a private web carve-up. For free usage, you give up your privacy and data to the algorithmic targeted advertising of Web 2.
Our data is centralized and savaged by giant corporations. Data localization rules and geopolitical walls like China's Great Firewall further fragment the internet.
The decentralized Web3 reflects Berners-original Lee's vision: "No permission is required from a central authority to post anything... there is no central controlling node and thus no single point of failure." Now he runs Solid, a Web3 data storage startup.
So Web3 starts with decentralized servers and data privacy.
Web3 begins with decentralized storage.
Data decentralization is a key feature of the Web3 tech stack. Web2 has closed databases. Large corporations like Facebook, Google, and others go to great lengths to collect, control, and monetize data. We want to change it.
Amazon, Google, Microsoft, Alibaba, and Huawei, according to Gartner, currently control 80% of the global cloud infrastructure market. Web3 wants to change that.
Decentralization enlarges power structures by giving participants a stake in the network. Users own data on open encrypted networks in Web3. This area has many projects.
Apps like Filecoin and IPFS have led the way. Data is replicated across multiple nodes in Web3 storage providers like Filecoin.
But the new tech stack and ideology raise many questions.
Giving users control over their data
According to Ryan Kris, COO of Verida, his “Web3 vision” is “empowering people to control their own data.”
Verida targets SDKs that address issues in the Web3 stack: identity, messaging, personal storage, and data interoperability.
A big app suite? “Yes, but it's a frontier technology,” he says. They are currently building a credentialing system for decentralized health in Bermuda.
By empowering individuals, how will Web3 create a fairer internet? Kris, who has worked in telecoms, finance, cyber security, and blockchain consulting for decades, admits it is difficult:
“The viability of Web3 raises some good business questions,” he adds. “How can users regain control over centralized personal data? How are startups motivated to build products and tools that support this transition? How are existing Web2 companies encouraged to pivot to a Web3 business model to compete with market leaders?
Kris adds that new technologies have regulatory and practical issues:
"On storage, IPFS is great for redundantly sharing public data, but not designed for securing private personal data. It is not controlled by the users. When data storage in a specific country is not guaranteed, regulatory issues arise."
Each project has varying degrees of decentralization. The diehards say DApps that use centralized storage are no longer “Web3” companies. But fully decentralized technology is hard to build.
Web2.5?
Some argue that we're actually building Web2.5 businesses, which are crypto-native but not fully decentralized. This is vital. For example, the NFT may be on a blockchain, but it is linked to centralized data repositories like OpenSea. A server failure could result in data loss.
However, according to Apollo Capital crypto analyst David Angliss, OpenSea is “not exactly community-led”. Also in 2021, much to the chagrin of crypto enthusiasts, OpenSea tried and failed to list on the Nasdaq.
This is where Web2.5 is defined.
“Web3 isn't a crypto segment. “Anything that uses a blockchain for censorship resistance is Web3,” Angliss tells us.
“Web3 gives users control over their data and identity. This is not possible in Web2.”
“Web2 is like feudalism, with walled-off ecosystems ruled by a few. For example, an honest user owned the Instagram account “Meta,” which Facebook rebranded and then had to make up a reason to suspend. Not anymore with Web3. If I buy ‘Ethereum.ens,' Ethereum cannot take it away from me.”
Angliss uses OpenSea as a Web2.5 business example. Too decentralized, i.e. censorship resistant, can be unprofitable for a large company like OpenSea. For example, OpenSea “enables NFT trading”. But it also stopped the sale of stolen Bored Apes.”
Web3 (or Web2.5, depending on the context) has been described as a new way to privatize internet.
“Being in the crypto ecosystem doesn't make it Web3,” Angliss says. The biggest risk is centralized closed ecosystems rather than a growing Web3.
LooksRare and OpenDAO are two community-led platforms that are more decentralized than OpenSea. LooksRare has even been “vampire attacking” OpenSea, indicating a Web3 competitor to the Web2.5 NFT king could find favor.
The addition of a token gives these new NFT platforms more options for building customer loyalty. For example, OpenSea charges a fee that goes nowhere. Stakeholders of LOOKS tokens earn 100% of the trading fees charged by LooksRare on every basic sale.
Maybe Web3's time has come.
So whose data is it?
Continuing criticisms of Web3 platforms' decentralization may indicate we're too early. Users want to own and store their in-game assets and NFTs on decentralized platforms like the Metaverse and play-to-earn games. Start-ups like Arweave, Sia, and Aleph.im propose an alternative.
To be truly decentralized, Web3 requires new off-chain models that sidestep cloud computing and Web2.5.
“Arweave and Sia emerged as formidable competitors this year,” says the Messari Report. They seek to reduce the risk of an NFT being lost due to a data breach on a centralized server.
Aleph.im, another Web3 cloud competitor, seeks to replace cloud computing with a service network. It is a decentralized computing network that supports multiple blockchains by retrieving and encrypting data.
“The Aleph.im network provides a truly decentralized alternative where it is most needed: storage and computing,” says Johnathan Schemoul, founder of Aleph.im. For reasons of consensus and security, blockchains are not designed for large storage or high-performance computing.
As a result, large data sets are frequently stored off-chain, increasing the risk for centralized databases like OpenSea
Aleph.im enables users to own digital assets using both blockchains and off-chain decentralized cloud technologies.
"We need to go beyond layer 0 and 1 to build a robust decentralized web. The Aleph.im ecosystem is proving that Web3 can be decentralized, and we intend to keep going.”
Aleph.im raised $10 million in mid-January 2022, and Ubisoft uses its network for NFT storage. This is the first time a big-budget gaming studio has given users this much control.
It also suggests Web3 could work as a B2B model, even if consumers aren't concerned about “decentralization.” Starting with gaming is common.
Can Tokenomics help Web3 adoption?
Web3 consumer adoption is another story. The average user may not be interested in all this decentralization talk. Still, how much do people value privacy over convenience? Can tokenomics solve the privacy vs. convenience dilemma?
Holon Global Investments' Jonathan Hooker tells us that human internet behavior will change. “Do you own Bitcoin?” he asks in his Web3 explanation. How does it feel to own and control your own sovereign wealth? Then:
“What if you could own and control your data like Bitcoin?”
“The business model must find what that person values,” he says. Putting their own health records on centralized systems they don't control?
“How vital are those medical records to that person at a critical time anywhere in the world? Filecoin and IPFS can help.”
Web3 adoption depends on NFT storage competition. A free off-chain storage of NFT metadata and assets was launched by Filecoin in April 2021.
Denationalization and blockchain technology have significant implications for data ownership and compensation for lending, staking, and using data.
Tokenomics can change human behavior, but many people simply sign into Web2 apps using a Facebook API without hesitation. Our data is already owned by Google, Baidu, Tencent, and Facebook (and its parent company Meta). Is it too late to recover?
Maybe. “Data is like fruit, it starts out fresh but ages,” he says. "Big Tech's data on us will expire."
Web3 founder Kris agrees with Hooker that “value for data is the issue, not privacy.” People accept losing their data privacy, so tokenize it. People readily give up data, so why not pay for it?
"Personalized data offering is valuable in personalization. “I will sell my social media data but not my health data.”
Purists and mass consumer adoption struggle with key management.
Others question data tokenomics' optimism. While acknowledging its potential, Box founder Aaron Levie questioned the viability of Web3 models in a Tweet thread:
“Why? Because data almost always works in an app. A product and APIs that moved quickly to build value and trust over time.”
Levie contends that tokenomics may complicate matters. In addition to community governance and tokenomics, Web3 ideals likely add a new negotiation vector.
“These are hard problems about human coordination, not software or blockchains,”. Using a Facebook API is simple. The business model and user interface are crucial.
For example, the crypto faithful have a common misconception about logging into Web3. It goes like this: Web 1 had usernames and passwords. Web 2 uses Google, Facebook, or Twitter APIs, while Web 3 uses your wallet. Pay with Ethereum on MetaMask, for example.
But Levie is correct. Blockchain key management is stressed in this meme. Even seasoned crypto enthusiasts have heart attacks, let alone newbies.
Web3 requires a better user experience, according to Kris, the company's founder. “How does a user recover keys?”
And at this point, no solution is likely to be completely decentralized. So Web3 key management can be improved. ”The moment someone loses control of their keys, Web3 ceases to exist.”
That leaves a major issue for Web3 purists. Put this one in the too-hard basket.
Is 2022 the Year of Web3?
Web3 must first solve a number of issues before it can be mainstreamed. It must be better and cheaper than Web2.5, or have other significant advantages.
Web3 aims for scalability without sacrificing decentralization protocols. But decentralization is difficult and centralized services are more convenient.
Ethereum co-founder Vitalik Buterin himself stated recently"
This is why (centralized) Binance to Binance transactions trump Ethereum payments in some places because they don't have to be verified 12 times."
“I do think a lot of people care about decentralization, but they're not going to take decentralization if decentralization costs $8 per transaction,” he continued.
“Blockchains need to be affordable for people to use them in mainstream applications... Not for 2014 whales, but for today's users."
For now, scalability, tokenomics, mainstream adoption, and decentralization believers seem to be holding Web3 hostage.
Much like crypto's past.
But stay tuned.
Aldric Chen
3 years ago
Jack Dorsey's Meeting Best Practice was something I tried. It Performs Exceptionally Well in Consulting Engagements.
Yes, client meetings are difficult. Especially when I'm alone.
Clients must tell us their problems so we can help.
In-meeting challenges contribute nothing to our work. Consider this:
Clients are unprepared.
Clients are distracted.
Clients are confused.
Introducing Jack Dorsey's Google Doc approach
I endorse his approach to meetings.
Not Google Doc-related. Jack uses it for meetings.
This is what his meetings look like.
Prior to the meeting, the Chair creates the agenda, structure, and information using Google Doc.
Participants in the meeting would have 5-10 minutes to read the Google Doc.
They have 5-10 minutes to type their comments on the document.
In-depth discussion begins
There is elegance in simplicity. Here's how Jack's approach is fantastic.
Unprepared clients are given time to read.
During the meeting, they think and work on it.
They can see real-time remarks from others.
Discussion ensues.
Three months ago, I fell for this strategy. After trying it with a client, I got good results.
I conducted social control experiments in a few client workshops.
Context matters.
I am sure Jack Dorsey’s method works well in meetings. What about client workshops?
So, I tested Enterprise of the Future with a consulting client.
I sent multiple emails to client stakeholders describing the new approach.
No PowerPoints that day. I spent the night setting up the Google Doc with conversation topics, critical thinking questions, and a Before and After section.
The client was shocked. First, a Google Doc was projected. Second surprise was a verbal feedback.
“No pre-meeting materials?”
“Don’t worry. I know you are not reading it before our meeting, anyway.”
We laughed. The experiment started.
Observations throughout a 90-minute engagement workshop from beginning to end
For 10 minutes, the workshop was silent.
People read the Google Doc. For some, the silence was unnerving.
“Are you not going to present anything to us?”
I said everything's in Google Doc. I asked them to read, remark, and add relevant paragraphs.
As they unlocked their laptops, they were annoyed.
Ten client stakeholders are typing on the Google Doc. My laptop displays comment bubbles, red lines, new paragraphs, and strikethroughs.
The first 10 minutes were productive. Everyone has seen and contributed to the document.
I was silent.
The move to a classical workshop was smooth. I didn't stimulate dialogue. They did.
Stephanie asked Joe why a blended workforce hinders company productivity. She questioned his comments and additional paragraphs.
That is when a light bulb hit my head. Yes, you want to speak to the right person to resolve issues!
Not only that was discussed. Others discussed their remark bubbles with neighbors. Debate circles sprung up one after the other.
The best part? I asked everyone to add their post-discussion thoughts on a Google Doc.
After the workshop, I have:
An agreement-based working document
A post-discussion minutes that are prepared for publication
A record of the discussion points that were brought up, argued, and evaluated critically
It showed me how stakeholders viewed their Enterprise of the Future. It allowed me to align with them.
Finale Keynotes
Client meetings are a hit-or-miss. I know that.
Jack Dorsey's meeting strategy works for consulting. It promotes session alignment.
It relieves clients of preparation.
I get the necessary information to advance this consulting engagement.
It is brilliant.
Max Chafkin
3 years ago
Elon Musk Bets $44 Billion on Free Speech's Future
Musk’s purchase of Twitter has sealed his bond with the American right—whether the platform’s left-leaning employees and users like it or not.
Elon Musk's pursuit of Twitter Inc. began earlier this month as a joke. It started slowly, then spiraled out of control, culminating on April 25 with the world's richest man agreeing to spend $44 billion on one of the most politically significant technology companies ever. There have been bigger financial acquisitions, but Twitter's significance has always outpaced its balance sheet. This is a unique Silicon Valley deal.
To recap: Musk announced in early April that he had bought a stake in Twitter, citing the company's alleged suppression of free speech. His complaints were vague, relying heavily on the dog whistles of the ultra-right. A week later, he announced he'd buy the company for $54.20 per share, four days after initially pledging to join Twitter's board. Twitter's directors noticed the 420 reference as well, and responded with a “shareholder rights” plan (i.e., a poison pill) that included a 420 joke.
Musk - Patrick Pleul/Getty Images
No one knew if the bid was genuine. Musk's Twitter plans seemed implausible or insincere. In a tweet, he referred to automated accounts that use his name to promote cryptocurrency. He enraged his prospective employees by suggesting that Twitter's San Francisco headquarters be turned into a homeless shelter, renaming the company Titter, and expressing solidarity with his growing conservative fan base. “The woke mind virus is making Netflix unwatchable,” he tweeted on April 19.
But Musk got funding, and after a frantic weekend of negotiations, Twitter said yes. Unlike most buyouts, Musk will personally fund the deal, putting up up to $21 billion in cash and borrowing another $12.5 billion against his Tesla stock.
Free Speech and Partisanship
Percentage of respondents who agree with the following
The deal is expected to replatform accounts that were banned by Twitter for harassing others, spreading misinformation, or inciting violence, such as former President Donald Trump's account. As a result, Musk is at odds with his own left-leaning employees, users, and advertisers, who would prefer more content moderation rather than less.
Dorsey - Photographer: Joe Raedle/Getty Images
Previously, the company's leadership had similar issues. Founder Jack Dorsey stepped down last year amid concerns about slowing growth and product development, as well as his dual role as CEO of payments processor Block Inc. Compared to Musk, a father of seven who already runs four companies (besides Tesla and SpaceX), Dorsey is laser-focused.
Musk's motivation to buy Twitter may be political. Affirming the American far right with $44 billion spent on “free speech” Right-wing activists have promoted a series of competing upstart Twitter competitors—Parler, Gettr, and Trump's own effort, Truth Social—since Trump was banned from major social media platforms for encouraging rioters at the US Capitol on Jan. 6, 2021. But Musk can give them a social network with lax content moderation and a real user base. Trump said he wouldn't return to Twitter after the deal was announced, but he wouldn't be the first to do so.
Trump - Eli Hiller/Bloomberg
Conservative activists and lawmakers are already ecstatic. “A great day for free speech in America,” said Missouri Republican Josh Hawley. The day the deal was announced, Tucker Carlson opened his nightly Fox show with a 10-minute laudatory monologue. “The single biggest political development since Donald Trump's election in 2016,” he gushed over Musk.
But Musk's supporters and detractors misunderstand how much his business interests influence his political ideology. He marketed Tesla's cars as carbon-saving machines that were faster and cooler than gas-powered luxury cars during George W. Bush's presidency. Musk gained a huge following among wealthy environmentalists who reserved hundreds of thousands of Tesla sedans years before they were made during Barack Obama's presidency. Musk in the Trump era advocated for a carbon tax, but he also fought local officials (and his own workers) over Covid rules that slowed the reopening of his Bay Area factory.
Teslas at the Las Vegas Convention Center Loop Central Station in April 2021. The Las Vegas Convention Center Loop was Musk's first commercial project. Ethan Miller/Getty Images
Musk's rightward shift matched the rise of the nationalist-populist right and the desire to serve a growing EV market. In 2019, he unveiled the Cybertruck, a Tesla pickup, and in 2018, he announced plans to manufacture it at a new plant outside Austin. In 2021, he decided to move Tesla's headquarters there, citing California's "land of over-regulation." After Ford and General Motors beat him to the electric truck market, Musk reframed Tesla as a company for pickup-driving dudes.
Similarly, his purchase of Twitter will be entwined with his other business interests. Tesla has a factory in China and is friendly with Beijing. This could be seen as a conflict of interest when Musk's Twitter decides how to treat Chinese-backed disinformation, as Amazon.com Inc. founder Jeff Bezos noted.
Musk has focused on Twitter's product and social impact, but the company's biggest challenges are financial: Either increase cash flow or cut costs to comfortably service his new debt. Even if Musk can't do that, he can still benefit from the deal. He has recently used the increased attention to promote other business interests: Boring has hyperloops and Neuralink brain implants on the way, Musk tweeted. Remember Tesla's long-promised robotaxis!
Musk may be comfortable saying he has no expectation of profit because it benefits his other businesses. At the TED conference on April 14, Musk insisted that his interest in Twitter was solely charitable. “I don't care about money.”
The rockets and weed jokes make it easy to see Musk as unique—and his crazy buyout will undoubtedly add to that narrative. However, he is a megabillionaire who is risking a small amount of money (approximately 13% of his net worth) to gain potentially enormous influence. Musk makes everything seem new, but this is a rehash of an old media story.