More on Personal Growth

Scott Stockdale
3 years ago
A Day in the Life of Lex Fridman Can Help You Hit 6-Month Goals
The Lex Fridman podcast host has interviewed Elon Musk.
Lex is a minimalist YouTuber. His videos are sloppy. Suits are his trademark.
In a video, he shares a typical day. I've smashed my 6-month goals using its ideas.
Here's his schedule.
Morning Mantra
Not woo-woo. Lex's mantra reflects his practicality.
Four parts.
Rulebook
"I remember the game's rules," he says.
Among them:
Sleeping 6–8 hours nightly
1–3 times a day, he checks social media.
Every day, despite pain, he exercises. "I exercise uninjured body parts."
Visualize
He imagines his day. "Like Sims..."
He says three things he's grateful for and contemplates death.
"Today may be my last"
Objectives
Then he visualizes his goals. He starts big. Five-year goals.
Short-term goals follow. Lex says they're year-end goals.
Near but out of reach.
Principles
He lists his principles. Assertions. His goals.
He acknowledges his cliche beliefs. Compassion, empathy, and strength are key.
Here's my mantra routine:
Four-Hour Deep Work
Lex begins a four-hour deep work session after his mantra routine. Today's toughest.
AI is Lex's specialty. His video doesn't explain what he does.
Clearly, he works hard.
Before starting, he has water, coffee, and a bathroom break.
"During deep work sessions, I minimize breaks."
He's distraction-free. Phoneless. Silence. Nothing. Any loose ideas are typed into a Google doc for later. He wants to work.
"Just get the job done. Don’t think about it too much and feel good once it’s complete." — Lex Fridman
30-Minute Social Media & Music
After his first deep work session, Lex rewards himself.
10 minutes on social media, 20 on music. Upload content and respond to comments in 10 minutes. 20 minutes for guitar or piano.
"In the real world, I’m currently single, but in the music world, I’m in an open relationship with this beautiful guitar. Open relationship because sometimes I cheat on her with the acoustic." — Lex Fridman
Two-hour exercise
Then exercise for two hours.
Daily runs six miles. Then he chooses how far to go. Run time is an hour.
He does bodyweight exercises. Every minute for 15 minutes, do five pull-ups and ten push-ups. It's David Goggins-inspired. He aims for an hour a day.
He's hungry. Before running, he takes a salt pill for electrolytes.
He'll then take a one-minute cold shower while listening to cheesy songs. Afterward, he might eat.
Four-Hour Deep Work
Lex's second work session.
He works 8 hours a day.
Again, zero distractions.
Eating
The video's meal doesn't look appetizing, but it's healthy.
It's ground beef with vegetables. Cauliflower is his "ground-floor" veggie. "Carrots are my go-to party food."
Lex's keto diet includes 1800–2000 calories.
He drinks a "nutrient-packed" Atheltic Greens shake and takes tablets. It's:
One daily tablet of sodium.
Magnesium glycinate tablets stopped his keto headaches.
Potassium — "For electrolytes"
Fish oil: healthy joints
“So much of nutrition science is barely a science… I like to listen to my own body and do a one-person, one-subject scientific experiment to feel good.” — Lex Fridman
Four-hour shallow session
This work isn't as mentally taxing.
Lex planned to:
Finish last session's deep work (about an hour)
Adobe Premiere podcasting (about two hours).
Email-check (about an hour). Three times a day max. First, check for emergencies.
If he's sick, he may watch Netflix or YouTube documentaries or visit friends.
“The possibilities of chaos are wide open, so I can do whatever the hell I want.” — Lex Fridman
Two-hour evening reading
Nonstop work.
Lex ends the day reading academic papers for an hour. "Today I'm skimming two machine learning and neuroscience papers"
This helps him "think beyond the paper."
He reads for an hour.
“When I have a lot of energy, I just chill on the bed and read… When I’m feeling tired, I jump to the desk…” — Lex Fridman
Takeaways
Lex's day-in-the-life video is inspiring.
He has positive energy and works hard every day.
Schedule:
Mantra Routine includes rules, visualizing, goals, and principles.
Deep Work Session #1: Four hours of focus.
10 minutes social media, 20 minutes guitar or piano. "Music brings me joy"
Six-mile run, then bodyweight workout. Two hours total.
Deep Work #2: Four hours with no distractions. Google Docs stores random thoughts.
Lex supplements his keto diet.
This four-hour session is "open to chaos."
Evening reading: academic papers followed by fiction.
"I value some things in life. Work is one. The other is loving others. With those two things, life is great." — Lex Fridman

Nitin Sharma
2 years ago
Quietly Create a side business that will revolutionize everything in a year.
Quitting your job for a side gig isn't smart.
A few years ago, I would have laughed at the idea of starting a side business.
I never thought a side gig could earn more than my 9-to-5. My side gig pays more than my main job now.
You may then tell me to leave your job. But I don't want to gamble, and my side gig is important. Programming and web development help me write better because of my job.
Yes, I share work-related knowledge. Web development, web3, programming, money, investment, and side hustles are key.
Let me now show you how to make one.
Create a side business based on your profession or your interests.
I'd be direct.
Most people don't know where to start or which side business to pursue.
You can make money by taking online surveys, starting a YouTube channel, or playing web3 games, according to several blogs.
You won't make enough money and will waste time.
Nitin directs our efforts. My friend, you've worked and have talent. Profit from your talent.
Example:
College taught me web development. I soon created websites, freelanced, and made money. First year was hardest for me financially and personally.
As I worked, I became more skilled. Soon after, I got more work, wrote about web development on Medium, and started selling products.
I've built multiple income streams from web development. It wasn't easy. Web development skills got me a 9-to-5 job.
Focus on a specific skill and earn money in many ways. Most people start with something they hate or are bad at; the rest is predictable.
Result? They give up, frustrated.
Quietly focus for a year.
I started my side business in college and never told anyone. My parents didn't know what I did for fun.
The only motivation is time constraints. So I focused.
As I've said, I focused on my strengths (learned skills) and made money. Yes, I was among Medium's top 500 authors in a year and got a bonus.
How did I succeed? Since I know success takes time, I never imagined making enough money in a month. I spent a year concentrating.
I became wealthy. Now that I have multiple income sources, some businesses pay me based on my skill.
I recommend learning skills and working quietly for a year. You can do anything with this.
The hardest part will always be the beginning.
When someone says you can make more money working four hours a week. Leave that, it's bad advice.
If someone recommends a paid course to help you succeed, think twice.
The beginning is always the hardest.
I made many mistakes learning web development. When I started my technical content side gig, it was tough. I made mistakes and changed how I create content, which helped.
And it’s applicable everywhere.
Don't worry if you face problems at first. Time and effort heal all wounds.
Quitting your job to work a side job is not a good idea.
Some honest opinions.
Most online gurus encourage side businesses. It takes time to start and grow a side business.
Suppose you quit and started a side business.
After six months, what happens? Your side business won't provide enough money to survive.
Indeed. Later, you'll become demotivated and tense and look for work.
Instead, work 9-5, and start a side business. You decide. Stop watching Netflix and focus on your side business.
I know you're busy, but do it.
Next? It'll succeed or fail in six months. You can continue your side gig for another six months because you have a job and have tried it.
You'll probably make money, but you may need to change your side gig.
That’s it.
You've created a new revenue stream.
Remember.
Starting a side business, a company, or finding work is difficult. There's no free money in a competitive world. You'll only succeed with skill.
Read it again.
Focusing silently for a year can help you succeed.
I studied web development and wrote about it. First year was tough. I went viral, hit the top 500, and other firms asked me to write for them. So, my life changed.
Yours can too. One year of silence is required.
Enjoy!

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.
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Jano le Roux
3 years ago
Never Heard Of: The Apple Of Email Marketing Tools
Unlimited everything for $19 monthly!?
Even with pretty words, no one wants to read an ugly email.
Not Gen Z
Not Millennials
Not Gen X
Not Boomers
I am a minimalist.
I like Mozart. I like avos. I love Apple.
When I hear seamlessly, effortlessly, or Apple's new adverb fluidly, my toes curl.
No email marketing tool gave me that feeling.
As a marketing consultant helping high-growth brands create marketing that doesn't feel like marketing, I've worked with every email marketing platform imaginable, including that naughty monkey and the expensive platform whose sales teams don't stop calling.
Most email marketing platforms are flawed.
They are overpriced.
They use dreadful templates.
They employ a poor visual designer.
The user experience there is awful.
Too many useless buttons are present. (Similar to the TV remote!)
I may have finally found the perfect email marketing tool. It creates strong flows. It helps me focus on storytelling.
It’s called Flodesk.
It’s effortless. It’s seamless. It’s fluid.
Here’s why it excites me.
Unlimited everything for $19 per month
Sends unlimited. Emails unlimited. Signups unlimited.
Most email platforms penalize success.
Pay for performance?
$87 for 10k contacts
$605 for 100K contacts
$1,300+ for 200K contacts
In the 1990s, this made sense, but not now. It reminds me of when ISPs capped internet usage at 5 GB per month.
Flodesk made unlimited email for a low price a reality. Affordable, attractive email marketing isn't just for big companies.
Flodesk doesn't penalize you for growing your list. Price stays the same as lists grow.
Flodesk plans cost $38 per month, but I'll give you a 30-day trial for $19.
Amazingly strong flows
Foster different people's flows.
Email marketing isn't one-size-fits-all.
Different times require different emails.
People don't open emails because they're irrelevant, in my experience. A colder audience needs a nurturing sequence.
Flodesk automates your email funnels so top-funnel prospects fall in love with your brand and values before mid- and bottom-funnel email flows nudge them to take action.
I wish I could save more custom audience fields to further customize the experience.
Dynamic editor
Easy. Effortless.
Flodesk's editor is Apple-like.
You understand how it works almost instantly.
Like many Apple products, it's intentionally limited. No distractions. You can focus on emotional email writing.
Flodesk's inability to add inline HTML to emails is my biggest issue with larger projects. I wish I could upload HTML emails.
Simple sign-up procedures
Dream up joining.
I like how easy it is to create conversion-focused landing pages. Linkly lets you easily create 5 landing pages and A/B test messaging.
I like that you can use signup forms to ask people what they're interested in so they get relevant emails instead of mindless mass emails nobody opens.
I love how easy it is to embed in-line on a website.
Wonderful designer templates
Beautiful, connecting emails.
Flodesk has calm email templates. My designer's eye felt at rest when I received plain text emails with big impacts.
As a typography nerd, I love Flodesk's handpicked designer fonts. It gives emails a designer feel that is hard to replicate on other platforms without coding and custom font licenses.
Small adjustments can have a big impact
Details matter.
Flodesk remembers your brand colors. Flodesk automatically adds your logo and social handles to emails after signup.
Flodesk uses Zapier. This lets you send emails based on a user's action.
A bad live chat can trigger a series of emails to win back a customer.
Flodesk isn't for everyone.
Flodesk is great for Apple users like me.

Waleed Rikab, PhD
2 years ago
The Enablement of Fraud and Misinformation by Generative AI What You Should Understand
Recent investigations have shown that generative AI can boost hackers and misinformation spreaders.
Since its inception in late November 2022, OpenAI's ChatGPT has entertained and assisted many online users in writing, coding, task automation, and linguistic translation. Given this versatility, it is maybe unsurprising but nonetheless regrettable that fraudsters and mis-, dis-, and malinformation (MDM) spreaders are also considering ChatGPT and related AI models to streamline and improve their operations.
Malign actors may benefit from ChatGPT, according to a WithSecure research. ChatGPT promises to elevate unlawful operations across many attack channels. ChatGPT can automate spear phishing attacks that deceive corporate victims into reading emails from trusted parties. Malware, extortion, and illicit fund transfers can result from such access.
ChatGPT's ability to simulate a desired writing style makes spear phishing emails look more genuine, especially for international actors who don't speak English (or other languages like Spanish and French).
This technique could let Russian, North Korean, and Iranian state-backed hackers conduct more convincing social engineering and election intervention in the US. ChatGPT can also create several campaigns and various phony online personas to promote them, making such attacks successful through volume or variation. Additionally, image-generating AI algorithms and other developing techniques can help these efforts deceive potential victims.
Hackers are discussing using ChatGPT to install malware and steal data, according to a Check Point research. Though ChatGPT's scripts are well-known in the cyber security business, they can assist amateur actors with little technical understanding into the field and possibly develop their hacking and social engineering skills through repeated use.
Additionally, ChatGPT's hacking suggestions may change. As a writer recently indicated, ChatGPT's ability to blend textual and code-based writing might be a game-changer, allowing the injection of innocent content that would subsequently turn out to be a malicious script into targeted systems. These new AI-powered writing- and code-generation abilities allow for unique cyber attacks, regardless of viability.
OpenAI fears ChatGPT usage. OpenAI, Georgetown University's Center for Security and Emerging Technology, and Stanford's Internet Observatory wrote a paper on how AI language models could enhance nation state-backed influence operations. As a last resort, the authors consider polluting the internet with radioactive or misleading data to ensure that AI language models produce outputs that other language models can identify as AI-generated. However, the authors of this paper seem unaware that their "solution" might cause much worse MDM difficulties.
Literally False News
The public argument about ChatGPTs content-generation has focused on originality, bias, and academic honesty, but broader global issues are at stake. ChatGPT can influence public opinion, troll individuals, and interfere in local and national elections by creating and automating enormous amounts of social media material for specified audiences.
ChatGPT's capacity to generate textual and code output is crucial. ChatGPT can write Python scripts for social media bots and give diverse content for repeated posts. The tool's sophistication makes it irrelevant to one's language skills, especially English, when writing MDM propaganda.
I ordered ChatGPT to write a news piece in the style of big US publications declaring that Ukraine is on the verge of defeat in its fight against Russia due to corruption, desertion, and exhaustion in its army. I also gave it a fake reporter's byline and an unidentified NATO source's remark. The outcome appears convincing:
Worse, terrible performers can modify this piece to make it more credible. They can edit the general's name or add facts about current wars. Furthermore, such actors can create many versions of this report in different forms and distribute them separately, boosting its impact.
In this example, ChatGPT produced a news story regarding (fictional) greater moviegoer fatality rates:
Editing this example makes it more plausible. Dr. Jane Smith, the putative author of the medical report, might be replaced with a real-life medical person or a real victim of this supposed medical hazard.
Can deceptive texts be found? Detecting AI text is behind AI advancements. Minor AI-generated text alterations can upset these technologies.
Some OpenAI individuals have proposed covert methods to watermark AI-generated literature to prevent its abuse. AI models would create information that appears normal to humans but would follow a cryptographic formula that would warn other machines that it was AI-made. However, security experts are cautious since manually altering the content interrupts machine and human detection of AI-generated material.
How to Prepare
Cyber security and IT workers can research and use generative AI models to fight spear fishing and extortion. Governments may also launch MDM-defence projects.
In election cycles and global crises, regular people may be the most vulnerable to AI-produced deceit. Until regulation or subsequent technical advances, individuals must recognize exposure to AI-generated fraud, dating scams, other MDM activities.
A three-step verification method of new material in suspicious emails or social media posts can help identify AI content and manipulation. This three-step approach asks about the information's distribution platform (is it reliable? ), author (is the reader familiar with them? ), and plausibility given one's prior knowledge of the topic.
Consider a report by a trusted journalist that makes shocking statements in their typical manner. AI-powered fake news may be released on an unexpected platform, such as a newly created Facebook profile. However, if it links to a known media source, it is more likely to be real.
Though hard and subjective, this verification method may be the only barrier against manipulation for now.
AI language models:
How to Recognize an AI-Generated Article ChatGPT, the popular AI-powered chatbot, can and likely does generate medium.com-style articles.
AI-Generated Text Detectors Fail. Do This. Online tools claim to detect ChatGPT output. Even with superior programming, I tested some of these tools. pub
Why Original Writers Matter Despite AI Language Models Creative writers may never be threatened by AI language models.

Pen Magnet
3 years ago
Why Google Staff Doesn't Work
Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.
To boost employee efficiency.
Not surprising. Few envisioned Google declaring a productivity drive.
Sunder Pichai's speech:
“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”
The primary driver driving Google's efficiency push is:
Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.
Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.
Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.
Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.
In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.
FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.
Google has hardly ever discussed effectiveness:
Apparently openly.
Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.
Amazon trumps Google. In reality, it treats its employees poorly.
Google was the founding father of the modern-day open culture.
Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.
20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.
After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.
Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?
If so, would Google follow suit?
If so, how does Google go about doing it?
Before discussing Google's likely plan, let's examine programming productivity.
What determines a programmer's productivity is simple:
How would we answer Google's questions?
As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.
Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.
Deconstruct our main question.
How exactly do you change the culture of the firm so that productivity increases?
How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.
How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)
How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?
When implementing a large-scale organizational change, success must be carefully measured.
The fastest way to do something is to do it right, no matter how long it takes.
You require clearly-defined group/team/role segregation and solid pass/fail matrices to:
You can give performers rewards.
Ones that are average can be inspired to improve
Underachievers may receive assistance or, in the worst-case scenario, rehabilitation
As a 20-year programmer, I associate productivity with greatness.
Doing something well, no matter how long it takes, is the fastest way to do it.
Let's discuss a programmer's productivity.
Why productivity is a strange term in programming:
Productivity is work per unit of time.
Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.
As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.
All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.
Time is money — is not just a proverb, but an economical fact.
Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.
Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.
Programming productivity isn't linear, unlike manufacturing and maintenance.
Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.
Reversing the programming duties has no effect. Experts aren't needed for productivity.
These patterns remind me of an XKCD comic.
Programming productivity depends on two factors:
The capacity of the programmer and his or her command of the principles of computer science
His or her productive bursts, how often they occur, and how long they last as they engineer the answer
At some point, productivity measurement becomes Schrödinger’s cat.
Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.
Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.
Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.
Google can pull it off if it wants to.
What Google meant in reality when it said that employee productivity has decreased:
When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.
They can't multiply their work's influence over time.
Programmers who produce excellent modules or products are unsure on how to use them.
The best data scientists are unable to add the proper parameters in their models.
Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.
Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.
Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.
So, Google employees aren't productive.
How to fix it?
Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.
SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.
Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.
Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.
Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).
In conclusion:
Software development isn't linear. Why should the makers be measured?
Notation for The Big O
I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)
The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)
Google (or any large corporation) can do this.
Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.
Plot the influence of each employee over time using the X and Y axes, respectively.
Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).
Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.
After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.
Example of a Big(O) Category:
If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.
The Google interview truth:
O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.
O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.
CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.
Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.
UX/UI Designers must still prototype UI elements despite improved design tools.
All test cases are proportional to use cases/functional units, hence testers' work is O(N).
Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.
Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.
Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.
The fastest way to do something is to do it right, no matter how long it takes.
Conclusion:
Google is at the liberal extreme of the employee-handling spectrum
Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.
Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.
Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.
Any attempt to redefine people's measurements will affect the organization emotionally.
The more Google compares apples to apples, the higher its chances for future rebirth.
