Writers' rooms, improv, and lessons from Tim Burton | Wendy Calhoun, Edgewood Place Entertainment

Here is the link.

Wendy Calhoun, Hollywood producer and writer, shares how to get everyone in a room to thrive and create a collective idea that’s better than any individual one. From Nashville to Justified to Empire, Calhoun has worked with with many teams to make different storylines come alive. Where does she start? With a warm-up. Calhoun recommends starting any creative process with a warm-up that has no right or wrong answers, one that gets everyone to participate so no one dominates the conversation and no voice goes unheard. She also builds on the improvisation tactic of “yes, and…” and introduces “yes, or…”, allowing participants to acknowledge the validity of a previous idea and provide an alternative. These tactics allow bolder creativity to blossom and provide the group with diverse options. Next time you’re writing an award-winning project, make sure to: engage everyone, respect the speaker, go beyond the first ideas, check your biases at the door, and actively listen.


Warmup -
anticipate the discussion

writer room - express themselves early
safe place to share - leave the room - do not let every one dominate the conversation.

She pitched the idea - ...

The Dr. Jekyll and Mr. Hyde of process | Kristen Gil, Google

Here is the link.

Kristen Gil, vice president of Google’s internal consulting group, talks about finding the balance between process that supports innovation and process that hurts innovation. She recognizes that processes can encourage collaboration, enable rapid evaluation, and foster conversation, but also that processes can be so rigid and stale that they prevent teams from achieving their purpose. Drawing examples from Google’s early hiring processes, Alphabet’s moonshot factory, X, and Google’s workspace design, Gil encourages you to think about when your processes are working and when they’re becoming a roadblock.

What makes one team smarter than another? | Anita Williams Woolley, Carnegie Mellon University

Here is the link.

Dr. Anita Williams Woolley, associate professor of Organizational Behavior and Theory at the Tepper School of Business at Carnegie Mellon University, shares why some teams are smarter than others and how “collective intelligence” is a key predictor of team performance. People tend to focus on individual attributes when predicting team success, whether looking at hockey teams or presidential cabinets. Woolley argues that organizations need to look more closely at the value of collective intelligence and how team members perform together; her research shows that this is a much better predictor of team performance than individual IQ. Woolley finds that team diversity and social perceptiveness (the ability to pick up nonverbal cues from others) are critical ingredients of collective intelligence. Her recommendations? 1) Set egalitarian norms when you’re convening a team; leave no room for stars or loafers. 2) Pay attention to the skills and collaboration abilities of the team and avoid hiring people who are particularly domineering or negative.

re:Work 2016 highlights

Here is the link.

Google explains why "Hiring is the Most Important Thing You Do"

Here is the link.

Leadership, Google-nish
Cognitive ability

Specific - culture fit ? - unconscious bias - across country flight

Academic dilemma - what to choose
Step forward - limited information - ambiguity -

What does structured interviewing mean?

1. using validated high-quality questions that relevant to the role
2. scoring with standardized rubrics
3. Providing interviewer training and calibration

Why structured interviews?

they are more effective, more efficient &make both ...

Interview questions

Predict performance -> not favorite algorithm

Why use a rubric?

Inteview feedback

Make hiring decision work

Interviewer training

Data, Structure, and Science in Hiring at Google | Kerry Cathcart, Staffing Program Manager

Here is the link.

Data, structure and Science in Hiring at Google

First round - I took some notes:

Structure questions

01 - Using validated, high-quality questions that are relevant to the role
02 -
03 - Providing interviewer training and ...

Behavioral 

past focused

Often begin with "tell me about a time when "

Useful to understand the impact a candidate has hand in previous roles

Hypothetical 

Future focused

Often begin with "Image that"

Why use a rubric?

Consistency and objective when scoring
Fairness across candidates and interviews
Accuracy predicting success on the job

giving interviewers feedback

Making hiring decisions by committee

Candidate experience matters

83% percent job candidates will talk about job experience.
3 things most impactful -

How to prepare?
Actually interview itself

Measuring experience 
positive - not getting the job

Questions and answers:

Second round: 1:49 PM - 2:09 PM

Hiring attributes for assessment - Google attributes

Skills required on day 1 to get the job done.
General cognitive ability

Last six months tough problem to solve

re:Work with Google

Here is the link.

How well a candidate can contribute to the Google experience.

Laszlo Bock on how Google is changing the nature of work

Here is the link.

Becoming a Googler...and Other Opportunities

Here is the link.

Here is the blog I took some notes in 2017.

First round, 31 minutes:

You can learn vs you know what you are doing

What google looks for:

1. Learning ability

2. Emergency leadership
team 4 - 6 people, step in/ step out

3. Culture fit - just like us, people are comfortable with ambiguity.
humanity, conscientious

3. Expertise, good engineer, great at it.

5 - 10 times, comes out something new - Look at the problem again and again.

14% percent no college degree - How google selected them?

Online training, self-taught. Pick up a lot of places, how to assess these?

Look at deep, net hire each year 5000 - 8000, 2 million application.

Every day MIT people size of people applies every day, 11,500 students.


Relationship matters - build relationship 

Unconscious bias - take away 10 dollars from junior people to senior people in bonus. 

#59 Beth Seidenberg - General Partner, Kleiner Perkins Caufield & Byers

Here is the article.

Longtime Kleiner Perkins investor Beth Seidenberg has raised $320M for her own fund

Here is the article.

KPCB CEO Workshop

I like to find a few videos to watch. Here is the channel on youtube.com.

How Google Thinks About Hiring, Management and Culture

Sept. 14, 2019

Introduction

It is time for me to review the video. I like to figure out if I grow and can understand better about this topic.

30 minutes study

Here is the video.

I spent time to watch the video back in 2017. Here is the blog.

I am getting older and I like to learn more about this topic.

Last two years I experienced four onsite interviews, one for Amazon onsite Seattle June 6, 2018. Three onsite interviews in 2019, Amazon, Facebook, Fortinet, one phone screen from Docusign.

About the book - "Work Rules!: Insights from inside Google that will transform how you live and lead"

LEGENDS OF TRADING: THE STORY OF PAUL TUDOR JONES

Here is another 13 minutes video. I like to watch a few more videos about the billionaire.

Stock Market Crash 2020 – Six Bear Market Indicators

Here is the article.

Watch CNBC's full interview with Paul Tudor Jones

I like to spend another 20 minutes to watch the interview. Here is the link.

Billionaire investor Paul Tudor Jones sits down with CNBC's Andrew Ross Sorkin on the markets, the latest JUST Capital rankings and the overall health of the economy.

The Log: What every software engineer should know about real-time data's unifying abstraction

Here is 30 pages article. I like to spend time to read the paper.

Best Dividend Achievers and Beyond

Here is the article.

Case study: 126 Word ladder II - simple version - find all paths

Sept. 13, 2019

Introduction

It is my 10:00 PM as an interviewer on interviewing.io platform. I spent 42 minutes to interview the interviewee using word ladder II simple version, find all paths. It is learning experience for me as an interviewer, and also I like to explore the algorithm as an interviewer. It was exciting and I was so happy to learn from the mistakes, bugs written.

Case study

Here is the transcript.

My feedback

I did point out the challenging part to apply BFS, how to store so many intermediate paths, what is space complexity concern.

After 30 minutes, I also reviewed the code, and ran test case, and then pointed out the problem to store two paths in one variable.

How do you predict the next financial crisis?

Here is the link.

Paul Tudor Jones - Just imagine when next recession comes

Here is the link.

Paul Tudor Jones II: Why we need to rethink capitalism

Here is TED talk link.

Paul Tudor Jones II loves capitalism. It's a system that has done him very well over the last few decades. Nonetheless, the hedge fund manager and philanthropist is concerned that a laser focus on profits is, as he puts it, "threatening the very underpinnings of society." In this thoughtful, passionate talk, he outlines his planned counter-offensive, which centers on the concept of "justness."

Billionaire David Tepper: Habits For Success and Advice On Making It In Finance (2018)

Here is 35 minutes interview video.

David Tepper - wiki

Here is the wiki page.

In 2009, Tepper's hedge-fund earned about $7 billion by buying distressed financial stocks in February and March (including Bank of America common stock at $3 per share), and then profiting from their recovery that year.^[13] A total of $4 billion of those profits went to Tepper's personal wealth, making him the top-earning hedge fund manager of 2009 according to The New York Times.^[14] In June 2011, he was awarded the Institutional Hedge Fund Firm of the Year.^[15] In 2013 Forbes ranked him as top hedge-fund earner of 2012, moving him up to the 166th wealthiest person in the world.^[1]

Paul Tudor Jones - wiki

Here is the wiki page.

LEGENDS OF INVESTING: THE STORY OF CARL ICAHN

Here is the link.

Carl Icahn's Top 5 Secrets to Success

Here is the link of 5 minutes video.

Carl Icahn is part of the top 50 richest men in the world with a net worth of $16.9 billion, according to Forbes. He is widely known as one of the most polarizing people in Wall Street with a reputation for delivering controversial decisions and initiatives that heavily influence corporate America. Some of his widely reported ventures include his takeover efforts of Texaco, Trans World Airlines (TWA), and American Airlines. He founded Icahn Enterprises, formerly known as American Real Estate Partners, a highly diversified multinational holding company in New York. Icahn is the chairman of American developer and manufacturer Federal-Mogul as well. His brash leadership style and fearless takes on the market has made Icahn one of the highly respected men in the world today.

Woman to Watch: Grab co-founder Hooi Ling Tan

Here is the link.

Grab, formerly known as GrabTaxi or MyTeksi in Malaysian dialect, is a ride-hailing app like Uber and Lyft. It revolutionized how people commute and do logistic stuff with the use of an app. Behind its success is Harvard Business School graduate Anthony Tan but did you know the other Grab co-founder by the name of Hooi Ling Tan?

Who is Hooi Ling Tan?

Hooi Ling Tan co-founded Grab and has stayed with the ride-hailing giant for six years. Prior to it, she was Senior Director at SalesForce, handling Price Intelligence and Monetization and an associate at McKinsey and Company. She earned her MBA at Harvard Business School and graduated with a degree in Mechanical Engineering from the University of Bath.

Grab Co-Founders Anthony Tan and Hooi Ling Tan on 'Bloomberg Studio 1.0'

Here is the link.

Leetcode 305: Island count II

Sept. 13, 2019

Introduction

It is so enjoyable to write a short algorithm called island count II. I like to post my solution somewhere so that I can track my progress of learning.

My practice

Here is my C# code from my Leetcode github algorithm folder.

Here is the folder in my repository called 100 hard level algorithms.

The problem statement can be looked up here:

A 2d grid map of m rows and n columns is initially filled with water. We may perform an addLand operation which turns the water at position (row, col) into a land. Given a list of positions to operate, count the number of islands after each addLand operation. An island is surrounded by water and is formed by connecting adjacent lands horizontally or vertically. You may assume all four edges of the grid are all surrounded by water.

Example:

Given m = 3, n = 3, positions = [[0,0], [0,1], [1,2], [2,1]].
Initially, the 2d grid grid is filled with water. (Assume 0 represents water and 1 represents land).

0 0 0
0 0 0
0 0 0

Operation #1: addLand(0, 0) turns the water at grid[0][0] into a land.

1 0 0
0 0 0   Number of islands = 1
0 0 0

Operation #2: addLand(0, 1) turns the water at grid[0][1] into a land.

1 1 0
0 0 0   Number of islands = 1
0 0 0

Operation #3: addLand(1, 2) turns the water at grid[1][2] into a land.

1 1 0
0 0 1   Number of islands = 2
0 0 0

Operation #4: addLand(2, 1) turns the water at grid[2][1] into a land.

1 1 0
0 0 1   Number of islands = 3
0 1 0

We return the result as an array: [1, 1, 2, 3]

Challenge:

Can you do it in time complexity O(k log mn), where k is the length of the positions?

Highlights of solution using union find algorithms

1. Understand the union find algorithm, which can be implemented using the array with parent id
2. Union find algorithm original parent id is itself
3. Set all element with value not 0 as a new island
4. Check all its four neighbor, if the neighbor's node is not -1, then see if the parents are the same or not. If not, union two disjoint sets.
5. Only challenge job is to write function called findRoot using recursive function, path compression.
6. Two for loops, outside one is to loop each position, inside loop to check four directions.

Uber CEO Dara Khosrowshahi on 'Bloomberg Studio 1.0'

Here is the interview.

Veronica Dagher - Wealth managemnet senior report

Here is the page to read.

Maria Sharapova on the Loneliness of Losing and Winning | WSJ

Sept. 13, 2019

Introduction

I like to watch the video. I just took a few minute to do some research, just share the comparison between Sharapova and Serena Williams net worth and prize money.

I understand that it is so important to learn investment, and how to treat money properly. I was wondering how come I did not grow up and understood that health and relationship is more important compared to clothing, until I was 52 years old, struggled financially and started my personal finance research starting from Nov. 2018.

Serena William s   Prize money: $92,543,816, net worth  $157 million
Sharapova                                    $38,000,000, net worth $195 million

My notes

Here is the link.

How to Set Your Career Goals

Here is the link.

How to set "Career" goals?

current -> future
Envision
Plan
Commit

Smart goals

Specific, Meaningful, aligned, relerant?,

How to Advance Your Career | Michigan Ross School of Business

Here is the link.


Take some risk.

How many ideas you like to try?

take care of yourself, space, accountable.

Personal board advisor - mentorship

growth mindset, space, accountability, thrive

Changing The World, One Student, One Idea At A Time - Michigan Ross Dean Scott DeRue

Here is the link.

Google’s Quest to Build a Better Boss

Here is the article I like to read.

By ADAM BRYANTMARCH 12, 2011

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Mountain View, Calif.

IN early 2009, statisticians inside the Googleplex here embarked on a plan code-named Project Oxygen.

Their mission was to devise something far more important to the future of Google Inc. than its next search algorithm or app.

They wanted to build better bosses.

So, as only a data-mining giant like Google can do, it began analyzing performance reviews, feedback surveys and nominations for top-manager awards. They correlated phrases, words, praise and complaints.

Later that year, the “people analytics” teams at the company produced what might be called the Eight Habits of Highly Effective Google Managers.

Now, brace yourself. Because the directives might seem so forehead-slappingly obvious — so, well, duh — it’s hard to believe that it took the mighty Google so long to figure them out:

“Have a clear vision and strategy for the team.”

“Help your employees with career development.”

“Don’t be a sissy: Be productive and results-oriented.”

The list goes on, reading like a whiteboard gag from an episode of “The Office.”

“My first reaction was, that’s it?” says Laszlo Bock, Google’s vice president for “people operations,” which is Googlespeak for human resources.

But then, Mr. Bock and his team began ranking those eight directives by importance. And this is where Project Oxygen gets interesting.

For much of its 13-year history, particularly the early years, Google has taken a pretty simple approach to management: Leave people alone. Let the engineers do their stuff. If they become stuck, they’ll ask their bosses, whose deep technical expertise propelled them into management in the first place.

But Mr. Bock’s group found that technical expertise — the ability, say, to write computer code in your sleep — ranked dead last among Google’s big eight. What employees valued most were even-keeled bosses who made time for one-on-one meetings, who helped people puzzle through problems by asking questions, not dictating answers, and who took an interest in employees’ lives and careers.

“In the Google context, we’d always believed that to be a manager, particularly on the engineering side, you need to be as deep or deeper a technical expert than the people who work for you,” Mr. Bock says. “It turns out that that’s absolutely the least important thing. It’s important, but pales in comparison. Much more important is just making that connection and being accessible.”

Project Oxygen doesn’t fit neatly into the usual Google story line of hits (like its search engine) and misses (like the start last year of Buzz, its stab at social networking). Management is much squishier to analyze, after all, and the topic often feels a bit like golf. You can find thousands of tips and rules for how to become a better golfer, and just as many for how to become a better manager. Most of them seem to make perfect sense.

Problems start when you try to keep all those rules in your head at the same time — thus the golf cliché, “paralysis by analysis.” In management, as in golf, the greats make it all look effortless, which only adds to the sense of mystery and frustration for those who struggle to get better.

That caveat aside, Project Oxygen is noteworthy for a few reasons, according to academics and experts in this field.

H.R. has long run on gut instincts more than hard data. But a growing number of companies are trying to apply a data-driven approach to the unpredictable world of human interactions.

“Google is really at the leading edge of that,” says Todd Safferstone, managing director of the Corporate Leadership Council of the Corporate Executive Board, who has a good perch to see what H.R. executives at more than 1,000 big companies are up to.

Project Oxygen is also unusual, Mr. Safferstone says, because it is based on Google’s own data, which means that it will feel more valid to those Google employees who like to scoff at conventional wisdom.

Many companies, he explained, adopt generic management models that tell people the roughly 20 things they should do as managers, without ranking those traits by importance. Those models often suffer “a lot of organ rejection” in companies, he added, because they are not presented with any evidence that they will make a difference, nor do they prioritize what matters.

“Most companies are better at exhorting you to be a great manager, rather than telling you how to be a great manager,” Mr. Safferstone says.

PROJECT OXYGEN started with some basic assumptions.

People typically leave a company for one of three reasons, or a combination of them. The first is that they don’t feel a connection to the mission of the company, or sense that their work matters. The second is that they don’t really like or respect their co-workers. The third is they have a terrible boss — and this was the biggest variable. Google, where performance reviews are done quarterly, rather than annually, saw huge swings in the ratings that employees gave to their bosses.

Managers also had a much greater impact on employees’ performance and how they felt about their job than any other factor, Google found.

“The starting point was that our best managers have teams that perform better, are retained better, are happier — they do everything better,” Mr. Bock says. “So the biggest controllable factor that we could see was the quality of the manager, and how they sort of made things happen. The question we then asked was: What if every manager was that good? And then you start saying: Well, what makes them that good? And how do you do it?”

In Project Oxygen, the statisticians gathered more than 10,000 observations about managers — across more than 100 variables, from various performance reviews, feedback surveys and other reports. Then they spent time coding the comments in order to look for patterns.

Once they had some working theories, they figured out a system for interviewing managers to gather more data, and to look for evidence that supported their notions. The final step was to code and synthesize all those results — more than 400 pages of interview notes — and then they spent much of last year rolling out the results to employees and incorporating them into various training programs.

The process of reading and coding all the information was time-consuming. This was one area where computers couldn’t help, says Michelle Donovan, a manager of people analytics who was involved in the study.

“People say there’s software that can help you do that,” she says. “It’s been our experience that you just have to get in there and read it.”

GIVEN the familiar feel of the list of eight qualities, the project might have seemed like an exercise in reinventing the wheel. But Google generally prefers, for better or worse, to build its own wheels.

“We want to understand what works at Google rather than what worked in any other organization,” says Prasad Setty, Google’s vice president for people analytics and compensation.

Once Google had its list, the company started teaching it in training programs, as well as in coaching and performance review sessions with individual employees. It paid off quickly.

“We were able to have a statistically significant improvement in manager quality for 75 percent of our worst-performing managers,” Mr. Bock says.

He tells the story of one manager whose employees seemed to despise him. He was driving them too hard. They found him bossy, arrogant, political, secretive. They wanted to quit his team.

“He’s brilliant, but he did everything wrong when it came to leading a team,” Mr. Bock recalls.

Because of that heavy hand, this manager was denied a promotion he wanted, and was told that his style was the reason. But Google gave him one-on-one coaching — the company has coaches on staff, rather than hiring from the outside. Six months later, team members were grudgingly acknowledging in surveys that the manager had improved.

“And a year later, it’s actually quite a bit better,” Mr. Bock says. “It’s still not great. He’s nowhere near one of our best managers, but he’s not our worst anymore. And he got promoted.”

Mark Klenk, an engineering manager whom Google made available for an interview, said the Project Oxygen findings, and the subsequent training, helped him understand the importance of giving clear and direct feedback to the people he supervises.

“There are cases with some personalities where they are not necessarily realizing they need a course correction,” Mr. Klenk says. “So it’s just about being really clear about saying, ‘O.K., I understand what you are doing here, but let’s talk about the results, and this is the goal.’ ”

“I’m doing that a lot more,” he says, adding that the people he manages seem to like it. “I’ve gotten direct feedback where they’ve thanked me for being clear.”

GOOGLE executives say they aren’t crunching all this data to develop some algorithm of successful management. The point, they say, is to provide the data and to make people aware of it, so that managers can understand what works and, just as important, what doesn’t.

The traps can show up in areas like hiring. Managers often want to hire people who seem just like them. So Google compiles elaborate dossiers on candidates from the interview process, and hiring decisions are made by a group. “We do everything to minimize the authority and power of the manager in making a hiring decision,” Mr. Bock explains.

A person with an opening on her team, for instance, may have short-term needs that aren’t aligned with the company’s long-term interests. “The metaphor is, if you need an administrative assistant, you’re going to be really picky the first week, and at six months, you’re going to take anyone you can get,” Mr. Bock says.

Google also tries to point out predictable traps in performance reviews, which are often done with input from a group. The company has compiled a list of “cognitive biases” for employees to keep handy during these discussions. For example, somebody may have just had a bad experience with the person being reviewed, and that one experience inevitably trumps recollections of all the good work that person has done in recent months. There’s also the “halo/horns” effect, in which a single personality trait skews someone’s perception of a colleague’s performance.

Google even points out these kinds of biases in its cafeteria line. The company stacks smaller plates next to bigger ones at the front of the line, and it tells people that research shows that diners generally eat everything on their plate, even if they are full halfway through the meal. By using the smaller plate, Google says, they could drop 10 to 15 pounds in a year.

“The thing that moves or nudges Googlers is facts; they like information,” says Ms. Donovan, who was involved in the management effectiveness study and the effort to encourage healthier eating. “They don’t like being told what to do. They’re just, ‘Give me the facts and I’m smart, I’ll decide.’ ”

The true test of Google’s new management model, of course, is whether it will help its business performance of the long haul. Just a few hours after Mr. Bock was interviewed for this article in mid-January, Google surprised the world by announcing that Larry Page, one of its co-founders, was taking over as C.E.O. from Eric E. Schmidt.

Though Mr. Schmidt explained the move on Twitter by writing, “Day-to-day adult supervision is no longer needed,” the company made clear that the point was to speed up decision-making and to simplify management.

Google clearly hopes to recapture some of the nimbleness and innovative spirit of its early years. But will Project Oxygen help a grown-up Google get its start-up mojo back?

D. Scott DeRue, a management professor at the Ross School of Business at the University of Michigan, applauds Google for its data-driven method for management. That said, he noted that while Google’s approach might be unusual, its findings nevertheless echoed what other research had shown to be effective at other companies. And that, in itself, is a useful exercise.

“Although people are always looking for the next new thing in leadership,” he said, “Google’s data suggest that not much has changed in terms of what makes for an effective leader.” Whether Google’s eight rules will still apply as the company evolves is anyone’s guess. They certainly aren’t chiseled in stone. Mr. Bock’s group is continuing to test them for effectiveness, watching for results from all the training the company is doing to reinforce the behaviors.

For now, Mr. Bock says he is particularly struck by the simplicity of the rules, and the fact that applying them doesn’t require a personality transplant for a manager.

“You don’t actually need to change who the person is,” he says. “What it means is, if I’m a manager and I want to get better, and I want more out of my people and I want them to be happier, two of the most important things I can do is just make sure I have some time for them and to be consistent. And that’s more important than doing the rest of the stuff.”

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Continue reading the main story

Google manager research project

Here is the link.

Google hasn’t always properly appreciated management. In 2002, Google ran an uncontrolled “experiment” by simply getting rid of all managers. It didn’t go well. So in 2008 a team of researchers set out to prove what some at Google suspected - that managers don’t matter. But very quickly the team discovered quite the opposite. Managers matter a lot.

The research effort, called Project Oxygen, pivoted to figure out exactly what makes for a great manager at Google. The guiding question shifted from “Do managers matter?” to “What if every Googler had an awesome manager?” Project Oxygen identified a set of common behaviors among the best managers and those behaviors now guide management development programs. The team has been able to show an overall improvement in management at Google by helping managers get better at coaching, decision making, collaboration, empowering teams, managing team energy, staying results-oriented, communicating, developing teams, and sharing a vision.

How Google Makes Managers Awesome | Michelle Donovan

Here is the link.

Managers matter a lot and can have a huge impact on employee performance. Support your people by sharing what makes a great manager, providing development opportunities, celebrating great managers, and more. Google hasn’t always properly appreciated management. In 2002, Google ran an uncontrolled “experiment” by simply getting rid of all managers. It didn’t go well. So in 2008 a team of researchers set out to prove what some at Google suspected - that managers don’t matter. But very quickly the team discovered quite the opposite. Managers matter a lot. The research effort, called Project Oxygen, pivoted to figure out exactly what makes for a great manager at Google. The guiding question shifted from “Do managers matter?” to “What if every Googler had an awesome manager?” Project Oxygen identified a set of common behaviors among the best managers and those behaviors now guide management development programs. The team has been able to show an overall improvement in management at Google by helping managers get better at coaching, empowering teams, managing team energy, staying results-oriented, communicating, developing teams, and sharing a vision.

HBSGX - Hartford Small Cap Growth

Sept. 12, 2019

Introduction

It is time for me to learn more about this mutual fund. I think that the return is above 25% based on dividend income.

My case study

I have Par 401 K, recently I ran mint.com and then I found out that I got dividend from the fund.

8/27/2019
HBSGX - Hartford Small Cap Growth HLS IB -Dividends/Capital Gains -Purchase
$45.13 Price: 26.04

4/29/2019

HBSGX - Hartford Small Cap Growth HLS IB -Transfers In/Out -Purchase $257.57 Price 32.42, Qty 7.942, Amount 257.57 I like to spend time to study HBSGX mutual fund, and then I learn what I should do next in terms of my 401 K management. Here is the page to look up performance.

Kafka Inside Keystone Pipeline

Here is the article.

A small project: study 100 managers working for Facebook or Google or other high tech

Sept. 11, 2019

Introduction

It is part of my learning experience how to learn project management. One of ideas is to search Facebook linkedin profile, and then I like to study up to 100 managers linkedin profile.

One idea enriches my life 

I like to learn from Linkedin profile, and build up some curiosity how to be successful in general. I will check education, job history, and all other interesting things.

To be a software programmer, there are so many things I can choose to work on. But I do think that it is better for me to learn how Facebook manages the team, culture, how people work together etc.

Cloud Identity: Converging Mobility, Identity and Context (Cloud Next '18)

Here is the video.

I like to spend time to watch the video.

Vidya Nagarajan of Google Cloud

Here is the video.

Unifying User, Device, and App Management With Cloud Identity (Cloud Next '19)

Here is the link.

IDaaS, IAM, hybrid, EMM, UEM… So many tools, so little time. Join this session to see how Cloud Identity can help you unify user and device management, protect company data, and control access to company resources leveraging the BeyondCorp security model. Expect to see lots of demos!

My First Month at Facebook!

I like to spend 10 minutes to read the article, here is the link.

I am searching good ideas in the article, here is the one:

Soon after my first week, I was most surprised by how the company value “Focus on Impact” is so real! People have been asking me “What’s the Impact of a specific work planned?” , “What’s the Impact my team can make over next few months?” and several impact-related questions. This was not something I was explicitly asked before. It took me a while to really think through the impact and articulate it before I proposed any ideas and approaches. I quickly realized how this mantra was instrumental in helping me efficiently lay out the vision and goals for my team.

Linkedin profile study - Director, Product Management at Facebook

Here is the linkedin profile.

I think that it is better for me to study Linkedin profile compared to check wechat message so often.

I like to read Linkedin profile and see how people are connected through "People Also Viewed" section.

Facebook Tech Careers - Asia Pacific

Here is the link.

Facebook operates on a truly unprecedented scale. Managing such incredible amounts of data and traffic requires unconventional thinking and coming up with lightning fast solutions in real time. Our work is as bold as it is fast and impacts billions of people every day.

4 qualities that helped me to succeed as an engineer at Facebook

Here is the article.

I spent more than a few hours to surf linkedin.com, and I like to read a lot of Facebook research scientist and manager profiles as possible.

Finally I came cross this sharing.

1. Overcome impostor syndrome - I joined Facebook five years ago, and I was working with very smart and experienced teammates who were Stanford or Harvard graduates. Initially, I felt like I wasn’t as capable or as talented as them, and I needed to constantly prove myself.

It took me a while to realize that impostor syndrome is very normal, and it is ok for anyone to feel this way. Facebook had given me this terrific opportunity to work with the brightest minds in the industry, but at same time my fear of not being good enough made me doubt my abilities.

4. Ruthlessly prioritize – It’s important to take consistent inventory of the work you have in front of you and make sure that you’re focusing on the most important and impactful things. At Facebook, there will always be many things to do, and I've learnt to accept that I can’t do everything at once. Once I had that figured out, I could prioritize my projects, and that helped me to stay organized and deliver a bigger impact to my team's goals. If you clearly communicate why you need to make tough prioritization decisions, Facebookers will understand. It’s part of our culture.

Researchers’ new algorithm helps computers distinguish between people with the same name

Here is the article. I like to read the article, and learn something today.



Solving that problem is the challenge that computer scientists Murat Dundar and Mohammad al Hasan, and doctoral student Baichuan Zhang, all of Indiana University — Purdue University Indianapolis, set themselves. They claim to have made an improvement on old methods, by using machine learning and a variety of sources to help figure out who’s who with different data sets.

Case study: How to write executable code in 45 minutes session?

Sept. 11, 2019

Introduction

It is the topic I like to work on, research and talk about. I had 45 minutes session to work on one algorithm. My goal is to learn how to write executable code in less than 45 minutes.

Case study

I experienced the pain to work on algorithm problem solving last month. I did write down my mistake, the algorithm is related to binary search. And there is another one is related to word ladder II. And there is another one related to DFS algorithm.

So I learn that it is important for me to warm up algorithms to prepare. I spent three hours to study 10 algorithms related to coach sessions I had in 2018, I was so surprised to learn those algorithms since I had no idea what those algorithms are in detail until I read my own blog and source code. Most important is to document my learning, and those mistakes and error usually will repeat itself in my performance.

Also, I learn from those interviewees I met after August 20, 2019. Here are a few things I did today.

1. Go over the example, spend at least 3 - 5 minutes to work on test case, step by step, work on test case, and explain my idea, what I should design in terms of time complexity, variable names.
2. Work on solution using the test case, explain what I think, explore. Make sure that I fully understand the problem. Also the interviewer knows what my idea is.
3. Ask permission to code. The interviewer said that I can code pseudo code or executable code. I choose to write executable code.
4. Because I work on test case and warm up, I can write very clearly and I explain to myself as well.
5. Once I finish coding, I immediately say that I like to test code using the following test cases.

I start from simple test case, "", "a", "aa", "baa", and make sure that every line of code is executed. I also added comment to explain the code.

General advice

It is a good idea to learn to solve as many hard level algorithms as I can. Since the hard level algorithm takes time, it is better to work on easy level ones, break into easy level ones. Make sure that I can solve those easy level ones without any bug.

Recently, I worked on word ladder II, 126, and I started to work on easy one, ask interviewees to work on interviewing.io.

Another thing is to work on my communication skills. Most important is to go over a test case, step by step, make sure that I understand the problem, and also solve the problem using my hand first.

Next thing is to code the solution followed by a few basic test cases.

I think that in general I should learn how to test my own code, learn how to break the code, and evaluate the solution again and again.

Crafting skills are so important, and I should always do my best. No matter what I write, either a blog, a discussion post, or an algorithm, comment, make sure that I can express myself clearly.

Actionable Items

I did not review my algorithm practice last weekend. Today I was surprised that I only spent 3 hours, what I reviewed is 10 coach sessions, a few mock interviews on pramp.com.

I should take thing seriously. Usually I should review around 100 - 150 algorithms in order to cover all basic topics.

Here is the transcript.

Lessons learned 

I like to document lessons learned from my own experience. I should stay humble, and also work hard like sprint 100 meters to test my own code using as many test cases as possible, question every possible things to break the code.

Case 1: Binary search - index-out-of-range, missing else statement for if case. Here is the discussion post.
Case 2: DFS - brute force solution, do not exhaust all possible option. Nice and clean solution, simplified word ladder II is here.
Case 3: Use extra space, worst thing is impossible to implement in five minutes for extra requirement. Implementation is here.

GOTO 2016 • Cluster Management at Google with Borg • John Wilkes

Here is the video.

What I like to do is to spend some time to learn something today.

One thing I like to do is to search Google, Borg vs Kubenetes. And I also like to learn the presenter.

One day vacation - system design

Sept. 11, 2019

Introduction

It is my vacation day. I am planning to study system design after August 20, and how I can do is very challenging for me. Since I have experience how to advance my algorithm and data structure last 4 years, learning system design is much challenging task.

Half hour study

I decided to review Martin's presentation: Is kafka a database? Here is the link.

I like to spend time to learn better about system design in 2019.

One day vacation - island count II

Sept. 11, 2019

Here is the blog I like to study about the algorithm which is locked on Leetcode.com.

A 2d grid map of m rows and n columns is initially filled with water. We may perform an addLand operation which turns the water at position (row, col) into a land. Given a list of positions to operate, count the number of islands after each addLand operation. An island is surrounded by water and is formed by connecting adjacent lands horizontally or vertically. You may assume all four edges of the grid are all surrounded by water.

Example:

Given m = 3, n = 3, positions = [[0,0], [0,1], [1,2], [2,1]].
Initially, the 2d grid grid is filled with water. (Assume 0 represents water and 1 represents land).

0 0 0
0 0 0
0 0 0

Operation #1: addLand(0, 0) turns the water at grid[0][0] into a land.

1 0 0
0 0 0   Number of islands = 1
0 0 0

Operation #2: addLand(0, 1) turns the water at grid[0][1] into a land.

1 1 0
0 0 0   Number of islands = 1
0 0 0

Operation #3: addLand(1, 2) turns the water at grid[1][2] into a land.

1 1 0
0 0 1   Number of islands = 2
0 0 0

Operation #4: addLand(2, 1) turns the water at grid[2][1] into a land.

1 1 0
0 0 1   Number of islands = 3
0 1 0

We return the result as an array: [1, 1, 2, 3]

Challenge:

Can you do it in time complexity O(k log mn), where k is the length of the positions?

Highlights of solution using union find algorithms

1. Understand the union find algorithm, which can be implemented using the array with parent id
2. Union find algorithm original parent id is itself
3. Set all element with value not 0 as a new island
4. Check all its four neighbor, if the neighbor's node is not -1, then see if the parents are the same or not. If not, union two disjoint sets.
5. Only challenge job is to write function called findRoot using recursive function, path compression.
6. Two for loops, outside one is to loop each position, inside loop to check four directions.

C++ code in the study blog starts here:

C++ code in the study blog ends here:

Actionable Items

Plan to write C# solution as well in short future. The problem is called Leetcode 305, word ladder II. 

One day vacation - review algorithm and data structure

Sept. 11, 2019

Introduction

It is my one day vacation. I stay at my home office, and I like to review some algorithms .

What to work on

I like to review algorithms based on my own practice.

I like to review easy level algorithms, 10 session with my ex-coach in 2018, pramp.com 10 rounds of mock interviews, and then 2019 practice.

Jon Skeet - C# in depth

I like to spend 10 minutes to google Jon skeet.

Where is C# headed? - Mads Torgersen, Jon Skeet

Here is the link. 

Petr Mitrichev

Here is the wiki page.