Learnings from being on my own

Ernest was a baller.

I’m always looking to learn and grow as much as I can, and so am now working for myself. I’m currently consulting for other businesses, doing product development and/or data analysis, since I have a generalist software + statistics background. I see it as a great way to work with different, awesome people, on different problems, while learning about different industries: it’s a way for me to take lots of little bets in my journey of doing interesting things, finding my passion/what I want to focus on, and becoming the best version of myself.

Here are some of the biggest things I’ve learned so far, even though it’s only been a short amount of time. Hopefully they are helpful and mostly generalizable, but everyone’s life is different so your mileage may vary.

1. Reflect on when in your life you’ve felt happiest and most fulfilled.

I looked back on my life and thought about when I really felt the most alive, happy, and fulfilled. For me, it came down to experiences where I manifested my dreams, despite any perceived risk. Of course, I could not have done it without the help and support of friends and family and partners-in-crime–I feel life is so much less meaningful without others–but it was not being dependent on anyone but myself in taking action to maximize my potential that made me feel fulfilled*.

For example, one of the first pieces of software I ever developed was a math flashcards application built in Visual Basic, with cheesy cartoon characters and everything. As a middle schooler who had just learned how to program, I was super proud of it and really excited whenever I got to work on it, because I had come up with the idea and it was up to me to manifest and build my own “dream”.

Another time when I felt happy and fulfilled was the period of a year or two of learning how to pick up girls. That itself is a story for another time, but again, I loved the experience of facing and overcoming perceived risk, via action, to become the best version of myself. There’s no doubt that I felt a lot of discomfort in a countless number of situations. But, especially in situations where the perceived risk is high but the real risk is low, the pain of regret usually hurts more than the pain of failure.

As a result, my overarching goal in life is to maximize the time I spend on these types of experiences.

What experiences have made you feel the most fulfilled in life?

2. Think about death.

Jeff Bezos, Steve Jobs, the ancient Stoics, and many others have used the tactic of thinking about death when examining life.

I like Bezos’s thought experiment the best for decision making, and I use it all the time: visualize that you are old and on your deathbed–would you regret having made decision A vs. decision B (vs. decision C, etc.)?

We all die someday. The inevitability is out of our control. So why not try to live the best life you can live?

3. Do things that make you happy, every day.

About a week after leaving my job, one random a day, I felt like I was in a deep rut: negative emotions like fear and self-doubt were spiraling out of control in my head. I needed to change things up–being in such a bad mood wasn’t moving me forward in life at all.

Taking 10 minutes to meditate helped (Tara Brach has some great guided meditations, Headspace is also great for beginners).

I hadn’t listened to any music in several days, so I put on some EDM, changed my environment a little, and cranked on work for a bit at a coffee shop. Those of you who’ve worked in a library and/or coffee shop before, it’s strangely motivating isn’t it?

I went to the gym in the late afternoon, which also helped because it took my mind off negative emotions and gave me sense of progress.

Later that night, I went to an event met new people. It was great to put myself in their shoes for a little and understand what they’re up to, and what they care about most.

Thanks for reading!

The new journey has only just begun, but those are the practices and mindsets I’ve implemented that have helped me so far. As always, advice is useless if you don’t internalize it, make it part of your mindset, and practice it.

Have a safe and relaxing holiday season!


*Reminds me of Rand’s Objectivism, I guess


What I learned from my side project in education technology: Formata


Screenshots of what the student would see, taken from the deck I sent to teachers.

Last winter, I built an MVP for an ed-tech product, called Formata. Here’s what it was, why I did it, and what I learned from it.

Why Education

I had been (and still am) trying little side projects in different industries because I like learning about and understanding new things. At the time, I had done some stuff in productivity and fintech, and I knew I wanted to have an impact on education eventually in my life. It’s been so influential on me and and is a huge lever to get us closer to what I call “opportunity equality” worldwide, so I decided to do a small project in education this time.

Principles of Educational Impact

I did a little thought experiment: I imagined myself as a middle school kid again, and thought about what influenced me the most, in my education. “My teachers” was the answer. Students spend the majority of their week day in school, and it’s the teachers that interact with them, and understand each and every child. I saw it first hand on a farm on the other side of the world: way more than the facilities and the curriculum, it’s the teacher that inspires the student and really has an impact on him or her.

Next, I asked, “Ok, so if teachers have the most impact on a child’s education, what makes a good teacher? What does “good” even mean? And how do you measure it?” I did some research, and came across the Gates Foundation’s Measures of Effective Teaching project, a project backed by hundreds of millions of dollars and pursuing these exact questions. Awesome!

Some more research led me to the interesting and sometimes controversial world of teacher evaluation. Traditionally, teachers have been evaluated by two methods: student test scores (also known as “value added”), and observations by someone like the principal. The thought is basically that student test scores, as the outcome of a teacher’s teaching, should correlate with his or her teaching ability. Sometimes, administration has a rubric for what they think makes a teacher good, and so a few times a year, the principal might sit in on a class for 15 or so minutes to observe and evaluate the teacher.

There are some fundamental issues with both methods, which I’ll mention briefly. It’s hard to see the principal observing each teacher a few times a year, for 15 minutes, having any strong relationship with how good the teacher actually is. The Gates Foundation has done research that shows that teacher observations are less reliable than test scores; however, tests on which teachers are usually evaluated (usually state-wide standardized ones) only happen once every year, and if they know this is tied to their employment, there’s a strong incentive to “teach to the test”.

Who interacts with teachers the most? Who would be best at evaluating them? The students themselves. Again, the Gates Foundation did a bunch of research on what exactly students should evaluate teachers on, sort of quantifying the aspects of a good teacher. They narrowed the most important characteristics down to what they called the “7 C’s”: caring, control, captivate, clarify, confer, consolidate, and challenge. Structured in the right way (e.g. low-stakes and anonymized, so the students aren’t incentivized to fudge), student perception questionnaires that asked about these characteristics were pretty reliable in discerning high performing teachers from the rest.

Building A Product

I noticed that in the Gates Foundation’s research, the student perception surveys were being administered with pen, paper, envelopes, stickers, etc. I felt like the surveys could be administered much more efficiently with technology; the results could also be tabulated and organized much better for teachers and administrators to learn from.

To further validate my idea, I went to a bunch of ed-tech meet-ups, talking to teachers and asking them what they thought about my idea. They all agreed that having more feedback, more frequently, on their teaching would be helpful.

I thought this was a pretty quick MVP to build, I could even do some of the analysis of feedback for the teachers manually myself at first. All the teacher would have to do was give me the email addresses of his/her students, and I could auto-generate emails and questionnaires, send them off, and aggregate the results.

Visualizations of student feedback I could generate for teachers, so they could pinpoint where to work on

Visualizations of student feedback I could generate for teachers, so they could pinpoint where to work on

Moving On

After a month of reaching out to teachers, those who I already met or knew and also those who I didn’t, and sending them my slide deck about Formata and its benefits, I finally got a few who said they were willing to try it. They were extremely busy though (all teachers are overworked), and had to get permission from their department heads, who had to get permission from the principal, to use it. Their effort fizzled out, and I did a re-evaluation of my own time, and moved on.

What I Learned

I learned about a lot of different things, but overall, I think this project reinforced two principles for me:

  • Ask better questions when doing customer development, and solve a problem.
    • My idea never really solved an important problem for my target audience, teachers. I should’ve talked to more administrators, who may care more about teacher evaluation. Also, you’re bound to get positive but not very useful answers when you ask someone what they think about your idea: whether it solves a big enough problem for them to actually integrate your product into their life is a different story. Not solving an important enough problem for teachers coupled with lots of bureaucracy and the fact that they’re overworked was not a recipe for excited users.
  • Keep doing things, don’t worry about failure.
    • I got to learn about an important and fascinating area of education by doing this project. I also got to learn about the realities of the space. I learned more about the power of customer development: that through observation and/or asking better questions, you can get to true pain points that people will pay you to solve. I learned that some types of problems and tasks excite me more than others. This project was also a great way for me to practice first principles thinking.

Thanks for reading this journal of sorts.


Cancer clinical trials and the problem of low patient accrual

Inspired by this contest to come up with ideas to increase the low amount of patient accrual for cancer clinical trials, I decided to look more into the data. Bold, by the way, is one of my all time favorite books, and was co-authored by the creator of the website, the xprize Foundation, and co-founder of Planetary Resources: Peter Diamandis. Truly someone to look up to.

Anyways, the premise of the contest is that over 20% of cancer clinical trials don’t complete, so the time and effort spent is wasted. The most common reason for this termination is the clinical trial not being able to recruit enough patients. Just how common is the low accrual reason though? And are there obvious characteristics of clinical trials that can help us better predict which ones will complete successfully, and what does that suggest about building better clinical trial protocols? I saw this as an opportunity to explore an interesting topic, while playing around with the trove of data at and various data analysis python libraries: seaborn for graphing, scikit-learn for machine learning, and the trusty pandas for data wrangling.

Basic data characteristics

I pulled the trials for a handful of the cancers with the most clinical trials (completed, terminated, and in progress), got around 27,000 trials, and observed the following:

  • close to 60% of the studies are based in the US*

*where a clinical trial is “based” can mean where the principal investigator (the researcher who’s running the clinical trial) is based. doesn’t give the country in which the principal investigator’s institution is in, so as a proxy, I used the country which had the largest number of hospitals the study could recruit patients at.

  • almost 25% of all US based trials ever (finished and in progress) are still recruiting patients


  • of those trials that are finished and have results, close to 20% terminated early, and 80% completed successfully (which matches the numbers the contest cited)


  • almost 50% of all US based trials are in Phase II, almost 25% are in Phase I


  • and interestingly, the termination rate does not differ very significantly across studies in different phases


Termination reasons

Next, I was interested in finding out just how common insufficient patient accrual was as a trial termination reason vs. others reasons. This was a little tricky, as gives principal investigators a free-form text field to enter their termination reason. So “insufficient patient accrual” could be described as “Study closed by PI due to lower than expected accrual” or “The study was stopped due to lack of enrollment”. So I used k-means clustering (after term frequency-inverse document frequency feature extraction) of the termination reasons to find groups of reasons that meant similar things, and then manually de-duped the groups (e.g. combining the “lack of enrollment” and “low accrual” groups into the same group because they meant the same thing).

I found that about 52% of terminated clinical trials end because of insufficient patient accrual. This implies that about 10% of clinical trials that end (either successfully, or because they’re terminated early) do so because they can’t recruit enough patients for the study.


Predicting clinical trial termination? provides a bunch of information on each clinical trial–trial description, recruitment locations, eligibility criteria, phase, sponsor type (industry, institutional, other) to name a few–which begs the question: can this information be used to predict whether a trial will terminate early, specifically because of low patient? Are there visible aspects of a clinical trial that are related to a higher or lower probability that it fails to recruit enough patients? One might think that the complexity of trial eligibility criteria and the number of hospitals from which the trial can recruit from could be related to sufficient patient accrual.

Here was my attempt to get at a solution to this question analytically: fitting/training a logit regression multi class classifier–whether a trial would be “completed”, “terminated because of insufficient accrual”, or “terminated for other reasons”–on a random partition of clinical trial data, and measuring its accuracy at classifying out-of-sample clinical trials. The predictors were of two types: characteristic (e.g. phase, number of locations, sponsor type, etc.) and “textual”, or features extracted from text based data like the study’s description and eligibility criteria. Some of these features came from a similar tf-idf vectorization process as described in the k-means section above, other features were the simple character lengths of these text blocks. Below is a plot showing the relationship between two of these features: length of the eligibility criteria block of text, and length of the study’s title, two metrics that perhaps get at the complexity of a clinical trial.


The result: the logit model could only predict correctly whether trials would complete successfully, terminate because of low accrual, or terminate for other reasons 83.6% of the time. This is a pretty small improvement over saying “I think this trial will complete successfully” to every trial you come across, in which case you would be correct 80.6% of the time (see the Completed vs. Terminated pie chart above). Cancer clinical trials are very diverse, so it makes sense that there don’t seem to be any apparent one-size-fits-all solutions to improving patient accrual.



Amazon’s secret sauce: the flywheel model

Amazon’s flywheel of growth. From Andreessen Horowitz’s blog post

After finishing The Everything Store recently, I wanted to share an interesting framework that Bezos used when founding Amazon. The book, by the way, is a phenomenal read and gives great insight into Bezos’s character and how he has led an innovative Amazon. Ambition, persistence, spontaneity, and being neurotic/obsessive are some of the most common traits of the successful people I’ve read about so far, and he certainly embodies all of them.

Bezos thought about Amazon’s business model as a “flywheel” in the early days, and claimed that this was their secret sauce. Without going into what an actual flywheel is, this was another way of saying that the business model possessed a positive reinforcement loop that grew stronger if you fed any part of it. To quote the book:

… Bezos and his lieutenants sketched their own virtuous cycle, which they believed powered their business. It went something like this: lower prices led to more customer visits. More customers increased the volume of sales and attracted more commission-paying third-party sellers to the site. That allowed Amazon to get more out of fixed costs like the fulfillment centers and the servers needed to run the website. This greater efficiency then enabled it to lower prices further. Feed any part of this flywheel, they reasoned, and it should accelerate the loop.

Starting up the flywheel can be difficult, but once results accumulate, momentum builds and business accelerates. In the flywheel model, all incentives are aligned in the same direction. Some strategic and managerial conclusions:

  1. Design for success: the flywheel model is just another example of how leaders can design for the successful operation of their company before any real rubber hits the road. All planning and no action is bad, but having some sort of goal and a plan before doing any serious execution, in principle, works a lot more efficiently than trying things haphazardly and seeing what works.
  2. Design for alignment: a business model is least impeded when the result of anyone’s actions promote everyone’s desires and best interests, especially when that cycle is self-reinforcing.
  3. Do everything to start, protect, and build that initial momentum

Fun fact: during the 1999 holiday season, a lost box of stuffed Jigglypuffs wreaked havoc on a few Amazon distribution centers (they weren’t called fulfillment centers back then). Bezos ordered staff to pull all-nighters looking for the bundle of Pokemon–customers always came first.


What trying to blog somewhat regularly does for me

A young Benjamin Franklin. I’m currently reading Isaacson’s biography of him: it’s brilliant, and Franklin was a baller. More to come later…

I have not been at all regular with my blog. I also have a bunch of draft posts on various topics just sitting there, partially written, mostly because I started writing and got stuck, or distracted, or ran out of time. Noticing that has made me want to write this, a short blog post about blogging (meta-blogging?).

Trying to blog somewhat regularly forces me to structure my thoughts, to come up with a cohesive, brief story that allows me to get my point across and hopefully get others thinking. This is something that I haven’t mastered yet–as evidenced by my collection of half-written draft posts–but I guess that’s the process of becoming a better writer, and where editing comes in. I wonder: do all the best bloggers edit their blog posts? Because I remember editing and revising essays for school over and over again, a process that took a lot of time. Some of the best bloggers that I follow seem to write off the cuff while maintaining brevity and an easy to follow structure in their posts.

The process of regularly structuring my point of view for writing also leads to the discovery of both holes in my thinking and also areas of opportunity that I can do more research on. Blogging also acts as a sort of accountability tactic: if I blog about doing something, then I feel even more compelled to do it. It certainly is a learning experience for me, and hopefully others can learn (about blogging, and about whatever else I talk about and share) along with me.


Warren Buffett: insights into his character, obsession with OPM

Buffett’s house in Omaha, Nebraska. He bought it in 1957 and still lives in it today.

I tend to idolize Warren Buffett a little, something rekindled after recently reading Making of An American Capitalist.

He’s brilliant, humble, focused, self-confident, and frugal. He started his own “golf ball” business as a kid, employing an army of friends to fish out golf balls from ponds in local golf courses,  and then to clean, organize, and resell them. During his short time at Penn, Buffett joined a fraternity. He would spend parties at his frat house sitting on the ledge by a window, expounding on investing, the gold standard, and other economic concepts–a throng of guys and gals would always gather on the floor in front of him, hanging on his every word. In the early days of running his first fund, Buffett was insanely secretive about his investments, working from his home like a hermit, only wearing t-shirts and underwear, and refused to compromise on his fund’s 6 month lock-up period and $50,000 minimum investment (a lot at the time), even for celebrity investors. Those are just some of the captivating insights into Buffett’s character.

Buffett’s vast amount of wealth does not necessarily intrigue me that much–it is about how he build it: with self-reliance, focus, discipline, and authenticity.

He is also obsessed with “other people’s money”, or OPM, and OPM is essentially how he was able to build such a great fortune. One of Buffett’s first outright purchases of a company was an insurance company–he owns the well known GEICO today–and he used the float to fund his investments. That early purchase is said to be worth half of Berkshire Hathaway’s value today–this insightful post by Noh-Joon on Quora explains that, as well as how Buffett is able to essentially turn a 5% increase in actual investment appreciation into a 15% return (hint: leverage and effectively negative interest rates from insurance underwriting discipline). Not to mention, he’s a great stock picker.


Some books I’m reading, and why

Ever since I got my Kindle 3 years ago, I’ve been reading more. A lot more: before my Kindle, I’d probably average less than one book a year (not including those required for school). For me, it seems that the convenience of reading was a big factor.

Why do I read? As Newton said, to “stand on the shoulder of giants”. So much of mankind’s history, so far, has been recorded in physical writing–not online. Books are still the best way to see into the minds of the greatest scientists, philosophers, leaders, businessmen, etc. of all time.

It’s a balance of course, between actually taking action, and sitting down to spend time learning. The two behaviors are not mutually exclusive: one does learn from taking action, usually skills. Experience–success and especially failure–can teach very important lessons. One can’t meet new people by reading books all the time either. Sometimes though, one can discover brand new ideas and ways of thinking by reading books, ideas that are only talked about in-depth through text, by those in our history who have made a big impact. It is a different way of broadening horizons and gaining perspective.

Onto a few of the favorite books that I am reading, or have read recently, and a short reason why:

  • Buffett: The Making of an American Capitalist, Roger Lowenstein
    • The first/original biography on Warren Buffett. Intriguing insight into who he was–and is–as a person, and what characteristics of his personality and events in his life made him so successful, walking the reader from early childhood through the rescue of the Salomon Brothers
  • Mindset, Carol Dweck
    • A book backed by lots of research studies on what the “growth mindset”  is, how it’s so related to success in life, and how to develop it. A good balance of theory and practicality.
  • One World Schoolhouse, Sal Khan
    • Khan, the founder of the successful and impactful Khan Academy, makes convincing arguments for school reform, and talks about his project and how Khan Academy is the start of an educational revolution. He also talks a little bit about his childhood and subsequent path to the founding of Khan Academy. Inspirational and informative.
  • Hooked, Nir Eyal
    • A very practical and impactful book on building habit forming products, products that have fiercely loyal customers who come back to use the product day after day, from someone who has lots of experience doing so. I’ve heard this one recommended a lot by my start-up friends, and it’s one that I often recommend as well, to entrepreneurs looking for a more practical, “business” book.
  • Power of Habit, Charles Duhigg
    • Basically, the science behind Hooked. I believe habits are one of the greatest “force multipliers” in life (definitely a post for another time), and in his book Duhigg presents the science behind them so we can better understand and utilize the power of habits.

You can see I prefer non-fiction, the reason why is pretty utilitarian.