Leather: Building the Frontend

1. Consistency I’ve attended a company management meeting each Wednesday afternoon since late July, when I started managing my engineering team. Managers from each sector of my company gather to give weekly reports on revenue, product developments, and other progress from the week prior. Afterwards, the CEO gives a presentation on some topic that’s relevant to management (feedback, recruitment, motivation, etc.). These presentations usually entail about five minutes of her personal thoughts and another 25 minutes of business advice from a handful of management-focused YouTube channels. Unsurprisingly, I tend to glean fairly little from the YouTube segment of the meeting. Yesterday, though, I found myself intrigued by the mantra of the meeting: quantity over quality. This isn’t what I typically believe, and I would normally dismiss someone’s advocacy of that position as contrarianism. <a target="_blank" href="https://www.youtube.com/watch?v=NOl4YXXiiZ0">One video</a> argued that many of history’s most renowned creators were also some of history’s most prolific. They cited Picasso, who apparently painted over 10,000 paintings and was obviously a master of his craft. Van Gogh, they said, was similarly prolific. Thomas Edison supposedly filed for around 1,500 patents, of which 1,000 were awarded, and one of which was the light bulb. I’m pretty receptive to this argument - that anyone with sufficient practice and output will produce something bright along the way. However, the video goes a step further, claiming that quantity is the cause of quality. Another manager chose this moment to thank our CEO for suggesting that he read Malcolm Gladwell’s The Tipping Point, which he mischaracterized as the book where he first learned of <a target="_blank" href="https://en.wikipedia.org/wiki/Outliers_(book)">the 10,000 hour rule</a>. Very cool. At any rate, there’s some truth to this view. None of us starts as an expert in any domain, and it’s comforting to believe that any of us can become an expert with sufficient commitment. As an analogue to my <a target="_blank" href="/posts/patience-by-default">post on Patience</a>, I’m guilty of not always demonstrating great perseverance, and I’m striving to do so better. This managerial meeting was a welcome reminder of that pledge. I’m actually writing this blog post today in an effort to do good on my commitment to commit. I went to all the trouble of building this blog; it would be a shame if I didn’t write to it more often. I’ve therefore promised myself that, at least through the end of 2021, I will author a new post each Thursday. Today is the first of those Thursdays. This process will also encourage me to lower my standards for this blog, as I’d ideally like to write more freely (i.e., about whatever’s on my mind that day), and I think weekly posts will force me to do just that. If the quality of my work improves as well, I’ll take it. 2. Appreciation My team is welcoming a new member this week. It’s my first time onboarding someone since I became the team lead, and it’s served as a welcome opportunity for reflection. I’ve done my best to involve all the existing team members in the new recruit’s onboarding; they’ve explicitly trained him, answered Q&As as a group, helped him set up tricky environments, and mentored him during shadowing sessions. I’ve been really pleased with their efforts. Deciding who would own which section of the new hire’s onboarding required that I consider everyone’s personal attributes, experiences, and areas of expertise. For instance, I wanted an experienced and technical team member to explain our code base. I wanted someone with a good grasp on process to explain how and why our team operates like it does. I wanted another recent hire to take on a high degree of personal mentorship, as the recent hire is familiar with onboarding and what it takes to get up to speed with the team. Furthermore, I realized that this week could serve as a stellar opportunity for us all to learn. If someone with particular expertise would be teaching the new hire, that expert might as well impart that knowledge on the entire group. So each day this week, we’ve hosted workshops where those expert teammates lead presentations on a particular aspect of what our team’s engineering position involves. As much as I prefer to let individuals self-organize, I, as manager, had to decide who would lead which workshop, given that I wanted to a) have people lead talks about one of their core competencies; and b) not have that much overlap between talks. Assigning these workshops, then, required some reflection on each team member’s unique qualities and abilities. I was reminded of how, when I became the team lead, I was more focused on what each team member was lacking than I was on each of their specialties (“superpowers”, writes Julie Zhuo in her guide <a target="_blank" href="https://www.juliezhuo.com/book/manager.html">The Making of a Manager</a>, which I recommend highly). But time, openness, and weekly 1:1s, also inspired by Ms. Zhuo, brought familiarity with each team member. And familiarity brought appreciation. I was blown away by the quality - and value - of the workshops. I watched the technical members’ eyes widen as another, less technically savvy teammate described how he organized his tasks and lessons to stay on top of his work and improve. This more organizationally sound member took diligent notes while another described his tactics when updating code. We each contributed our own thoughts in an open forum at the end of the workshop. I’ve learned from each of them, and I’m certain that each team member found value in each other’s workshop. It’s neat to have facilitated that sort of knowledge transfer, and it makes me think I’m taking some important steps as a team builder, as well becoming more appreciative of the differences that make us each stand out. I know how easy it is to fixate on the faults of those around us, so I’m pleased that my perspective has shifted and that I’m starting to recognize the strengths of those around me instead. 3. Detachment My first week as manager, I spent my Friday night at my desk until 10pm, toiling away at my weekly report, which I was to send to my CTO, among other executives, for the first time. Desperate to prove myself, I spent hours drafting unnecessarily complex charts and editing my email. When I finally sent it in, I collapsed on my couch, utterly drained from a week that overwhelmed me with the authority and accompanying responsibility that I’d been given. I spent that weekend finishing my first book on management and preparing for the upcoming week, for which I swore I would be better prepared than I was the first. During that first month, I stayed late each day. Whether I was catching up on organizational tasks, helping another teammate complete his/her work, or finishing my own individual responsibilities, I felt there was always more that needed to be done. And now, whatever was (or wasn’t) completed was my responsibility. I left the office each day exhausted, and the weekends were only a mild reprieve. Now, almost three months in, I’ve learned to take a step back. I’m no longer allowing my job to occupy my thoughts outside of work; to do so would devour my life. I’ll work late as is required to finish the tasks that I deem necessary to complete that night, but once I shut my laptop, my time is mine. I take time during the workday on Friday to draft my weekly report, which I submit by 6:30 that evening. From that point onward, though, I don’t consider work again until Sunday night. I’m now able to see friends, travel, explore, and play during my time, which I can credibly deem free. Professionally, I’ve learned how to delegate and channel work through my team members, and I’ve lessened my individual workload in order to allow myself time to help my team accomplish its larger goals. I do believe that I’m the most competent engineer on my team, which initially made it difficult to pare back my individual contributions, but I’ve begun to appreciate that, at least in my current position, I’m of more value to my team and company when I grant myself capacity to focus on my managerial responsibilities. I recognize the incongruity in my writing this post about work, and next week, at least, I’ll refrain from writing about my professional experiences. Hopefully I’m up to something interesting.

80 Days of Management

In September 2020, I bought call options on $SPG, <a target="_blank" href="https://en.wikipedia.org/wiki/Simon_Property_Group">Simon Property Group</a>. I was betting that, come the end of December, the stock price of America’s largest mall owner would rebound past $75, on the strength of COVID optimism and potential new use cases for SPG’s properties. Today, a share of $SPG sells for $124.50. This wasn’t an unusual bet for me to place. I also bet on UPS in August of last year, when newly appointed Postmaster Louis DeJoy oversaw <a target="_blank" href="https://www.npr.org/2020/08/19/903982558/dismantling-mail-sorting-machines-could-leave-a-lasting-mark-on-the-postal-servi">the disassembly of integral mail-sorting machines leading up to the 2020 election</a>. I bought cryptocurrencies around the time of the <a target="_blank" href="https://www.investopedia.com/bitcoin-halving-4843769">Bitcoin Halving</a> in May, as previous ‘halvings’ had pushed crypto prices to new highs. I’m clearly a gambler. Still, in hindsight, each of these investments should have been profitable. By 2021, Simon Property Group’s stock price exceeded $85. UPS increased by about 10% over the relevant period. Bitcoin’s price septupled from the time I bought it to its all-time high in April 2021. The $1,000 of Dogecoin that I bought in April 2020 was worth about $260,000 a year later. Regrettably, I didn’t see much of those profits. Demonstrating what’s known on <a target="_blank" href="https://www.reddit.com/r/wallstreetbets/">r/wallstreetbets</a> as paper hands, I got nervous and cashed out when my investments weren’t immediately fruitful*. Sometimes I sold for a loss, but often I just sold for less than what I would have earned, had I held on to my assets for longer. *Investors with diamond hands, conversely, hold on to their assets through adversity. I succeeded in developing a strategy, which I expected to be the difficult part. But my inability to ride out turbulence in the market prevented me from realizing the profits my investments could have yielded. Somewhat separately, if I had been willing to park my money in an index fund ($SPY, say) over the course of 2020, I certainly would have been more successful than I ended up being gambling on sharp price changes via options. But I had neither the forethought to plan with patience (index fund) nor the patience itself to ride out difficulty with my riskier bets (options). Patience is, of course, the subject of this post. From my work, my social life, and my investments, I’ve been noticing how patience has improved outcomes in several aspects of my life. I’ve also realized just how averse I’ve been to patience until now — especially to what I’m calling indeterminate patience. It’s fairly easy, I think, to exercise patience when an outcome is expected. Take the <a target="_blank" href="https://en.wikipedia.org/wiki/Stanford_marshmallow_experiment">marshmallow test</a>. If I know a second marshmallow is coming, I can wait to eat the first. Even if you don’t know what the outcome will be, waiting with the guarantee of some outcome is usually manageable. It’s easy to wait, too, when you know how long you’ll be waiting. But indefinite patience for an uncertain outcome — indeterminate patience — is a capacity I’ve only begun to develop, particularly after my college graduation in May 2019. The timing makes sense; there are few times in the structured environment of education when you need to practice that type of patience. You bounce from year to year, summer to summer, with complete knowledge of what lies in store. Your assignments are reliably returned, and you can sometimes plan out your curriculum years in advance, due to major requirements or lack of choice. There are, of course, circumstances throughout your education that demand something bordering indeterminate patience. If you want to earn captaincy for your team or presidency for your club, you may need to wait until you have sufficient experience and status within that organization to reach your goal. But there’s still a process, a structure, a promise that by fulfilling certain criteria, you will have a chance to succeed. You know how long it will take, and you know what you will need to do to increase your odds of success. After earning my bachelor’s degree, though, I, along with countless peers, stepped away from structure for what seemed like the first time. I’d experienced unstructured life for set periods — think summer internships or a semester abroad — but never indefinitely. With that lack of structure (alternatively, freedom) came an inability to envision my non-immediate future. I became frightened by uncertainty to the point that I neglected to consider my future at all; my fear manifested as short-termism. I took financial risks, gambling on the stock market and in casinos (although I’m not giving up poker). I took professional risks, leaving my first job after college well within a year. I took risks in my personal relationships. Given my impatience to invest over time in various facets of my life, I took shortcuts and hoped that I could luck my way into immediate gains — which I told myself could translate into a leg up for… well, whatever came next. I’ve settled into myself since graduating, and some criteria for success, at least for this stage of life, have emerged for me: hard work, intention, empathy, and patience. But only in the past few months have I begun to appreciate how easily one’s prospects can improve through disciplined investment over time. For instance, I hope and believe that I’ll become the manager of my engineering team by the end of the year, despite having joined my company only six months ago. This would be, of course, partially due to circumstance and good fortune, but my drive and effort — inspired by my commitment to working here for the foreseeable future — are already bearing fruit. If I were in this position at an earlier point of my life, I have no doubt that I would have become discouraged by the level of investment that success demanded. That being said, I don’t want to come off as a ride-or-die commitment advocate. There’s certainly a knowledge threshold for a given investment, after which I believe you’re justified in severing it. If you know that the job is wrong for you, you should leave. Paying mind to the <a target="_blank" href="https://thedecisionlab.com/biases/the-sunk-cost-fallacy/">sunk cost fallacy</a>, the difficulty lies in determining when you know enough to make a decision. In terms of decision-making, then, I suppose I consider patience to be the choice to continue to collect information, so the best decision-makers are the most able to realize when they’ve developed sufficient knowledge about a situation or investment to make a judgment. I, for one, am guilty of overestimating my level of knowledge of a given investment, which has historically brought me to rash decisions. I want to emphasize, though, that patience is a practical option. I don’t believe that it is an inherent good or that it should be practiced for its own sake. Rather, it offers two primary benefits at the expense of time (and <a target="_blank" href="https://www.investopedia.com/terms/o/opportunitycost.asp">however you would use that time</a>): knowledge and the myriad benefits of commitment*. *I’ve portrayed commitment and patience almost interchangeably in this post, and I should address that conflation. Commitment and patience are not the same. However, I believe that they should be employed together in almost all situations that demand indeterminate patience. If you’re patient but non-committal, you won’t be incentivized to pour your full efforts into an endeavor, and you won’t have the belief to stick by your investments. If you’re committed but impatient, you’ll be unable to realize the full benefits of your investments and will probably become embroiled in self-loathing from your constitutional inconsistencies. Employing patience and commitment in tandem requires intention, and it requires discipline. I’ve failed to embody all of these qualities at times, but I’m striving now to equal my own principles. Because the majority of benefits you can earn (a healthy relationship, a fulfilling professional position, a successful portfolio, etc.) require commitment, patience by default, upon entering an investment, should be a winning strategy. In other words, if you have to commit to something to find success, you should probably commit to commitment generally. Through your patience (and accompanying commitment), you’ll eventually develop sufficient knowledge to determine whether your investment is worthwhile. If it is, you hold; if it’s not, you cash out. Not all investments are worthy of your limited resources, but lacking patience with your investments will prevent you from realizing the full benefits of any. So be deliberate in your choices of investment, and have enough confidence in your initial judgments to exercise patience until given sufficient reason to do otherwise.

Patience by Default

For those of you who don’t know, the 2021-22 football season will boast a brand new UEFA tournament: the UEFA Europa Conference League (UECL). The UECL will represent the third tier of European club competition, below the Champions League and the Europa League. Much like the Europa League is a tournament for teams that are generally a calibre below the Champions League, the UECL is for teams that are generally a calibre below the Europa League. We’re talking clubs from the Finnish Veikkausliga, the Belarusian Premier League, the Andorran Primera Divisió, and every other top-flight domestic league from UEFA-participating countries, including the top 5 European leagues. Yes! This is real, and it’s coming to a screen near you this summer. But before we get to the intricacies of the UECL, we need to discuss some important Europa League changes for next season. The Europa League The Europa League, in the past, has offered clubs from lesser known leagues a chance to compete for European glory. Starting this upcoming season, though, only clubs from the top 15 European leagues, as determined by their UEFA country coefficients, will be eligible for direct entry into the Europa League. Yes, you read that correctly: Only clubs from the top 15 European leagues will be eligible for direct entry into the 2021-22 Europa League! Of course, the winner of each European league will still participate in the Champions League, and losers of each round of the Champions League, through the group stage, will trickle down to the Europa League. So champions from each league will still have the “opportunity" to participate in Europa League football if they drop down from the Champions League. But non-champions from leagues outside of the top 15 will no longer have any path to participate in Europa League. The top 15 leagues for 2021-22 UEFA competitions belong to, in order: <ol><li>Spain</li><li>England</li><li>Germany</li><li>Italy</li><li>France</li><li>Portugal</li><li>Russia</li><li>Belgium</li><li>Ukraine</li><li>Netherlands</li><li>Turkey</li><li>Austria</li><li>Denmark</li><li>Scotland</li><li>Czech Republic</li></ol> Of those, Spain, England, Germany, Italy, and France will each send two clubs to the Europa League. The rest will send one. If you can’t find your country in that list, then the only club from your country that can play in the Europa League is your domestic champion, and they will have to drop from the Champions League to do so. So you can kiss goodbye to one of Basel or Young Boys — The Swiss Super League is ranked 17th. The second ranked Greek team, too, won’t have any avenue to participate in Europa League. These changes will make for a much shorter Europa League campaign than those of the past. There will be only one Qualifying round and one Play-off round before the Group Stage, and the Group Stage is shrinking to 32 clubs from 48. The majority of participants in the Europa League will have dropped in from the Champions League. This all sounds awfully sad for Basel. They’re currently sitting 20 points behind the leading Young Boys, which means they’re already out of the running for the Swiss Champions League spot. But now they aren’t even eligible for Europa League! Fear not. Basel (if they can improve their form) will still have an opportunity to bask in the spotlight of European football. The UEFA Europa Conference League The UECL is UEFA’s solution to a long-standing competitive problem. Even in the Europa League — the second tier of European competition — smaller clubs haven’t really been able to compete with clubs from Europe’s top leagues. Since the Europa League’s rebirth in 2009, only 7 clubs outside of the top 6 leagues (top 5 + Portugal) have made the semi-finals of the competition. That’s 16%. Only 2 such clubs have made the final, for 9%. None have won. This isn’t shocking, but it also doesn’t sit quite right with me. Fans of the big boys hardly pay attention when they draw Standard Liège in the Europa League Group Stage; it’s a given that they’ll advance. Similarly, this sucks for Standard Liège, who routinely get thrashed by Arsenal and Sevilla and end up third or fourth in their group. The whole affair just isn’t that fun for anyone. So UEFA made a change for 2021-22, which will last through 2023-24 (three seasons). They’ve essentially cleaved Europa League in two. As described above, Europa League is now reserved for fallen champions and non-champions from the top 15 leagues. Everybody else who used to get smacked in Europa League now gets to duke it out in the UECL. And the prize? The UECL winner earns automatic entry into the Group Stage of the following season’s Europa League, just like the Europa League winner earns entry into the Champions League. Who Gets to Play? In all, 173 clubs will participate in the UECL. Of those, 128 clubs will be direct entrants into the UECL, and the remaining 45 will have dropped in from the Europa League or Champions League. I’ll first address how the 128 direct entrants are determined. Like the Europa League of years past, every UEFA-participating nation will enter at least one team in the UECL. However, unlike in the Europa League and the Champions League, the top leagues will send fewer teams to the UECL than the other leagues. The top 5 leagues will each send only one club. For Spain, Germany, Italy, and France, that club will be the top club in the domestic league that doesn’t earn Champions League or Europa League football. La Liga, for example, will send its 6th-placed club (currently Real Betis), assuming that that club doesn’t earn Europa League football either: a) by winning the League Cup; or b) by a Champions/Europa-qualified club winning the League Cup. England, excitingly, will be sending the winner of the EFL Cup to the UECL. If that club is already in European competition, though, as is likely, then the 6th-placed club in the Premier League will represent England in the UECL. At time of writing, Tottenham are 6th on the Premier League table and are in the final of the EFL Cup against Manchester City, so they’re probably my favorite to earn entry into the UECL for 2021-22. (July edit: It is Tottenham.) The same principle for the other big leagues applies to England, too. If 5th and 6th place qualify for Europa League by virtue of a 1st-6th club winning the FA Cup, then 7th place will enter into the UECL, assuming 1st-7th wins the EFL Cup. Leagues 6-15 will each send two clubs. These will generally be the 3rd- and 4th-placed clubs from those leagues. Leagues 16-50 will each send three clubs: the domestic runner-up, the domestic 3rd-placed club, and the domestic cup winner. These clubs will comprise over 80% of the direct entrants into the UECL and over 60% of total UECL participants. Leagues 51-55 will send only two clubs: the domestic runner-up and the domestic cup winner. Liechtenstein, of course, has its own rules. Because the country of 38,000 enjoys only 7 professional clubs, it doesn’t have a domestic league. However, those clubs sportingly compete for a domestic cup, and the winner of that cup will be the sole Liechtensteinian club to earn entry into the UECL. Those are all the direct entrants into the UECL. The rest of the participants will drop down from the Champions League and the Europa League. Of the 45 drop-downs, 20 will enter UECL Qualifiers directly from the Champions League’s earliest Qualifying rounds, so expect to see the Gibraltarian champions and runners-up in the UECL. 7 Europa League teams will drop into the UECL during the Play-off round, which will send 22 clubs through to the Group Stage. An additional 18 Europa League clubs will drop down during the Group Stage and beyond. The Format The UECL sports three Qualifying Rounds and a Play-off round prior to the Group Stage. The clubs from the lowest-ranked leagues will enter earliest, and clubs with better credentials (better league position, better league, or both) will enter later in the qualification process. The big clubs, from the top 5 leagues, will enter during the Play-off stage, where they’ll have to compete for a spot in the UECL Group Stage against: a) clubs that have advanced from earlier qualifying rounds; and b) the 7 Europa League clubs that lost in the final qualifying round of the Europa League and dropped down. 22 teams will advance from the Play-offs to the Group Stage, where 10 more Europa League drop-downs will join the competition. The 8 winners of the Group Stage will move onto the Knockout rounds. Group Stage runners-up, though, will have to earn their place in the Knockouts. The 8 Europa League clubs that come in third in their Europa League Group Stage will drop down and compete with the 8 UECL Group Stage runners-up for Knockout spots. With 16 teams remaining after the Group Stage and preliminary Knockouts, the tournament will begin the Knockout stage and progress exactly like the Champions League and Europa League. And the winner of the whole deal will earn automatic entry into the Europa League Group Stage the following year. That’s It That’s the tournament! There are clearly lots of changes on the horizon for continental competitions, and I’m looking forward to watching some fierce contests between lesser known sides take place in the UECL. UECL matches will be on Thursdays, at the same times as Europa League matches, and the first Qualifying Round begins on July 8, 2021. I'll probably start watching when the big clubs enter the fray, during the Play-offs, which begin on August 19, 2021. The Group Stage will start a month later, on September 16, 2021. And the inaugural UECL Final will take place on May 22, 2022, at Arena Kombëtare in Tirana, Albania. Save the date now, because we’ll all be following the UECL Knockouts at this time next year. TL;DR The Europa League is accepting fewer teams for seasons 2021-22 through 2023-24. The teams that got kicked out of Europa League due to this change will be joining a new competition: The Europa Conference League. It's basically the same thing to Europa League that Europa League is to the Champions League. The winner of the tournament will earn automatic entry to the Europa League Group Stage. Maybe Tottenham can win a trophy!

The 2021-22 Europa Conference League

I’ve participated in daily fantasy soccer on DraftKings for a few years. In an effort to increase my profitability, I recently began working with a statistician to develop a model that predicts player performances. Our model has been performing well, but I’ve had to painstakingly sift through the model’s output to actually select lineups; keep in mind, the statistical model merely predicts the number of fantasy points a player will earn for a given match. It does not advise on how to select from the players, even if we now have insight into their likely performances. Before I get into any more technical details, though, I ought to explain how <a target="_blank" href="https://www.draftkings.com/help/rules/8/123">DraftKings soccer</a> works. Each match, you’re asked to choose 6 players from the 22 who are on the field. Those 6 players, over the course of the match, will accumulate points through certain actions. For example, scoring a goal earns 10 points. Saving a shot, as a goalkeeper, is worth 2 points. Your objective is to choose 6 players that will perform better than the players that other DraftKings participants choose, as payouts only go to lineups above a certain percentile of the competition. Did I mention this is gambling? As you can imagine, some players are more likely to perform well than others. Cristiano Ronaldo, for example, will probably be the highest scorer in a given game. So why doesn’t everyone choose Ronaldo to be in their lineup? Because every player “costs” a certain amount, and he’s probably the most “expensive” player available. The price of a player generally reflects his likelihood of high performance, and Ronaldo, a reliably exceptional player, will cost an outsize portion of your budget. You have to determine whether the price of a player is worth his possible point output. That’s the name of the game: maximizing the points you can get from your lineup, given a fixed budget. Accurately predicting how players will perform, then, is a huge aspect of success in DraftKings. If you can predict with reasonable confidence that Ronaldo will outperform his average against, say, the worst team in his league, then maybe his steep price will be worthwhile. This is the value of my statistical model: it predicts with reasonable confidence how each player will perform. But predicting performance isn’t the whole picture. You still have to choose the players. After spending hours over the past weekends hand-selecting my lineups (as advised by the model), I decided I needed to refocus my efforts on one of the more difficult tasks I’d set before myself: optimizing the lineup. This may not sound tricky. Why can’t you just test every lineup, right? And choose the one that gets you the most points while remaining below the spending limit? Unfortunately, checking every option isn’t really a possibility. In case you don’t believe me, check out the <a target="_blank" href="https://en.wikipedia.org/wiki/Wheat_and_chessboard_problem">rice and chessboard proverb</a>. So I’ve known for a while that, if I want to really streamline this whole DraftKings thing and potentially automate the entire process of setting a lineup, I’ll need to tackle lineup optimization. I could probably approximate an ideal lineup by taking players with high value/price ratios, or something like that, but I want to solve this thing for real. Luckily, I studied a similar problem in a college algorithms course: the knapsack puzzle. Consider a thief in a department store. He sneaks in without tripping the alarms, and he discovers a vast array of items before him, spanning multiple floors. But he has only one backpack to fill. The thief, of course, is planning on selling the items he takes from the store, so he wants to fill his backpack with valuable items. How does he choose which items to take? His backpack has finite volume, and each item in the store has an associated value and volume. For instance, a piece of hanging art may be quite valuable, but it’s also likely to take up the majority of space in his bag. Pebbles from the koi pond, though they may be small, are worthless. Ideally, I think, he’d head over to the jewelry section and stuff his bag with diamond rings, which each have high value and take up very little space, so he can fit more valuable items into the bag. The knapsack algorithm, which solves the knapsack puzzle, is meant to determine, efficiently and accurately, how to select items given a “value” and “weight” (volume in the last example; price for DraftKings) associated with each item and a cap on the total “weight.” If you’re mathematically inclined, check out <a target="_blank" href="http://cse.unl.edu/~goddard/Courses/CSCE310J/Lectures/Lecture8-DynamicProgramming.pdf">this resource</a> from a Data Structures and Algorithms course at the University of Nebraska-Lincoln. It explains the premise well. At any rate, the standard knapsack algorithm involves a technique called dynamic programming. I promise it’s not as daunting as it sounds. Imagine you want to count to 10 using as many vowels as are possible in your numbers, but each number “costs” the value of that number. And say you only have 10 points to spend. For instance, “eight” has two vowels, and it costs, well, 8 points. Yeah, this would be a nuisance to count out. But we can approach it strategically. We can count up from the bottom and keep track of the highest-vowel combinations for each point threshold using a simple table. Let’s start with one. It has 2 vowels. So the maximum value we can obtain from using 1 point is 2 vowels. Two only has 1 vowel, and since we can’t repeat numbers, our maximum value from 2 points is 1 vowel. But when we get to three, we have a choice: to choose the combination of one and two or to choose three. One and two, combined, cost 3 points, and they have 3 vowels between them. Three, on the other hand, only has 2 vowels at the same cost of 3 points. So we choose the one-two combo and jot it down. Now, whenever we need to know the maximum value of 3 points, we can simply look it up in the table, rather than calculate it again unnecessarily. We can continue in that fashion — calculating values by using past calculations — until we’ve essentially calculated every combination and arrive at the answer (7 vowels). For that problem and other traditional knapsack problems, you can take as many items as you want; there’s no hard cap on quantity; only on weight. The DraftKings lineup optimization problem involves a limit on the number of items you can choose. There’s an additional wrinkle I haven’t addressed: the captain of your lineup. When you’re constructing a DraftKings lineup, you select one player to be your “captain”. The captain earns 1.5x points (a goal is worth 15, rather than 10), but he also costs 1.5x his normal price. Choosing the correct captain can often determine whether your lineup makes or loses money. So there are two dimensions of this problem that are beyond the standard knapsack algorithm: a 6-player limit and the captaincy. After some digging online, I concluded that this would not be a copy-and-paste sort of algorithm, as there was no clear solution on typical forums (StackOverflow, etc.). Given the complexity of the problem, I want to warn non-technical readers: the rest of this article may not be very digestible. I wrestled first with the capacity limit. I spent considerable time trying to tally the item count in my tracking matrix, like the one I described in the vowel-counting example. Instead of populating my matrix with simple values, though, I tried populating it with [value, num_items] tuples, thinking that I could stop adding new items once num_items reached the item limit. But that didn’t work. Any players toward the end of the list were excluded, even if they would be included in an optimal solution. I eventually realized the solution: dynamic programming. Yeah, the technique we’ve been using this whole time. Just like I’ve been using dynamic programming to calculate values for standard knapsack problems, I can use it to calculate the best value for each weight and item number combination, for each item limit (i.e. add a dimension). Meaning, I could start by creating a new matrix, for which each cell would have an item limit of 1. I populate that table, incorporating my prior [value, num_items] data structure, and set the limit of num_items that comprise each cell value to be 1. So if I’m considering adding to a value that already has incorporated the maximum value of items for that matrix, I won’t add it. Then, for the next matrix, I’ll increase the item limit by one, eventually creating a matrix of matrices, with one matrix for each number 1…Q, where Q = the lineup size. And instead of simply choosing the prior iteration’s value, as one normally would when the other potential prior value already boasts the item limit, I can check against the prior matrix. The values in the prior matrix are limited to one fewer item than the current matrix’s limit, so if the sum of that value and the current player’s value exceeds the prior iteration’s value, I’ll have found extra value that would otherwise have been missed. This aspect of the algorithm — matrix jumping — is integral to the solution. The final cell in the matrix set (matrixSet[Q-1][n][W]) will contain the maximum possible value. With that value and matrix set in hand, I can employ the standard 0-1 knapsack backtracking technique, modified to hop to prior matrices as necessary, to determine which players comprise the solution. If you’re code-literate and want to see the algorithm, please check out the <a target="_blank" href="https://github.com/rgsthethird/ConstrainedKnapsackAlgorithm">source code</a>. The program outputs an Excel file, which contains the optimal matrix set, although you have to install the <a target="_blank" href="https://openpyxl.readthedocs.io/en/stable/#">OpenPyXl package</a>. After tackling the limit problem, I resolved to take a slightly different approach for the issue of captaincy. I decided to reformulate the matrix set n times, and each time I would designate a different player captain (i.e. multiply his value and and weight by 1.5). I would keep track of the solution that yielded the highest point total and the captain of that matrix set. After iterating through all possible captains, I’ll have found the optimal captain and lineup, given that captain. When backtracking, I reestablish that player as captain in the data set. Finally, the algorithm is complete. For each potential captain, create Q matrices, and run a somewhat standard 0-1 knapsack algorithm for each matrix. Because the algorithm utilizes dynamic programming to build up to Q players, it occasionally backtracks to a prior matrix to improve on the value of that iteration/weight cell. For the techies out there, the algorithm has a time complexity of O(nWQ), where n = number of players, W = weight limit, and Q = quantity limit. When selecting a captain, the time complexity increases to O(n2WQ), as the algorithm cycles through each player one additional time. Still, there are variations of this problem to solve. Notably, other DraftKings soccer lineups require certain positions, such as Defender or Midfielder, to be filled. I’ll update this post once I’ve completed that variation of the algorithm, but I may not get to it for a bit.

Developing a Practical Algorithm

I recently finished <a target="_blank" href="https://www.amazon.com/Great-Firewall-China-Alternative-Internet-ebook/dp/B07MB474LV">The Great Firewall of China: How to Build and Control an Alternative Version the Internet</a>, written by CNN journalist <a target="_blank" href="https://www.cnn.com/profiles/james-griffiths">James Griffiths</a> in March of 2019, while I was sequestered in a cabin in a remote area of Washington State. I had read half of the book over the prior month, but this vacation provided a welcome opportunity to complete it. Before I began The Great Firewall, I knew that China boasts a robust technological ecosystem, as is demonstrated by the multitude of global technological entities that originated in China. TikTok is among the most recent and prominent examples. Huawei, the Chinese telecom giant, has inked contracts with governments across the world to develop their 5G networks. Alibaba appears to be Amazon’s sole rival in the global e-commerce arena. Almost undeniably, the only competitor to the American technological ecosystem is that of China. This I already knew. I was also vaguely aware of how China has banned some American technologies and companies from the Chinese market, through its “great firewall.” Similarly, the U.S. government has forced Chinese products and corporations from the American marketplace. These areas of knowledge were sufficiently interesting to compel me to learn more. So I purchased Griffiths’ book. Though the title suggests a technical manuscript, The Great Firewall is far from it. In my view, the firewall itself is actually the secondary topic of the book; the first is China’s philosophy of censorship and how that philosophy, combined with China’s technological prowess, has begun to overtake liberal, American ideals that promote freedom of information. The Great Firewall addresses the origins of the Chinese internet, the individuals responsible for the development of the country’s surveillance apparatus, how the Chinese Communist Party and the state internet work in tandem to support economic policy, and how the world has begun to split along authoritarian and liberal lines, each of which is supported by a technological and economic powerhouse in China or America. Readers who wish to develop a comprehensive, technical understanding of China’s firewall will be somewhat satisfied, but they should prepare themselves for a more human, political approach to the topic, than one that is overtly technical. My key takeaways from the book are also more political in nature than they are technical. In the opening pages, Griffiths ushers his readers into present-day China, to a setting with which most readers are likely familiar: the ongoing, pro-democracy protests in Hong Kong that arguably began in 2019. He describes protesters who employ encrypted telecommunication apps to circumvent government censors and monitors, in addition to their <a target="_blank" href="https://www.bloomberg.com/graphics/2019-hong-kong-protesters-umbrellas/">iconic umbrellas</a> used to combat physical attacks from authorities. Griffiths transitions from the protests to a geopolitical and historical account of China’s internet, acknowledging how Chinese officials quickly recognized the duality of the internet as a tool for both rebellion and suppression in the early 1990s. Through this lens, Griffiths describes how members of the Tibetan diaspora were closely monitored by Chinese authorities once they developed access to the internet; he details how the Uighurs, the ethnic minority population that inhabits the northwestern Xinjiang region of China, experienced complete internet blackouts as government-backed Internet Service Providers locked down the region in response to violent disputes taking place between Uighurs and the ethnic majority Han population in the opposite corner of the country. A picture began to come into focus: one in which China has exploited the internet to interrupt communication within groups that threatened the state-established status quo. The government also employs legions of human censors that supervise message boards and forums, flagging discordant information and promoting the party line through direct engagement with the supervised forums. After decades of development, the “great firewall,” which operates on an internal, national level and also filters information from international sources, automatically detects and removes undesirable content, such as pornography or speech disapproving of the CCP. Though Griffiths describes somewhat rudimentary blacklists, which include domains and IPs that are prevented both from circulation within China and from entering the country, I suspect that the advent of machine learning is bringing more effective censorship and surveillance techniques to the firewall. Griffiths does not address such advances. The “great firewall” also counts the majority of Chinese tech firms among its organs. The CCP, having rebuffed the attempts of American technology giants, such as Facebook and Google, to penetrate the Chinese market, has worked with local innovators — frequently veterans of the People’s Liberation Army — to develop technologies native to China that can compete with American firms. Among these are the aforementioned Huawei, ByteDance (the original developer of TikTok), and Alibaba, as well as Google emulator Baidu and technology conglomerate Tencent, which operates the <a target="_blank" href="https://www.businessinsider.com/chinese-superapp-wechat-best-feature-walkthrough-2019-12">ubiquitous “super-app”, WeChat</a>. These corporations, in addition to almost every technology startup in China, agree to self-censor and report dissidents to the CCP. Given the ever-expanding role that these monoliths play in regular Chinese life, citizens are largely unable to avoid using the very technologies that are designed to regulate the style and content of their communication. All the information citizens can access online has been pre-approved by the company or individual that provides it; in turn, it has been approved by the CCP. The complete system, with state-backed individual censors, automated ISP monitors, and technology companies that act as their own watchdogs for fear of government repercussion, is unavoidable for Chinese denizens, especially as their methods of communication and education convert to virtual spaces over more traditional formats. The implications of this constant surveillance — be it human or automated — are widespread. Political dissidents can be identified and tracked, with real-world consequences. Griffiths describes several groups and individuals that have been forced to move abroad due to their pro-democracy or anti-CCP views. Vocal dissidents who are unable to leave the country are often arrested. Towards the end of The Great Firewall, Griffiths describes a social credit system, similar to that of <a target="_blank" href="https://www.theatlantic.com/entertainment/archive/2016/10/black-mirror-nosedive-review-season-three-netflix/504668/">Black Mirror’s Nosedive</a>, that is enabled by the omnipresent surveillance apparatus. Supported by Tencent’s WeChat, <a target="_blank" href="http://www.xinhuanet.com/english/2019-06/14/c_138143745.htm">the social credit system</a> “derives from a plan announced by the State Council in 2014 to establish a nationwide tracking and credit system, combining financial and other data with people’s fingerprints and biometrics,” writes Griffiths. “For those with good credit, the benefits can be tangible: they can rent rooms without a deposit, get upgraded on flights, or receive free gifts when they apply for loans. For those at the opposite end of the scale, things are far more difficult: prices go up, they are often denied services, and they can even be prevented from traveling.” (281, One app to rule them all). Griffiths continues to portray how the credit system penalizes citizens for affiliating with those with low credit, forcing individuals to improve their credit for the good of family and friends and incentivizing them to disengage from those friends and family members with low social credit. “Actions that can cause deductions include missing a restaurant reservation, cheating in an online game, and jaywalking; while good deeds such as donating blood or recycling can boost a user’s score,” Griffiths continues. (282, One app to rule them all) This dystopian system unabashedly attempts to control Chinese citizens’ behavior, and it probably ranks as my most grotesque discovery from The Great Firewall. Though the technology to implement such a system is rejected in societies with more liberal values and exceeds the technological abilities of the majority of nations that would employ it, times are changing. Griffiths introduces, in the final third of his book, the global debate surrounding internet censorship and cyber-sovereignty. He positions societies on two sides of issue. More censorious states, such as China, Russia, and Uganda, support the notion of cyber-sovereignty, which is isolationist in nature and posits that every state should have control over the information and communication that take place within its established borders. America and its allies, often European, support the opposite: a globalist vision, with interconnectivity and a free flow of information between nations, regardless of geographic boundaries. Proponents of the Chinese vision argue that America, in particular, poses a danger to the rest of the world, as its technologies, such as Facebook and Twitter, have been used to destabilize nations across the world, citing Iranian protests in 2009 that, according to then-Secretary of State Hillary Clinton, were energized through American social media companies. To boot, <a target="_blank" href="https://www.nytimes.com/2009/06/17/world/middleeast/17media.html">the U.S. State Department even asked Jack Dorsey, CEO of Twitter, to postpone regularly scheduled maintenance during the protests, as Iranian revolutionaries were using the platform to communicate.</a> Proponents of cyber-sovereignty suggest, apparently somewhat reasonably, that American technological dominance threatens international world order, as users around the globe have become increasingly reliant on American firms for information and communication. And China offers the technology to subvert that American interference with sovereign affairs. China has engaged governments around the world, notably Russia and those in Africa and South America, to offer Chinese censorship and surveillance technologies to governments that wish to impose such restrictions on their national internet. As a result, authoritarian-leaning states have begun to track their own dissidents and detain those who mock or defy their regimes, such as Stella Nyanzi, an activist who likened her Ugandan president to a pair of buttocks on Facebook. In response to her post, <a target="_blank" href="https://en.wikipedia.org/wiki/Stella_Nyanzi#Arrest">Nyanzi was jailed</a> in a maximum-security prison for thirty-three days. China’s influence has also extended from governments to businesses and private citizens, through its economic might. Griffiths cites the Marriott Hotel chain, an employee of which unwittingly committed a gaff that sent shockwaves through the company in January 2018. The employee, who operated Marriott’s Twitter account, <a target="_blank" href="https://www.scmp.com/news/china/society/article/2128124/marriott-sacks-employee-who-liked-twitter-post-tibet-independence">accidentally “liked” a tweet from Friends of Tibet, a pro-independence lobbyist group</a>, who had congratulated Marriott’s inclusions of Tibet, Taiwan, and Hong Kong in a drop-drown menu of an email that asked customers to provide their country of address. Although Tibetans might claim independence from China, the Chinese state certainly considers the region of Tibet as its own, as it does with Taiwan and Hong Kong. “Craig Smith, president of the hotel chain’s Asia Pacific office, gave a groveling apology to the state-run China Daily,” (309, Epilogue) writes Griffiths, in response to the employee’s mistake. Marriott Hotels’ implicit endorsement of Tibetan independence, via Tibet’s inclusion in the hotel chain’s drop-down menu, invited Chinese nationalists to hunt for similar inadvertent endorsements from other companies around the world. Griffiths describes how Delta Airlines, apparel retailer Zara, and Mercedes-Benz, among others, were discovered to have made similar faux pas on their social media pages or platforms, and the companies were forced to make an unexpected decision: to include China’s contentiously autonomous regions in their media and risk losing Chinese business or to scrub the regions from their platforms. Even I, an individual, have grappled with my decision to publish this review, for fear of potential future backlash, should I ever be in a position where my stance on Taiwanese autonomy or Chinese censorship is scrutinized. Upon my completion of The Great Firewall, I was left with a wariness of modern technology and a greater understanding of how these new technologies, which increasingly dominate our lives, offer governments the ability to control our exposure to information and to therefore manipulate our behavior. I also have developed an appreciation for the free flow of information I enjoy as an American (to the extent private companies don’t self-censor), even if that freedom is accompanied by a responsibility to critically evaluate the information I encounter online. So accept this review with a grain of salt, I suppose. Griffiths, who has spent considerable time on the ground in China, does take care to address each position charitably, and he discusses the technological nuances and geopolitical implications of “the great firewall” with expertise and enthusiasm. I recommend his book to anyone whose interests include technology, geopolitics, and China.

The Residual

Leather: Building the Frontend

80 Days of Management

Patience by Default

The 2021-22 Europa Conference League

Developing a Practical Algorithm

The Great Firewall of China: Key Takeaways