Readers share their thoughts on talking — or not talking — about big goals.
I wasn’t able to read a lot this month. Most of the things I read were for school. For some reason, I was just really tired most of the time, and even during my morning commute to work, I just didn’t feel like reading. I think it mostly has to do with my reading slump after finishing Thick As Thieves by Megan Whalen Turner. I’m hoping to hop out of this slump this month.
In any case, here’s what I read for school. These books are for my technical entrepreneurship class.
The Lean Startup by Eric Ries
My professor claims that The Lean Startup was a real game-changer several years ago. I can tell it was, because a lot of the principles mentioned in this book are things that are being actively practised in the industry, at least in the companies I’ve worked for. Things like A/B testing and MVPs that seem like very reasonable things were surprisingly not very ubiquitous some years ago.
The main thing I didn’t like about this book was how disorganized it was. I think there was an attempt to organize the book into sections, but it didn’t work, because a whole lot of the things mentioned in the first few chapters were incessantly repeated throughout the entire book. Not only were the concepts repeated across chapters, but the author has one of those high-school essayist syndrome where they try to repeat the thesis ten times in a paragraph. It just gets very redundant. Don’t get me wrong, the ideas are extremely helpful and important. I just did not like the way they were written.
Business Model Generation
The coolest thing about this book is its format. I ended up buying a physical copy, and I would recommend to anyone who wants to read this book to also buy a physical copy. Its strengths are really in how the message is conveyed. The design is spectacular, very sleek and almost magazine-like.
The most important parts of this book is the first quarter. After you finish reading the different sections of a business model and the different types of business models in existence, the content gets a little uninteresting after that. The chapters on storytelling and visualization were pretty much common-sense. And you can tell that they’re common-sense, because there were basically around three main ideas surrounding them that was repeated over and over again throughout the pages.
Well, here’s to hoping I’ll get more interesting things to read this month.
You know that saying, “How do you expect people to love you when you don’t love yourself?” Or I don’t know, something along those lines. I don’t remember it being quite so harsh, as I’m sure I’ve seen that saying on several get-well sites.
Well, that’s how I’m feeling about my own characters. I have talked about this before in this other post. Before that, I also mentioned being bored of my own story. I have taken a break from my story for several weeks, and I am now gearing up for next month’s Camp NaNoWriMo. I have dusted off my notes, and once again, refactored the plot. I spruced up the characters. I have read and reviewed three writing books.
Here’s the thing. I don’t think the problem is with the concept of my characters or the concept of my story. I think the problem is with me, the writer. Let me clarify what I mean about that. When I think of my story, I get very excited… but only if I am thinking about it from the point of view of a reader. The concept I have come up with is something I have wanted to read for a long, long time and the main reason I decided to write this story is because I am done waiting for the market to cater it to me. A lot of the plot points I constructed for my story are ones I would love to read about. Same with the characters; I created my characters to be, if not similar to the characters I love from other books, at least they possess qualities that I know I would like as a reader.
And this is the problem. I’m more interested in reading my story than I am in writing it.
The writing books don’t help at all in this regard. All of the writing books I’ve read try to instruct writers in how they can make their story enjoyable for their readers. However, none of them have any advice for how authors can enjoy writing their own stories. Is this just a problem I have?
Someone at work brought this up during lunch, and I read it after my break. I’m more on the ML/Big Data side of things, but as an aspiring writer, I can very, very much attest to the frustrations of NLPers. I’m glad someone finally called out the academic trend of “over-selling” especially when it pertains to deep learning, which is a buzzword these days that receives a lot of hype.
I think the problem definitely starts in academia and the sense of competitiveness there, but I also wish that tech journalism was better. I remember reading this paper on using neural networks to separate the content and style of a piece of artwork; some articles that responded to this were so excited that they even deemed human artists obsolete. Or perhaps it wasn’t excitement so much as fear of the impending AI apocalypse. *sigh* I just wish for a more honest, more grounded coverage of what’s going on in the computer science community instead of the super-hyped up things we currently get both from the media and educational institutions.
And you know what? I also wish for more coverage on failed experiments in general. It’s great to hear about what’s working, but how do we know about things that people have tried before and didn’t quite work out? Isn’t that as informative as the successes?
Wow, I realize that I’ve only ever had “Writing Woes” posts, where I talk about everything that goes wrong in my writing. I didn’t actually have a positive writing post until now, which is kind of sad now that I think about it.
Anyway, “win” is probably an overzealous word for what happened, but small wins are still wins in my book. Nothing dramatic happened, except that I managed to untangle the big hairy plot that I talked about in my previous Writing Woes post. Not only did I manage to do it, but I did it in 7 days. That’s… impressive by my standards, considering that I’ve been straining against this plot since the beginning of the year. Is it super-polished? Hah, no, I don’t think I’ll get to that stage until I’ve gone through 3 drafts at least. But the good news now is that I can move forward with my 1st draft without wanting to pull all my hair out.
I took a 3-week break from my story, and when re-outlining, I considered every plot point up for debate. And that worked out so well for me. When I considered that some of the determining plot points didn’t need to happen, or did not need to happen the way that I envisioned it would, it was much easier to tease out the tangles in the plot. I still lost a considerable number of characters, but I think it’s for the better. (Remember Nasi, the tarsier? I don’t know why I didn’t nuke him out of the story from the get-go. The poor animal had no speaking lines, had very little motivation, and didn’t contribute to the plot. But as attached as I had become to this useless character, I wound up giving him the pink slip as well.)
I believe there’s another Camp NaNoWriMo coming up in July, and I am going to try and finish the 1st draft then. I know it’s an ambitious goal, seeing it’s taken me 7 months to write the first half. But I think it’s also pretty telling that this children’s book is only halfway done at 70,000 words. I think I need to tell the story with much less words. Considering this is the first draft, I’ll resort to ‘telling’ rather than ‘showing’ if I need to move the plot along.
My hope is to be able to churn out a complete 2nd draft by the end of the year. It’s actually this goal that prompted me to re-outline my plot. My initial plan was to push through the first draft and figure out the changes to the plot as I go along, but it was causing me to lag behind my goals. I’ve read many writers advice that when you’re writing a draft, you shouldn’t go back and edit right away, but keep writing with your changes in mind. This wasn’t enough for me. I really had to revisit the entire story. It was disorienting for me to keep writing without addressing the issues from the parts I’d already written. It’s hard to build upon the story without knowing what events happened previously.
For this post, I’m refocusing for a moment on my full-time job. I know that this blog is mostly filled with my hobbies and personal projects, so it might seem like those are the only things I do. However, most of my life actually revolves around my career in tech.
I started my internship as a data scientist at the beginning of the month. It’s my 2nd full-time job as a computer scientist, and in some ways, I cannot help but compare it to my 1st full-time job. I worked as a front-end software engineer for over two years in a smaller company. Both companies are great, filled with talented people I get along with. More importantly, in both companies I am doing work that I am passionate about even though they are different.
And that’s what I want to focus on in this post: the difference between my experience as a front-end software engineer from a small start-up(-ish) company, and my impression so far as a data science in a much, much larger company.
I knew that the work would be different. And yet, I think I naively assumed that the job would be similar enough that I could measure my productivity in the same way. In my old job, I knew I was being productive when I managed to finish my assigned tickets. Depending on the tasks, I could finish about five moderate bugs in a day; for new features, I could at least get some new code out to code-review within a day or two at most.
In my new job, the process is entirely different. We’re working in Kanban style, rather than sprints. My tasks are a little more vague. Instead of having a specific goal I could measure, like changing the header background from white to grey, or adding a pop-out to a link, I’m assigned tasks like visualizing the clusters of similar items. As you can see, this task is less measurable. For one thing, the end goal isn’t to just have a nice visualization, right? Underneath that statement, I know that my goal is also to analyze the visualization, to obtain insights from the clustering. And this means that I have to find out a clustering algorithm that can actually give me a good visualization; it means that I have to find the data that can work with such an algorithm; it means that I have to find a visualization that can actually give me insights. And in the end, how do I know if the insights are meaningful or not?
For the past four weeks, I have struggled a little with this vagueness. Yes, I know I could ask, but I get the impression that it’s also part of the job of a data scientist to figure out these things. Whenever I’m assigned a task, it’s no longer up to a product manager to break down that task for me. It’s up to me to figure out what’s involved in that process.
I think this is the biggest difference between my previous job and the current one. As a junior software developer, my job was to implement whatever the product managers told me to. This is in contrast with a research position, where my job is to discover what must be implemented.
I worry that I’m not being as productive as I can be, and my worries are compounded with the fact that I don’t actually know how to measure my productivity as a data scientist. Which leads me to this passage from The Lean Startup by Eric Ries.
When I worked as a programmer, that meant eight straight hours of programming without interruption. That was a good day. In contrast, if I was interrupted with questions, process, or — heaven forbid — meetings, I felt bad. What did I really accomplish that day? Code and product features were tangible to me; I could see them, understand them, and show them off. Learning, by contrast, is frustratingly intangible.
Wow. This book is required reading for my Technical Entrepreneurship course that runs alongside the internship. I don’t have much of an entrepreneurial spirit in me, but when I read this, I thought, “Aha! This is why this book is required reading!” I never realized what it was that bothered me as I started my career in data science, until I found this passage in the book. I could have never put it in a better way.
Learning, by contrast, is frustratingly intangible.
I realized much of what I do in my new job as a research intern is learning. When you’re researching, what you’re doing is learning. You’re learning what works and what doesn’t. I was so used to measuring my productivity in terms of how much code I write or how many tasks I finished. Now I have to figure out a way to measure my productivity in terms of learning and the return value from what I learn.
Alright, in an effort to liven up this blog from my incessant writing woes posts, I’m going to take a moment to talk about some of the books I’ve read this month so far. I think if I read really quickly, I might be able to read one more book before the month is up.
Story Genius by Lisa Cron
I’ve been having a lot of difficulty writing the first draft of my story, mostly because I had a hard time really writing from any of my characters’ perspectives. This book was recommended to me in response to that.
I think the most valuable lesson I learned in this book is how every story that captivates readers sufficiently is ultimately a character-driven story. I’ve read many writing books before, and some of them distinguish between “plot-driven” and “character-driven” stories. In Story Genius, Lisa Cron explains why any kind of meaningful story is actually character-driven, no matter if the plot has tons of exciting things going on.
I know, it’s not a ground-breaking concept. Even in my own reading experience, I tend to gravitate towards books where I sympathized with characters the most. And I think her explanation brings home why this is so: an event in a story (in other words, the actual plot) has very little meaning unless the character gives us a context in which to make sense of that event. So really, even your most plot-driven story, if it’s good, is actually anchored by the protagonist.
Other than that, I feel like this book doesn’t offer anything else that is truly unique that sets it apart from other writing books. I think if you’ve read other writing books before, the bulk of the book after the first several chapters would feel achingly familiar. I’ve also seen other reviewers point out that they would have liked to see actual neuroscience explored in this book. I have to agree that the title and subtitle give off a more scientific vibe than what I got. Most of the time, the author would only say things like, “it’s brain science!” or “our brains are wired to look for this and that.” Now, while that was sufficient for me, because all I wanted was to learn writing techniques, I can understand why others might be frustrated about it.
The Queen’s Thief Books 4 & 5 by Megan Whalen Turner
It’s difficult for me to review these books, because there’s just so much to say. I feel like I’m not going to say anything that haven’t been said before, which is unfortunate, because this series is my absolute favourite, and I feel as if I should be able to say something more personal about it. But I can’t, not succinctly anyway.
In A Conspiracy of Kings, we follow Sophos, the heir to the throne of Sounis, as he is sold into slavery by rebels. This book is my 2nd most frequently reread book in the entire series (yes, even more so than The Queen of Attolia, which I know is the favourite of many many fans of the series). But there’s something about Sophos’s character that just calls to me. I mean, Eugenides is impressive and amazing and I love reading about his tricks and cleverness. But Sophos feels so much more human in comparison, and more relatable in that aspect. His earnestness and even his naivety made me root for him throughout his entire journey. And I feel that because he doesn’t begin as this awe-inspiring figure in the same way Eugenides had always been, Sophos’s character arc then becomes more pronounced. The climax of this book is one of the best things I’ve ever seen, and I almost keeled over seeing how Sophos manoeuvred the difficulties of his situation.
Thick As Thieves is the much awaited (and I mean 7-year-wait) fifth book of the Queen’s Thief series. Similar to the two previous books, we have a brand new protagonist in this book: Kamet. Many people would remember Kamet from his little stint in The Queen of Attolia as the slave and secretary of the antagonist, Nahuseresh. Thick as Thieves follow Kamet’s adventure as his life as a slave is turned upside-down when he finds himself fleeing for his life from the Mede Empire. This book echoes The Thief moreso than the other three books in narration style and the types of twists that had been pulled. Much of the book is about the adventure, and very little political intrigue, unlike QoA, KoA and ACoK. Since this is just my first time reading this book (and I’m sure that like the other books in the series, this one can only get better in rereads), I have to say I’m a little underwhelmed by Kamet as a protagonist. I think I say this, because I read TaT almost as soon as I finished ACoK. And like I said above, Sophos is so, so dear to my heart, and Kamet just had very big shoes to fill. I found myself reading more for the sake of Kamet’s companion (I believe it’s a spoiler if I reveal who it is), than I did for Kamet’s sake. That said, I believe that eventually I’d warm up to Kamet like I did to Costis in KoA.