To view the comparative translation project, click the link here.

I start this post by referring to “Textual Structures”, my favorite chapter of a recent book I read titled Design for Information by Isabel Meirelles. While the majority of the 2013 book focused on various forms of quantitative data, this chapter was uniquely focused on information presented in textual format and how such data could be represented.

As the word cloud shows, I love textual information. More colloquially, I love reading, writing, being wordy, and thinking loosely about etymology. Naturally, this chapter piqued my interest.

How would you represent textual information if not for presenting the raw text itself?

The answer to this question is not clear, at least it wasn’t back in 2013. Meirelles writes of the scarcity within the methods for textual data visualization, tracing its short history back to 1999 where the first book to contain a chapter on document visualization “Using Vision to Think” by Card et al., was published.

Work on textual data analysis and visualization has the goal of finding patterns and relationships within its corpus text. Once such patterns are found, it is a matter of visualizing them in an appropriate manner.

There are several types of textual data visualizations that Meirelles shares, categorized by Marti Hearst, a professor at the School of Information at the University of California Berkeley. They are written below:

1. Visualizations of the connections among entities within or across documents

2. Visualizations of word concordances and frequency

3. Visualizations of the relationships of words

Reading this chapter inspired me to explore how textual data could be processed, analyzed, and eventually visualized. The rest of this post will cover just that: the motivation behind my recent textual visualization project, process, and learnings along the way.

Let’s begin by thinking over project motivation. Back in university—with “back” referring to a ripe year and a bit ago—I had worked with a professor to build some materials considering the role of translation in literary interpretation. From this research, I came to the conclusion that although we often trust the fidelity and 1-1 mapping of semantics with both human and machine translations such as Google Translate, each translation fundamentally becomes a descendant, but not an exact copy of the original. A translation is borne from the original work, but is fundamentally its own entity and different in structure, meaning, and delivery. With this thought still in mind, I determined the theme of my project: visualizing comparative translation.

The next set of questions came up naturally:

• What language-to-english comparison?

• What source text to analyze?

The answers to these questions would be determined with constraints in mind.

With a limited set of languages in my tool-belt, I soon decided on Japanese-to-English translations. This was my original mother-tongue and a language I knew I could get translation help from a subject expert (my mom). With no desire to run into legal issues on my personal project, I determined that the corpus of work needed to be old; it needed to be in the public domain. Not only would the original work need to be old, the translations would need to be as well, since they are covered by their own copyright.

The Ogura Hyakunin Isshu (OHI), a waka poetry anthology from 13th century Japan deemed old enough. The OHI translates to Ogura’s one hundred people, one hundred poems and contains, as the name reads, 100 poems from 100 poets. The most well-known version was collected by anthologist Fujiwara no Teika for his home near Ogura Mountain, in Kyoto. Thus the name Ogura.

Being a classical work of literature, it has been translated over a dozen times. Several translations were well past their copyright as well, and were safe to use. I decided upon four. The translators and their respective year of publishing are included as follows: Frederick Victor Dickins (1866), Yone Noguchi (1907), William Ninnis Porter (1909), and Clay MacCauley (1899/1917).

With the corpus text determined, I then embarked on understanding it.

When comparing and analyzing any form of poetry, its essential to know a bit more about it than its pure definition. At the start of this project, I was a waka novice. I’m now, passably proficient with the help of online resources. For the many who are similarly unfamiliar with it, waka poetry is a classical form of Japanese verse totals to 31 syllables and is arranged into a 5-7-5-7-7 syllable structure for each verse. These poems focus on themes such as love, and the four seasons. I include one particularly sassy example, Noguchi’s English translation of OHI’s poem 38 by Lady Ukon.

Despite some conceptions of poetry being loose and undefined, waka poetry is well defined in both structure and use of literary device!

Structurally, it is divided into an upper and lower section. The first 3 lines (known in japanese as ku) form the upper part called the kami-no-ku (5-7-5) and typically sets the scene through physical descriptions of nature. The last 2 ku form the lower part called the shimo-no-ku (7-7) and often shifts to the author’s internal reflection. Within these sections, often overlapping, is a pivot that connects observation with revelation and observation. Translations may invert this narrative structure, or add extra details to connect the two sections.

Waka poetry also employs various literary devices. These are not found in all poems, but are common and relatively standard. Most notable among them is a pivot word, called kakekotoba which is a form of word where a single phonetic word contains two meanings and often help to bridge the kami-no-ku and the shimo-no-ku. There is also makurakotoba, which translates literally to pillow word. Makurakotoba are 5-syllable epithets that are placed before specific words (eg. god, mountain) to add rhythm and evoke visual imagery. Kigo, or season words are also incredibly common. They are words associated with a specific season (eg. cherry blossoms for spring) that show the reader the time of the year without necessarily stating the season directly. There are several other literary techniques used in waka poetry, but these are the three devices that I have focused on drawing out in my analysis.

An example of a poem annotated for both structure and literary devices are included below:

Learning about the structure and literary devices present in waka poetry, a method for analysis began to develop.

Following the upper/lower structure of waka poetry, I was curious to analyze the preservation of semantics in each section across both the original, and translations. This form of abstraction would allow a reader to quickly view preservation of structure across translators. For instance, it could help an individual see than one author tended to invert the original structure, while one maintained it. It could also help to identify insertions (lines with meanings found nowhere in the original) or deletions.

Additionally, the literary devices utilized could also be analyzed in a similar location-based manner.

With an intention in mind, I started out with a pen-on-paper approach to the analysis. I chose several poems and analyzed all four translations against the original, mapping out preservation and migration of meaning.

As this anthology contains 100 poems, my eventual goal was to make this manually intensive task into one that was computationally driven.

After one such graphing brainstorm, I was reminded of another colorful graph I had seen recently on Dimitar’s screen. It looked a little something like this:

Inquiring on what I had originally called chromosome graph we were eventually able to narrow down the graph to have been a synteny graph.

If the concept of synteny is new to you, it was for me too. The premise behind it, however, is relatively straight forward and draws surprising parallels to comparative translation analysis.

Syntenic analysis is used in genomics to study the physical arrangement of DNA sequences and gene positions across species. It is a powerful tool to study the relationship between species that once shared a common ancestor. It is used to identify complex structural changes to the genome, such as rearrangements, insertions, and deletions.

Synteny is further broken down into levels: micro and macro. Macrosynteny looks at whether large blocks of genes remain on the same chromosome across species. Microsynteny is the conservation of local gene content.

I wondered if this concept could be used for my translation problem. Within comparative translations, we can liken the original work as the “ancestor gene”, and the translations as descendants that draw information from the ancestor, but rearrange and modify to reflect their language, personal biases, and cultural context.

Additionally, the levels-based approach of this scientific analogy worked particularly well for wake poetry which contains a clear structure and defined use of literary devices. Macrosynteny can be viewed as the conservation of the overall structure (kami-no-ku and shimo-no-ku). Microsynteny looks into the literary devices to understand the preservation of local content such as the kigo, and kakekotoba. Through this, we can begin to compare and contrast not only the original text to the translation, but translations against each other.

With a plan for a synteny-inspired visualization of comparative translation, the bones of the project were coming together. The rest of the project was spent figuring out details like, how to turn a manual process into a computational one and how to design the user interface and specific visuals. Sparing the full details of failed experiments and trials and errors, I’ll quickly sum up where we went from here.

The UI and visualizations were developed in Figma prior to any analysis. With an idea for the exact analyses that would take place, I mocked up what I intended the pages to be, and how users could interact with it. Despite changes that would eventually occur over the design process, the overall layout persisted through iterations of improvements. These mockups also informed the actual engineering for the site, where I used Claude Code.

The computational handling of poems was tricky. Starting out, I wanted to make an analysis that was as robust and reproducible as possible (fearing the dreaded “slop” AI is notorious for) while managing to accurately draw out semantics from the text. This manifested into iterations of using high dimensional vector embeddings through the Global Vectors for Word Representation (GloVE) machine learning model. These worked terribly with something as complicated and archaic as both the English and Japanese I was working with. At the end of a week long exploration of deterministic(ish) models, I resolved that it was time to bring out the magic black box: LLMs.

I developed a thorough prompt to classify and map sections of the poems. This prompt would classify the upper and lower levels, as well as the literary devices in each poem. The results were immediately better; not perfect of course, but better.

In order to maximize accuracy and reliability within LLM classification, I added a second, human evaluation step. As mentioned earlier, my mom—who previously worked formally as a translator between Japanese and English—was brought in to this project for extra validation.

With the great annotation on its way, we spent a week sitting down during evenings to annotate and correct classifications made by the LLM through a review site I made with Claude Code.

After completing annotations for all poems, as well as tweaking the site design, the final (for now) visualization is available to view here. I’ve included a short video walk through as well.

Before ending this post I want to mention a few caveats.

1. This project wasn’t a user research driven project. It was driven by a personal motivation to continue to learn information design, play with textual data, and better understand what the capabilities of data visualization are within a field such as comparative translation. It is not meant to big and grand, but rather, curious and hopefully, informative.

2. As mentioned earlier, this project used AI for site development and classification tasks! I know AI use is very contested across fields, including the information design field. Understandably so; AI-ed information design tends to suffer in both underlying though and structural data rigor. However, it also helps an individual to build and prototype creatively and quickly. Whether you agree with my utilization of AI or not, I worked to make it suit my learning needs as I focused on developing the design and process, rather than line-by-line code. I explain my usage and reasoning more in the about page of my site. Feel free to take a look!

3. Annotations are human, and therefore up to interpretation. With my annotation officer (mom) and myself, we looked at and approved and re-classified each poem in the anthology. During this process, we made decisions such as “Is this line represented anywhere within the original text or was it made up?” and “Is the english wording of ‘fisherwomen’ close enough to the original that referred to ‘Ama’, the women divers?”. We determined the answers to these questions to the best of our ability through cross referencing academic analyses, but at the end of the day, it was simply our best judgement. Keep this in mind when viewing the poems!

Finally, after all of this, I looked up and a month had passed, 100x5 poems had been analyzed, and through it all I had splashed around in the great lake of textual visualization.

Through this splashing, floundering, and diving, I continue to learn that this data lake is deep. A simple question becomes more complicated once you get closer to it. Execution always takes more than anticipated. But the process is fun, and what a joy it is to have fun while learning.

For more about the details about the project without the long winded process details, feel free to check out the about page of the project.

To view the flight delay dashboard, click here.

A common retort these days accompanying a statement or argument:

“Okay, but show me the data”

Or simply,

“Where’s the data?”

While the search for facts is a fair one, the statement is imprecise in its reference to data. When we ask for data, we want information.

Though colloquially, data and information are often used interchangeably, these words refer to different things. What can be understood when presented with data is different to when presented information.

Data refers to the unprocessed facts, or raw observations. Only after spending the time to organize, process, and analyze such data does it become useful information. Information can then be used to answer a question and assist in decision-making.

Say your friend tells you (an avid coffee drinker) some hopeful news,

Friend: “Turns out drinking 3 cups of caffeinated coffee a day lowers dementia risk.”

You: “Show me the data.”

Friend: Hands over a 100000x100 spreadsheet from a study tracking participants’ health metrics well as their daily caffeine consumption over ~10 years.

You: Either you’re a data wizard and after some thorough data processing and analysis you find that indeed, coffee is a miracle drink. Or more likely, the data means nothing to you and you’re stumped.

(example not factual, but inspired by a recent Harvard study looking at caffeine & dementia).

For most people, the mere acquisition of data is not enough to make an informed decision. To do so, we would need information.

Knowing that there is a difference between data and information, we should also recognize a growing gap between the two. As data grows bigger in absolute quantity and influence over decision making—through the advancement of data collection/storage technologies and the rise of AI decision-making which is fundamentally trained on big data, respectively—turning data into cohesive and useful information gets more complicated.

I approach these gaps as a recent data engineer who has seen that the collection, storage, processing, and cleaning of data into information is not cheap. It is both time and resource intensive. This makes information more expensive, even if the data was provided for free. While data can be free for public use, the information extracted from it can be private and paywalled.

We find ourselves at an interesting moment where we may have ample access to data, but not as much to information. Given that information is both valuable for decision making, yet expensive to produce, we can begin to consider two things. First, who values the information enough to pay for it? Second, who can afford it? Reversing this question, we can also think about it as the following: Who could take value from the information, but cannot afford it?

While the first two questions have a clear and semi-informed answer in my mind—and probably in yours—the third is more opaque (to me at least). It’s hard to focus on the populations that are underserved because they might be individuals and certain groups, not corporations. Individuals are more difficult to imagine clearly, because they don’t exist in the .

With no clear solution in mind, I bring up this point on information imbalance to consider what it may look like if a greater emphasis could be given on the third question. What if as a society, we emphasized building a wealth of information built on data to help people, rather than monetizing off of the data they provide?

To make this idea a bit clearer in my mind, I recently embarked on making my own information tool on public data: “Know Your Flights”. This is a data visualization tool for understanding US domestic flight delays through aggregating ~69 million flights over the past ~8 years.

As a semi-frequent flyer, I was excited to find that every domestic flight within the United States is tracked with delay information and freely provided by the Department of Transportation (with a several month delay in data availability). My motivating principle behind creating this tool was to enable better decision making upon planning air travel. Delays in flights are incredibly common and range from a several minute to multi-hour delay. In building a tool to aggregate averages in flight delays across routes and carriers, I hoped to see if trends existed within flight data, and whether they could be visualized in an easily comprehensible manner.

For instance, if I know historically that Tuesday afternoon travel between SFO to EWR has a much higher rate of delays than morning travel, I could make a “safer” flight decision. Or if I could see that airline A is on average 20 minutes more delayed that airline B on this route, well, I’d probably opt for the better performing one.

See a short walkthrough below:

This delay data is not something that carriers provide. However, I believe it could be informative for an individual planning domestic aviation travel in the US. At the very least, it can be an interesting exploration and provide one example of a data tool that works to serve people, human people. Human people who hope to reach a destination or connection on time.

I won’t get into the details of designing this dashboard in this post, but if you’re curious, you can see more on the about page of the dashboard, along with my project’s page of my portfolio.

I end here by repeating: there is so much data. While not all of it is free, there is a lot that is.

Where data exists, information can follow.

Where information is, truth, informed decisions, and possibly less future flight traumas can reside.

On these days, I reflect on what we call “last” year—finding a narrative within the experiences, stresses, and adventures that made up the past 365 days—and attempt to make good guesswork for the year ahead.

It is on these days that I often feel one of two things. I may feel a sense of surprise with how similar yesterday, marking yesteryear, is with today, a supposed new chapter. Alternatively, I sometimes experience awe with just how much change can occur within the short time span.

I turned twenty-three last week, and the transition between twenty-two and twenty-three feels more like the latter. This might have been to be expected given that at the start of twenty-two I had just graduated from undergrad, sparking a natural time of accelerated change. Despite this, I doubt my year-younger self would have fathomed the actualized rate of change.

Thus, in an effort to understand what these changes were, I decided to sketch out a few very informational diagrams about my year. This served as both a reflective exercise, and a first pass at making my information design piece inspired by what informational designer and Pentagram partner Giorgia Lupi calls “data humanism”. Data humanism is her design philosophy that focuses on how data can represent human experience past informal and well-packaged “big data” visualizations that we so often see in the media. For myself, as someone with a data science education, the idea of data humanism—and informational design in general—interested me as a natural intersection between data and the arts.

The concept of data humanism can best be described with an example from the coining individual. Take a look at a data visualization by Lupi, tracking her long covid symptoms with painted color markers. This visualization was shown in a OpED piece for the New York Times, drawing awareness to the gravity of Long Covid, a chronic and debilitating illness that some individuals would have after testing positive for Covid.

What does this visualization do that a more “standardized” plot could not? It provides human annotations, unique symbology, and tells the story of one individual, from the perspective of that very person. In doing so, the data tells a human story, rather than simply pushing an objective.

Inspired by this example and others, I began with a broad goal of capturing some of the defining themes from my year, bounded to what had occurred in exactly the last 365 days. I brainstormed ideas in a sketchbook, thinking about what this past year has meant to me:

• Days I lived

• Places I moved

• Jobs I worked

• Coffees dates with friends

• Photos taken

While there were many more representations of my year through different experiences, many were stored in my fuzzy memory bank, rather than existing in any hard drive or on paper. Thus, I stuck to mostly simple measures: days, places, jobs.

The process of sketching out a few diagrams on paper produced a clearer intent in my mind for my visualization. In making the first visualization, somewhere within drawing the first 10 dots—somewhat randomly and scattered—to completing a circle-like formation of all 365 dots, I began to reflect further. In the process of drawing tiny dots repetitively, I thought about the months from June 2025 to June 2026. I considered how September, 2025 was my first month after moving to New York. A very frenzied, chaotic, fun, and anxious time, the days felt long with activity. I scattered dots far away from each other. Thinking about the 2 weeks of Christmas, the dots became clumped together, just as the days morphed into one another almost seamlessly. Days spent considering my career path and purpose were towards the bottom of the page.

A personal narrative made out of dots. Dots that represented how our individual days interact with each other, without ever touching. Zooming out of a day, or even month, we can begin to see the shape of our circumstances, our habits, and moods. Furthermore, in retrospective, such shapes become even clearer as certain trends taken precedence in memory.

To explore this idea further, I worked within Illustrator to make a poster of dotty-days, shaping my past few years. Think about it as a motivational poster, or perhaps a slightly foreboding message depending on how you see the glass filled:

For someone without the context of the process I went through, perhaps the dots on the poster make very little sense. I added years and boxes vaguely shaped as calendars (that is, rectangle) and Chinese red envelopes (given at New Years) to make the association stronger. However, for the sake of simplicity, I did not add any detail to the exact nature of the trends within the dots, nor annotate them. 2026 is still in process, so it will not be filled out until later! Furthermore on simplicity, I kept this poster to the primary colors, red, yellow, and blue, and white. This gives the poster a more vibrant and playful tone without being overwhelming.

If I were to continue to iterate on this poster, I would play around with the abstractness of the shapes created by the dots. Perhaps animal representations (eg. zodiac animals), or clearer trend lines may be interesting?

At any rate, with no smooth transition I’ll wrap this up with two short thoughts.

1. Data humanism!

2. We must be losing a day every year, they just keep going by quicker and quicker.

On August 15th, 2025 I landed in the big and boisterous New York City and made my way to Flatbush, Brooklyn where I’d stay for two weeks through an alumni sublease.

On August 30th, I moved up to Prospect Heights to another sublease, this time with Fien! There we lived for a month and a half as she commuted to Manhattan daily, and I worked remotely. To any that don’t know much about Brooklyn, and I didn’t either, Prospect Heights is becoming more expensive by the day. With a proposed ~40% rent increase by landlords, it was soon settled that we’d be moving.

On October 12, powered by Bagel Pub, we UHauled the free furniture we had collected from the streets of Brooklyn to the Upper West Side (with the help of Dimitar’s driving, thank you!). We had—with another university alumni from our year—gotten a lease for a cute 3B 1BR at the intersection of W 81 ST and Amsterdam. There we intended to stay for the year, and perhaps a bit.

Fast forward to the present, and to we now have all moved out to varying degrees. This past Monday, I packed my life into a closet and with one carry on, left New York City for the next several months before moving again in the fall.

It is quite literally cheaper to fly across the Atlantic to Bulgaria to visit your boyfriend and his family before traveling to Japan to see family than it is to afford New York City rent and amenities. So, one year out of graduation, I am fulfilling the unemployment prophecy—going to live at home!

While going home is something I’m looking forward to, New York City—and more specifically, the Upper West Side—has deeply etched itself in my memory as a place I love and will miss, if not just to walk around in.

The New York City I experienced was much less the flashy lights and Times Square, and more so one marked by the local sights of the UWS. Upon leaving, I made a few postcards of my favorite spots, a way to commemorate the lovely place I was able to call home for a brief period.

I enjoy collecting postcards and it’s a habit I picked up during college. Attending a university that involved a lot of moving—once every semester to a new country—it was important that souvenirs be light. More so, inexpensive. Even further more, doubling as wall art.

Perhaps hyperlocal postcards are not a really a thing.

A postcard made for commercial tourism is oftentimes required to portray a well known narrative, one that is recognizable by many. The yellow cabs, the Empire State Building, the Brooklyn Bridge. Made for travelers with limited time to see everything and for folks at home curious to know the most “iconic” sight to see. Postcards can serve as proof that you were there. You saw the things that were made to be seen and did the things that were made for you to do.

Despite this, I feel more of an urge to collect mementos of places I have gotten to call home. A cardstock that remembers that I loved going to the Natural History Museum, weekend coffees at Sote, and passing the house on my street covered in foliage.

In some future, I hope sending and receiving hyperlocal cards becomes a thing. Send me cards detailing the path you take to walk to work, or the bar on the corner, or the lamp in your living room. Proof of life behind the postcard and within these spaces.

So to start this proposed future, here are postcards, some watercolor, others drawn with Procreate. All of places I’ve been wanting to share with people back home. If you came to visit, this is where I’d take you:

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Inspiration is one of those terms that confuses me.

Staring at a wall of purple polka dots may inspire one to pursue graffiti, another to purchase grapes, and a third, nothing at all. Inspiration can shape a future action, change a life, or be a passing emotion. It can be anything and everything and almost nothing.

The latin root verb inspirare means “to breathe or blow into”. Such air could be the breathed in to prepare for action, or just as easily breathed out in transit.

Despite being an amorphous “thing”, I think looking for inspiration is very important. It is fun. Recently, I’ve been spending a fair bit of time searching for inspiration. The productivity of it is yet to be confirmed. It might look like scoping out portfolio and interesting projects, attending a talk like Jon’s, or even just looking out for fun tile arrangements of the NYC subway during my commutes. This inspiration can then go on to catalyze some action to work on a specific project, and when conspicuous enough, serve as a model to trace for said projects.

To be inspired feels a bit like that word game “associations”.

This is the game where you find hidden themes between words and concepts. Inspiration can then be thought to be an association tied to an idea or action. I think back to the introduction of Murray Gell-Mann’s 1994 book “The Quark and the Jaguar: Adventures in the Simple and the Complex” where he writes of his jaguarundi sighting inspiring an awareness of the connection between the most complex beings and his research on elementary particles, motivating him to write the aforementioned book. He writes,

“Meeting the jaguarundi in Belize somehow strengthened my awareness of the progress my colleagues and I had made in understanding better the relation between the simple and the complex, between the universal and the individual, between the basic laws of nature and the particular, earthly subjects I had always loved.

The more I learned about the character of that relation, the more I wanted to communicate it to others. For the first time in my life, I felt the urge to write a book.”

(Gell-Mann, p. 18)

Perhaps inspiration can be the association of like and unlike things that provides a perspective and way of framing a problem. That’s what I saw in Jon’s talk as well.

In each of Jon’s projects he shared, there was a common discussion of the role of inspiration in shaping design direction. Such inspiration was described to come from various forms, as a physical form, a social concept, a foreign term, or a product function.

For example, Jon first described a project with the Mallorcan tile manufacturer Huguet on a customizable garden tile set, inspired by hedges of the English garden (Huguet X Pentagram). This could be considered to be inspiration by analogue.

(Image Source: Creative Boom, 2022)

In another project with Quandela, a french quantum computing company, Jon’s team at Pentagram developed their design for containing equipment. The team was drawn upon principals directly from quantum computing, reflecting them within the design itself. They drew inspiration specifically from the ideas of duality and gates within quantum computing. Duality was explored through non-equivalent corrugation on the right and left side panels (Pentagram, n.d.). Extending the concept of “gate”, Jon mentioned that the team utilized the character for gate within the Chinese alphabet and designed the rack to resemble this character.

門

This could be thought of as cases where inspiration in design followed the terminology of the field’s principles, associated with language.

(Pentagram, n.d.)

The final example I’ll share from the talk is the work Jon and his team did with Lightmatter, a silicon photonics and computing hardware company. Designing the server boxes for Lightmatter, the team was inspired by the geometry of light guides that create optical interference. I’ve included a diagram of such geometries below, with a major disclaimer that it’s included for purely visual purposes. If you hope to understand what’s going on in this diagram, you can check out the linked source.

(Forsythe, 2019)

The final server box panel mimicked this pattern to be easily recognizable. For a passing Quantum Engineer, the processes of such hardware are immediately signaled. We can think of this as inspiration via function.

(Pentagram, n.d.)

Good design, and perhaps good process more generally, can be found alongside associative inspiration and clear storytelling.

I write this to explore, for myself at least, what happens when I stop thinking of inspiration as sparkling air, and rather, as an intentional practice of association with my surroundings and my thoughts. If inspiration can be found in such a way, it is not as daunting and requires only that we experience, observe, and learn about many things.

Despite this clarity of definition, I think that last task can be increasingly difficult. Attention economy, brain rot, etcetera. With regards to these buzzwords is a consideration of what we’re left with when a large portion of content we encounter is meant to occupy us intensely. I can’t count the number of times I laughed so intensely over a reel only to forget about it after finally closing Instagram. Maybe Instagram and other social media could be truly inspiring, if not designed to be so addictive.

On that note, Dimitar and I discussed our convergence toward what can be called a “quiet walk”. In the past, it may have simply been called a “walk”. The principle of this is to walk with no content streaming into your ears. To just walk and observe, to think or not! Just to walk and to be. To associate the legs to the ground and the eyes to the blue jay in the tree, inspiration is found in real life.

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Searching up how to write a resignation letter, I learned that there aren’t any emotions in corporate America.

Within my personal country, I feel joy.

Quitting a stable-salaried job after not even a year of work would not be my traditional definition of joy. A year ago, it would likely have been the opposite.

At the time I was in my last semester of college and becoming increasingly anxious that my career trajectory was much less of a solid trajectory with tangible goals, and more of a game of blind darts, guided by intuition. This likely arose from my resolute pride in being a generalist that had led me through high school and now, university.

Upon entering university and determining a major, my work experience, knowledge, and goals were limited. With limited information and a sense of pragmatism about the job market, I had decided to pursue a computer science degree. I liked doing most things, and could stomach learning data structures and algorithms. AI was mostly a sci-fi narrative and ChatGPT was still a year and a half from its original, clunky launch. Fast forward to 2025, graduating, and in San Francisco; AI models and the ensuing workplace restructuring was all that anyone could talk about. I was faced with the stark realization that not only may there not be an entry level position I could land, but furthermore, that type of work itself was rapidly changing alongside LLMs.

This disturbed me. If my job would require me to outsource my thinking to a machine, what would be the point of working? I wanted to go back to basics.

At this same time, I got fixated with the thought of furniture. Comparing an imagined tech job with something like cabinet making, I wondered if I had made a terrible choice in how I spent my past four years. Had I been lying to myself about my skills and interests if such a job interested me much more than writing lines of code? Of course, code, I had some experience in. My fabrication experience was limited to a 4th grade Fab Lab class I had taken, where I had made a clock (see figure 1). All to say, I was fully embedded in the day dreaming about a different life I could have chosen. The world was upside down and purpose was a very far away concept. Through fabrication fever, I remembered something that had given me purpose throughout high school: climate advocacy.

Figure 1 (my one and only figure here). A clock I made way back when.

In high school, I had founded a climate club in Muncie, Indiana. In college, I became interested in climate resiliency through modeling and simulations. Without overthinking it, I decided to try to enter a growing field called “climate technology”. Graduating college, I found an internship at a startup working utilizing AI to speed up renewable energy due diligence. In October, I transitioned to a full time employee as a data analyst. In December, my company was acquired by a larger DaaS company working on renewable data. Along with the product, I moved into this new company and was given the role of “junior data engineer”.

Five months passed in this position, and eventually the push and pull factors had compounded to be large enough to leave.

Most notable, however, was a sense of clarity I had not experienced in the past. Yes, I may be a generalist, but there were fundamentally certain types of work I enjoyed more or less than others. I was not agnostic as I once believed myself to be and I did in fact have natural proclivities and aversions. I realized that the friction I felt in my day to day tasks arose from the feeling that these two were swapped. I had been spending the majority of my working hours doing what I was averse to.

Why hadn’t I realized this earlier? I probably had, but needed more proof. Additionally what one would call a creative career had not felt feasible despite my joy when working artistically and creatively. It wasn’t the safe option. But again, perhaps there never was a safe option. Perhaps there was, and now it is rapidly disappearing. What happens when we begin to operate outside of the notion of safety, and towards the things that make us feel alive and inspired?

With this in mind, I offer myself a clean break.

And yes, in this job market! And yes, despite hearing horror stories of neverending unemployment.

In this job market, where it may feel that the meaning in your work is diminishing with every new model “drop”, I don’t think there is a better time to reflect on what one truly enjoys, and take a step towards a future you actively decide to build. Bye bye to the preordained! Hello to what comes after.

So with that, hello and welcome to my blog!