Month: May 2026

Sci-fi game writing sample.

I did a writing sample for one of my applications:

So far out from Earth, I’m twirling in stardust. At the end of radio waves, where we last heard the warm human voices we knew, at the edge of the two hundred light-year bubble. This is an aimless mission to nowhere places. I think the mission journal should be read as a dark comedy, not reported interactions of an inquisitive human. Every planet a cruel joke where we get life and biomes that seem less and less like Earth. After the first fifty stifling atmospheres, eighty blobs of gelatinous prokaryotes that we laughingly classify as lifeforms, and one hundred poisonous soups called oceans, Earth seems more and more a fairy tale. Will we ever see it again? Farther and farther it seems to recede. The geniuses who sent us here without a reliable star map to get back home with fuel sources along the way set us up to practically go on fumes. Rarely, we encounter sunsets that are a wondrous pale yellow like Sol, dipping into mountains and oceans that look promising, but are only ephemeral dreams of lush green and teeming sea. The bright flecks of burning sand we pass every day through the vacuum incinerate those dreams of mine, which are nothing but vaporous excitement that there would be spiritual life.

– From Eval to…Pt. 2: Empowerment & Education, or Quality & Brand –

Aside from the more technical roles for us evaluators (some say “power users”) I mentioned last, I came upon two other options: AI Documentation & Literacy Specialist and AI Content Specialist.

For the first, I have previously built simple tutorials and led some lunch-and-learns on web skills at my positions and so was interested in that this position can fit “educator-writers.” I want to leverage my writing, explaining, and evaluation skills. I like to make tech, including AI, easy to access and useful, and material of this type produced includes “plain English” guides, interactive tutorials, safety checklists, FAQs, and ethical usage policies. I can create, update, and maintain these materials and help thousands of people. I take the complex, evolving topics and break them down for companies–or grandmothers. It’s about empowerment and education, while simplifying.

The second involves infusing company products with soul and empathy, while maintaining editorial standards. Your products will come across more human, not robot. Products can include: master AI style guides, prompts to generate perfect articles, scripts, and reports. It’s about quality and brand, while performing high-level editing and matching tone.

The first is mission, the second is craft. Educational strategy v. high-level editorial oversight.

In both of these capacities, I can apply my journalism background and my attention to clarity, tone, and usefulness in my AI analysis.

I did a little job projection research and it does seem like the AI Documentation & Literacy Specialist is a role for which demand will remain steadier over the long term. Meanwhile, AI Content Specialist has a current high availability of positions and may evolve into the orchestrator, an expert who manages multiple outputs to ensure quality (much spoken about right now).

I presented these as two more options for the AI analyst/evaluators who like me want to move forward into more responsibility and impact (and career potential). For me, I am leaning more to the education side. It seems like the more “future-proof” because companies are realizing that using the tech safely and effectively is a demand that will not go away. Internal training materials and public-facing literacy guides will always be needed.

I may continue this in a third part as I go, but to my fellow evaluators, do you have a trajectory you are interested in? Love to hear from you on what you are doing or planning!

– From Eval to…Pt. I: Experimentation –

I learned from a prospective employer that the work I and other employees have done is more that of “power users.” It wasn’t diminishing what I’ve done, just a more accurate description. Still made me want to level up.

So one direction is either getting the best out of my experience as a power user or going beyond prompting and response evaluation. Now I’m in the learning trenches, battling it out with my lack of knowledge. I’ve been going deeper into the world behind the tools we use every day.

I’m learning the difference between a few extended career paths, and the first set of options are: LLM evaluation engineers, machine learning research engineers, and applied AI scientists. How do they think, how do they test, how do they iterate, and how do they measure performance beyond just “good output”?

Understanding prompt intuition is only one layer. (It’s different from my JavaScript skills as well, though those help.) Evaluation design, controlled experimentation, model behavior analysis, and measurable improvement are what separate power users from builders. I’m putting on my lab coat.

I’ll keep you updated on how this goes.

Love and Deep Space

In China, there are 30-35 million more men than women and Chinese women have five lovers to choose from.

Love and Deep Space is the first 3D otome video game, originating from China, and has garnered its share of female western players. The player stars as a female protagonist with their choice of one of five androgynous male characters as romantic partners. While the game has a central quest and the typical gacha elements (in-game purchases of virtual items), players can collect photos of themselves with their AR boyfriends in real-world environments.

This past January over 790,000 users played, down to about 475,000 this month, the majority being women aged 18-34, mainly of Chinese demographic.
But what is driving young women to pursue companionship with virtual characters instead of IRL men?

AI characters offer emotional rather than physical interaction. The facts on the ground in China are exacerbating the difference between the genders.

The dynamics resulting from the male-female disparity in China are increased opportunities for educated urban women, rural males having consequently less choice, and the lingering effects of the COVID-19 shutdown, something much more severe than Westerners encountered, resulting in widespread loneliness.

In China, there is a saying that “hand machines” (phones) create ghosts — or suck out your soul. People are known to charge their phones three or more times a day. The addiction breeds more loneliness.

We might look to Japan as the place where tech trends originate (sometimes passing through South Korea to China).
In that country, the AI toy Kirobo is used to keep the elderly company. It has its uses, but at what cost? The machine is family now.

AI, phones, robots, all artificial, all taking the human away.

The CCP’s “Land of Infinite Hope” vision for 2035 (always a lot of plans), where the party aims for more AI automation in factory labor, households, and government services, has the potential to make unemployment and loneliness much worse. Artificial lovers seem a harbinger of what is to come.