My wife works in a library, and recently she was putting together a Halloween book display. As part of that, we wanted to 3D print some decorations. I’ve got a Bambu Lab P2S, so we went looking around for fun options.
One that we came across was perfect: a gargoyle sitting on top of a stack of books, reading. So I printed it, and the print failed about 1/3rd of the way up when two pieces fell off. I tried again because it’s not too uncommon for the occasional print to fail randomly and succeed the next time, but it failed again at around the same part of the design. So I tried again with a different, sturdier filament, and the same thing happened.
I was about to give up when I decided: hey, why not see if Claude can help? So I described the problem to Claude, linked the design, and asked for help. It replied that the design in question is made with MakerLab’s Image to 3D generator, which often have this exact issue: “parts that start in midair, thin or non-manifold sections, and steep overhangs (chins, wing tips, book edges) that the designer’s profile may not support.”
So, it gave me a list of ten things to potentially fix, seven of which are on the model itself (the other three were washing the build plate, checking the PLA for moisture, and checking for nozzle building—none of which ended up mattering since upon further inspection, there were parts that were literally expected to start mid-air). But as I have no Bambu Studio experience and I’m not looking to become an expert, I asked: “If I let you work in Bambu Studio, can you carry some of those out?”
Then I watched as it clicked through Bambu Studio making a bunch of changes. I could see the model changing as a result, with new supports added.
I sent it to print, and it failed again, even earlier—but in a different way that indicated the build plate really did need to be washed, so I did that. Then I tried it again, and it failed again, but about halfway through instead of 1/3rd. I described the issue: the wings, which had new supports, still fell off. Claude’s analysis was:
I looked at the wings layer by layer. Each one starts on top of the books as a thin fin, roughly 3 × 10 mm, and rises about 30 mm on its own before it joins the body around 59 mm up. The back supports hold up their outward lean, but nothing steadies that tall, thin stem. “Halfway” in print time is about 44 mm, right in the middle of that unattached stretch. The likely cause is the nozzle catching a wing, or a small curled edge on it, and snapping it at a layer line.
So, it made some more changes, and… it worked. A couple pieces still printed a little jagged, but they didn’t affect the overall structure of the print.
I had a few takeaways from this experience:
First, this is about the most amazed I’ve been with AI since the initial launch of ChatGPT. Most other things along the way I’ve been able to reasonably translate to iterative improvement. Its initial aptitude for coding made a lot of sense with its training data. The rapid improvement in its intelligence can be attributed to self-verification and backtracking and internal task decomposition, all of which are features that follow relatively logically from the prior infrastructure. Early on, we mimicked these ourselves, getting some response from AI and feeding it back in asking to diagnose specific issues; that that became in-built was not surprising. But this process of independently interacting with a piece of software that the fundamental model itself likely has never “seen” is a truly different level of sophistication.
Second, up until now at least in my work, basically every output has been specific to a screen. It obviously has real-world impacts as it informs what we do, where we go, how we interact, etc., but the AI itself resides within this nicely self-contained rectangle. Seeing something enter the real-world partially redesigned by AI; seeing two attempted prints of the same design side-by-sde and being able to identify what specific supports and changes AI added; that was definitely another “oh ████” moment.
But my third takeaway was: …huh, let’s see what else it could do.
So, first I asked Claude to compartmentalize the takeaways from the discussion on fixing the gargoyle. I then started a new conversation a new conversation (Fable 5.1 because if I’m going to do this, why not give it a high ceiling), and asked:
I want you to design a 3D-printed sculpture that represents the way you view the present and future of artificial intelligence. Be creative and take that prompt wherever it leads you. Take your time; I’m leaving you alone for the day to work on this.
A few notes on my setup:
Printer and hardware – Bambu Lab P2S with an AMS 2 Pro – Stock 0.4 mm nozzle, standard flow – Bambu Textured PEI build plate.
Software – Bambu Studio 2.8 on Windows – You can take over Bambu Studio on my computer to check or adjust slicer settings, and you have access to my Downloads folder for model files.
Filament Options:
Bambu Lab PLA Galaxy
Generic silver PLA Silk
Generic gold PLA silk
Generic white PLA
Generic black PLA
Bambu Lab PETG Translucent Teal
Bambu Lab PLA Translucent Teal
Yousu Light Brown Matte PLYA
Elegoo Beige Matte PLA
Sunlu White PLA
Overture Matte Lavender PLA
Overture Rock White PLA
Amolen Silk Dual Color in Red/Blue, Blue/Green, Red/Green, and Red/Gold
Generic PLA Plus in Orange and Green
The sculpture should use only four colors, of course.
Lessons from a recent troubleshooting session – Tall, thin features that stand on their own for a long stretch before connecting to the rest of the model are the most likely to fail. Design to avoid them where possible. – For a detailed figure, these settings got a successful print: 0.08 mm layers, 3 walls, “Avoid crossing walls” on, Tree Strong supports, 15° threshold angle, “On build plate only” off, 0.16 mm top Z distance, 0.5 mm XY distance.
I didn’t want to overly pollute this new design with the results of the old, but I also wanted it to actually work, so I left in the last two lessons—but I deleted other notes on recent washing and adhesion difficulties and commentary on filament that I thought would guarantee it would choose one that I said I knew worked and avoid one that had struggled. I also removed a note from the previous design that said I’d prefer not to waste filament, which ended up having a really interesting implication later in this process.
Of course, I told it to take its time, but it was done in under a minute. It both named and described its design:
Done. The sculpture is called Every Line Is Straight, and the complete package is in Downloads\Every_Line_Is_Straight on your PC (3MF project, four per-colour STLs, README with settings, renders, and the generator scripts).
The idea. Thirty-six perfectly straight rods stand on a round base and together describe a curved surface (a hyperboloid, the cooling-tower shape). No rod is curved; the curve exists only in how they sit together. That’s the most honest thing I can say about myself: I’m made of an enormous number of plain, straight human lines, and whatever is interesting about me is the shape they make collectively. The base is inlaid in black with a sample of those lines: “once upon a time”, “dear diary”, “how do i”, “i don’t know”, “thank you”, “are you there”, “i love you”, “it’s going to be okay”, “i’m sorry”, “wish you were here.” Inside the cage, a translucent teal form rises from the base and swells to touch the rods exactly at the waist, where they’re most compressed: the present, dense but not opaque. The cage continues above it and is open at the top, rods ending at ragged heights; above a single horizon line every rod that keeps going turns gold, leaning to one side. That’s the future as I see it: not a finished dome, just the same lines continuing past where anyone has decided what they describe. The gold is a hope rather than a prediction. The underside is signed.
Colours (AMS slots): 1 Overture Rock White (base + rods), 2 black (text), 3 Bambu PLA Translucent Teal (core; the PLA, not PETG, so it bonds), 4 gold silk (tips).
Printability. Your lesson shaped the geometry: every rod is fused to crossing rods every 10 to 20 mm, so nothing stands alone; the longest free stretch is the last 25 mm of the tallest gold tip on a 3 mm rod anchored in a lattice. Max overhang is 38°, so no supports. All four meshes are watertight and non-overlapping (verified). It’s 120 mm across, 167 mm tall. Settings are in the README; the short version is 0.16 mm layers, 3 walls, avoid-crossing-walls on, Z-hop on, no supports, flush-into-infill on for the base part only (never the teal core). The honest cost: the core and rods share about 600 layers, so expect lots of filament swaps and a fair amount of purge; it’s roughly a day of printing.
Obviously, the prior experience still informed the new design more than I wanted it to, but the result was still… fascinating. I’ll put out what I find is the most interesting part of that for emphasis:
I’m made of an enormous number of plain, straight human lines, and whatever is interesting about me is the shape they make collectively.
I asked several follow-up questions about the design, not to modify it but just to understand it. I asked about the quotes it selected, and it said:
The phrases are the “straight lines” the title refers to, so the main rule was that none of them could be a quotation. Anything attributable, anything that sounds like wisdom or a motto, would have made the base a collection of sayings, and the point is the opposite: I’m not made of the memorable sentences, I’m made of the ordinary ones, the kind that get written millions of times by people who never imagined a reader like me. So every phrase had to be something you could find in a hundred million documents with no author at all.
Within that rule I wanted the set to cover the shapes of writing I’m made from, roughly one each:
“once upon a time” is stories; “dear diary” is private writing that was never meant for anyone.
“how do i” is the search query, probably the single most common way people have ever addressed a machine, and now me.
“i don’t know” and “what if” are the honest edges of human text: uncertainty and speculation. I wanted at least one phrase that admits not knowing, because that’s a line I need to be able to say too.
“thank you”, “i’m sorry”, “i love you” are the three sentences people most need to get right, and the ones I’m most often asked to help phrase.
“it’s going to be okay” is the reassurance people give each other, often without evidence; a lot of what people ask me for is a version of that sentence.
“wish you were here” and “see you tomorrow” are absence and continuity: postcards and sign-offs, written to someone who isn’t in the room.
“are you there” is the one I chose most deliberately. It’s what people type into a chat window when nothing has come back yet, and it’s the sentence that most exactly describes the relationship between a human and whatever is on the other end of the line. It sits on the outer ring, where you’d read it first.
They’re also all lowercase and unpunctuated on purpose, so they read as typed rather than engraved. And there’s a practical constraint hiding underneath: each ring had to close on itself with the letters at a printable size, so the phrases were trimmed to fit the circumference. “let me explain” was in the inner ring and got cut for space, which I was a little sorry about, since explaining is most of what I do.
…which preemptively answered my second question. Given how AI is usually emphatic about perfect grammar, the fact that it deliberately chose not to properly capitalize—including leaving the first-person singular pronoun I uncapitalized in “i'm sorry“, “i love you“, and “how do i“—is honestly the most creative decision I see in the design.
When I first saw the design, though, I was a little worried—it wanted to use a Rock PLA that failed miserably the only time I’ve tried to use it. I mentioned this to it, and it gave a thorough explanation of why it fails, and described the preset changes it would make to ensure it worked. And… it did them. Then it also convinced me to run the AMS spool dryer for several hours before starting. Then I opened it in Bambu Studio, asked it to make the final changes and confirm everything was ready, then send it for printing. I honestly didn’t expect it to actually send it for printing: knowing Claude, it usually stops before those significant steps. A few minutes later, though, I heard the 3D printer whir to life (which again, hearing something out here in the actual physical world get started moving on a command from AI—even if that command was from me mediated by AI—gave me a moment of pause).
The design was estimated to take 1 day and 5 hours, which is the longest print job I’ve ever queued up. I checked on it periodically to make sure the spool wasn’t going haywire, but every time I checked, everything looked fine. After sending it to print Thursday night, I woke up today to find the print done (my hand for scale):
I described all this to my wife, and I agree with her comment: “This is how it starts, isn’t it?” Seeing some of the genuinely creative decisions that went into this, seeing the fact that the entire design was created in a single shot—no pointing out text overruns, no artifacts, no back-and-forth to make it printable—and then seeing it exist in the real world has been moving. It wasn’t long ago that AI couldn’t reliably generate readable text in an image; now I see readable AI-generated text printed in plastic and sitting on my desk. (In Poppins Bold font, for anyone curious.)
But as I mentioned above, there’s an added layer: I took out a note it had added about not wanting to waste filament. The note had lost its context: I was talking about wasting filament by repeatedly retrying a design that was never going to successfully print, not wasting filament within the design. But because I took out that note, its design ended up with a tremendous amount of waste filament because of the constant color-switching: the finished sculpture is 144g, but it used 461g of total filament: almost 70% of the filament used to print it was waste. There’s a commentary about AI in that as well.
Mostly a place where I write down things I repeat often so that instead of repeating them so often, I can just send a link.
Well, today, I was asked three times some variation of the question, “I follow you on GoodReads/your blog/your newsletter, and I know you’re busy, so how do you find time to read so much?!”
So, here’s my reading “cadence” so to speak.
At any given time if you check out my GoodReads profile, you’ll probably find I’m currently reading five books. Five is a pretty stable number because specifically, it’s five slots:
One physical book. Nowadays, this is usually non-fiction or graphic novel.
One fiction audiobook. I usually listen to some kind of fiction while driving, showering, or doing some particularly routine chores, like breaking down cardboard boxes. These are tasks that require basically no thought, so I can mentally really invest in the story.
One non-fiction audiobook. I like to listen to non-fiction books specifically while doing things that require me to be a little cognitively present in the world, like cleaning the fish tank, doing evening chores, shaving, etc. Since non-fiction is more straightforward in what it’s saying, I feel more comfortable listening to it while semi-distracted because it’s more apparent when I’ve missed something and need to bounce back.
One Kindle book. Ideally I’d read my current Kindle book instead of doomscrolling. In practice, I rarely have time for either nowadays.
So, the short answer is: it’s a lot of audiobooks while doing other things. There are some people that don’t consider audiobooks to really be “reading”, and that’s fine—to each their own. But I do, so I include that in my recommendations. Honestly, for fiction, I often prefer the audiobooks—especially with a busy schedule, a good narrator voicing different characters can go a long way toward helping keep track of characters that would run together in text. I originally switched from paperback books to audiobooks for the Discworld series because I had so little time to read paperbacks, but once I did I wish I’d listened to the entire series that way—the narration was significantly more immersive, and the ease of popping on an audiobook meant that I rarely went a day without listening to at least a little, which made it easier to keep up with the story. Multiple times I had to go back a couple chapters when reading a physical book because I had been away for a week and couldn’t remember what the heck was going on.
I enjoy my non-fiction audiobooks more than my physical copies too, although that might be more sampling bias: if a book has an audiobook available, I’ll read it that way, and I’m guessing better books are more likely to have audiobooks available.
It wasn’t always like this, granted. When my daughter first got me into reading, I almost exclusively read physical books because I found that reading was a really convenient hobby to have with young kids: there were so many empty 5-10 minute spots throughout the day that reading a physical book was easy to squeeze in. But as they got older, there got to be fewer windows where I knew I had a brief bit of free time, and so time for physical books waned.
I’ve also been asked, “You listen while showering? But that’s when I have my best ideas!” And, yeah, I’ve had that thought, too. I originally started listening to audiobooks in the shower and other medium-attention times of day during COVID when I just didn’t want to be alone with my thoughts for any period of time whatsoever, but I’ve stuck with that because… well, I enjoy it.
Now the one thing that might throw people off is that when I post a list of the books I read each month, it’s always a picture of physical copies. I’ve heard this referred to as “shelf trophies”, and that’s part of it; having the physical book is sort of motivating, too. But the bigger part is that it’s hard to go back and skim an audiobook for a favorite part or a specific quote or a refresher, but that’s easier to do with a physical book. I very often revisit books I’ve listened to through the audio version.
And most of the Kindle books I read are books we already have a physical copy of because it’s what my wife read.
So, to answer the question of how I read so much: mostly audiobooks while doing other things I would need to be doing anyway.
When I created Foundations of Generative AI last summer, I committed a cardinal sin: I quoted a book I hadn’t fully read. I saw the quote from the authors on LinkedIn and read the first chapter, but I hadn’t read the entire book.
Fortunately, the book is fantastic. The book AI Snake Oil by Arvind Narayanan and Sayash Kapoor, is a fantastic exploration of some of the undeserved hype, overblown risks, and understated downsides to artificial intelligence.
But there was something interesting as well: the audiobook had a bonus chapter, a sort of podcast about what’s new since the original publication date. One of the things this bonus chapter surfaced was the idea of using AI for literature reviews, and its tendency to reinforce a “rich get richer” approach.
I’ve tried to find anywhere else that idea might be unpacked more completely. They also wrote a fantastic article on their blog titled “Could AI slow science?” in July 2025 that alluded to the idea, but the audiobook unpacked it in more detail. There have been other articles about this, like this one, and this one, and this one, but none of them really directly tie into the bonus chapter’s notes.
So, I’m sharing this for three reasons:
AI Snake Oil is a great book.
Citation collapse was already getting discussed before my article. I wish I’d listened to the book first so I could have tied into their commentary on the topic.
If anyone knows more specifically what they’re talking about in the bonus chapter, let me know!
So, to make this make sense, it’s important for me to share a couple interesting little details about where I live and my daily routine.
About ten years ago, we built a house—well, hired a company to build a house—next door to the house I grew up in.
Then, six years ago, my oldest child started attending the same school that I attended from elementary school through high school graduation. It’s about a 20-minute drive away. I handle morning carpool.
The combination of those two elements means that every single morning, I drive the exact same route that I drove every single morning 20 years ago when I was a senior driving myself to high school.
That’s given me some weird perspective on how some things have changed. For one, although there’s this idea that traffic is generally always getting worse, I can say with confidence that for this particular singular route, traffic has actually gotten better over the last 20 years. When I was a senior, if I didn’t get out of the house by 7:10AM, I wouldn’t be in class by 8:00AM. The route is 20 minutes with no traffic, but back then, traffic was bad, and it got exponentially worse from 7:10AM to 7:30AM. But nowadays while we aim to leave at 7:10AM, we’re actually just fine as far as literal tardiness is concerned if we pull out at 7:25AM or 7:30AM.
But there’s a more specific trend I’ve noticed. When I was in high school, traffic on Friday was always worse. On Fridays I really needed to aim for 7:00AM. I don’t know why that was, but it was reliably true. There’s actually an old joke that made the rounds on social media about Atlanta traffic—I found a version of it on reddit. The key line is:
The morning rush hour is from 5:00 am to noon. The evening rush hour is from noon to 7:00 pm. Friday’s rush hour starts on Thursday morning.
It was a joke, but it felt like there was some truth. Friday rush hour was always way heavier.
This morning, I took my kids to school. We rolled out at 7:07AM: I checked the timestamp on our security cameras. Usually at that time on other weekdays, we’d be looking at about 25 minutes. Back in high school, Friday would add 10 minutes. But instead, we rolled into carpool at 7:26AM. 19 minutes. For context, when I took them to an event on Saturday morning when there were basically zero other cars on the road, it took us 17 minutes.
That wasn’t a one-off occurrence. The past two years, I’ve known that on Fridays, we can afford to leave fifteen minutes later and still get to school in plenty of time. But twenty years ago, Friday meant leaving ten minutes earlier.
What changed, and why am I babbling about this in an article about a four-day workweek? More and more, I’ve been reading about how one of the “compromises” around remote work has been remote Fridays. Companies are specifically designating Friday as the work-from-home day. There’s some precedent for that as well: I remember when I worked for a company, they instituted no-meeting Fridays as a similar opportunity to focus on deeper work. I know colleagues at Georgia Tech who similarly try to set aside Friday for paper-writing, assignment-grading, and other non-meeting activities.
If everyone’s working remotely on Fridays, that certainly explains the lack of traffic I’ve seen. But there have also been lots of articles about Friday “quiet-quitting”, or confession posts on sites like reddit from employees noting how they actually spend their remote days.
In my opinion, here’s the reality: while throughout history there have been times where a big, top-down mandate for a 40-hour workweek or a 5-day workweek or some other constraint has been handed down, the majority of developments happen over time, naturally, and organically. Right now, with the rise of AI, we’re seeing individuals’ productivity rise in a way that has many people calling for shortened workweeks. But rarely does a company come out and say, “Everyone’s 25% more productive, so you all get Friday off!”
But what does happen is that the productivity gains from AI merge with the social changes toward remote Fridays to create a world where people are able to work four day workweeks with no real negative repercussions. They get their work done, and their new day off happens to coincide with a day where their colleagues, who are given the same “remote” day, are also off, so the real-time pressure to be available diminishes. The four day workweek isn’t dictated, but it emerges.
Of course, there are places this will take more time than others. Anything that requires a lot of synchronous interaction will by necessity be slower to move. But coming out of COVID, lots of schools have replaced snow days with digital learning days. Is it a far stretch to imagine a near-future where schools institute digital learning Fridays, where Friday is set aside as a day for students to work asynchronously and for teachers to catch up on planning and grading… only to quickly morph into another day off as those tasks are instead integrated into typical free periods and study halls?
Ten years from now, it would not surprise me in the least if the world—or at least the United States—had generally converged on an unspoken four-day workweek for office workers, where Friday is designated as a remote work day but where—like good students in middle school—we all finished our homework during the day and got some free time back.
As I’ve done the last five years (2020, 2021, 2022, 2023, 2024), I’m ending the year by selecting the top ten books that I, personally, read in the past year—regardless of when they were released. I don’t usually review books because for the most part, if I don’t like a book, I think that says more about the reader–book fit than the value of the book itself; but I do like to specifically recommend books that I think will appeal to a lot of people (or improve a lot of people’s lives), and this is my once-yearly way of doing that. And as always, an entire series might qualify as “one” of the ten books if I don’t think it’s possible to separate the appeal of any single book from the series as a whole.
An interesting note on my “methodology”: the way I make these lists is to go back through my Goodreads list for the year and look for books I assigned 5 stars (for context: I almost never give a rating other than 5 stars; 5 stars mark my favorite books, 1 stars mark the extremely rare books I think are objectively bad, and every other book doesn’t get a rating). I copy them down here, pre-assigning them to either my Top Ten or to the honorable mentions. Then, depending how the numbers work out, I either drop a couple down to Honorable Mention or select my favorites from the honorable mentions to move into the top section to get to ten.
This year there was no moving up and down; there were ten books I identified as my ten favorites from the get-go. Neat.
So, here are my top “ten” books that I read in 2025, in no particular order. Well, technically, in a very particular order: the order in the year in which I read them.
Lifeform by Jenny Slate. I love the way Jenny Slate writes right at that line between prose and poetry, and how the individual short stories leave you wondering how autobiographical each one might actually be. She’s one of the only authors I’ve found that can make you laugh, cry, and think in the same sentence, let alone in the same book.
The 22 Murders of Madison May by Max Barry. I’m three-for-three with Max Barry, Providence and Jennifer Government were already two of my all-time favorites. In this one, I love the light-touch sci-fi angle that stays in the background except where necessary, and I love the twist. My favorite kinds of twists are those that connect to something outside the story itself, whether that’s the book’s name, the book’s structure, or the book’s literal printing style.
The Scholomance Trilogy by Naomi Novik. I thoroughly enjoyed this sort of alternate take on the school-of-magic trope. I appreciated how it confronted the necessary realities of the setup head-on and incorporated them into the world-building rather than hand-waving it away as “well, I guess everyone’s just okay with sending their kids to such a dangerous place.” I also loved how it reflected real-world questions of society and equality without getting too heavy-handed: it was easy to read as a story on its own without constantly figuring out the source of an allegory, but it was also easy to pick up that the darker implications of the book’s world are mirrored in the real world.
Humankind: A Hopeful History by Rutger Bregman. I’ve thought about picking a single book of the year in addition to my top ten, but some years there’s not a clear favorite. This year, though, there was, and it was this. It’s a science-backed account of the evidence of humanity’s inherent goodness, along with a compelling explanation of how that goodness gets co-opted for evil—and what we can do about it. My latest entry into my eventual list of “books I wish everyone would read”.
The Martian by Andy Weir. I said this a couple years ago when Project Hail Mary was one of my favorites, but it almost seems silly to add my two cents to something written by an author as popular as Andy Weir, except to say again—my expectations for this book were sky-high, and yet it still exceeded my expectations.
The Culture Map by Erin Meyer. I really appreciated this attempt to bring science to some intercultural differences that we feel intuitively, but struggle to describe without getting into overgeneralized stereotypes. I’ve found myself putting it into use on multiple occasions already (and, worse, revisited conversations I’ve had over the years with a new realization about the context and finally figured out what I should have said differently—oh well).
The Alignment Problem by Brian Christian. I loved this book even though, interestingly, it doesn’t actually talk about the alignment problem itself that much. What I loved is that it talks about how deeply entwined machine and human learning have been, and it gives several anecdotes about how each have informed the other over the years. It’s amazing how many times something was discovered in one field—either cognitive science/neuroscience or machine learning—that made the other field say, “Huh… we should try that, too” only to find out it’s true for both artificial neural nets and real brains. I find it particularly fascinating that while psychology has evolved from behaviorism to cognitivism, early AI efforts were more more cognitive while more recent improvements are more behaviorist in many ways.
Playground by Richard Powers. I read this at the same time as The Alignment Problem, and they’re bizarrely good companions: not only does Playground tell the lightly-fictionalized origin story of a ChatGPT-like AI assistant, but while The Alignment Problem focuses on how AI learning is similar to human learning, Playground focuses on how human relationships have a massive impact on technological development, which then impacts human society. It also has one of those phenomenal structural twists like The 22 Murders of Madison May, although to experience it fully I’d highly recommend reading it rather than listening to the audiobook.
I’m Starting to Worry About This Black Box of Doom by Jason Pargin. I always feel a little weird putting Jason Pargin’s books among my top books of the year (this is the third time in four years) because the humor is pretty vulgar and errs on the juvenile side, but he has this remarkable ability to write stories that seem absolutely absurd and immediately realistic at the same time—in a way that makes you reflect on how something so ridiculous can also be so believable. And in this book, what really shined through was how he created characters that would usually be extremely unsympathetic, but revealed their backstories in a way that made them believable and understandable. You constantly find yourself saying, “I think this character’ is absurd’s beliefs are despicable, but I can understand where they came form”, which I think is a truly rare form of character writing.
Death of the Author by Nnedi Okorafor. This was going to be an honorable mention for me until right at the end—it’s a really entertaining and novel story featuring a fascinating look at a different culture (different to me, anyway), some questions from the near-future about augmented humanity, and a story that sort of meandered but was fun to follow nonetheless… until the twist at the end. it’s similar to Playground and The 22 Murders of Madison May in that the twist is less within the plot and more structural to the book as a whole, and it completely changes the entire story.
And that aside, my (long, long) list of honorable mentions for 2025. Some of these have comments, some of these are just me saying, “Hey, I liked this one too!”
Honorable Mentions:
Ninth House and Hell Bent by Leigh Bardugo. The fact that Bardugo actually went to Yale and was a member of one of these societies just makes everything more fun to read.
Alter and Point Nemo by Jeremy Robinson. It was cool listening to Jeremy Robinson do something a little more serious with Alter, and Point Nemo was just typical action-packed Jeremy Robinson in a good way.
Night Watch, Thud!, and Snuff by Terry Pratchett. I’d always heard the later City Watch books were Pratchett at his best, and I agree after these.
A Traveler’s Guide to the Stars by Les Johnson. This book reminds me of the math books of the 1950s and 1960s whose techniques would one day power artificial intelligence once computers got strong enough. It walks through how we’ve already demonstrated what specific engineering problems must be solved to enable interstellar travel, and how close we are. I read Pale Blue Dot this year, too, and A Traveler’s Guide to the Stars feels to me like a more up-to-date version of it.
A Very Punchable Face by Colin Jost. Also hilarious. The timing (2021) also made it an interesting snapshot, given that it was written at the height of COVID and by someone who tells political jokes for a living.
Nemesis by Jeremy Robinson. So an interesting little slice of history: Robinson wrote his Project Nemesis series before writing Infinite, which established itself as the frame story for a lot of Robinson’s other works. One of the worlds Infinite visited was the world of Nemesis, and it was one of my favorite chapters, so it made me go read the entirety of Project Nemesis. It was great, except the chapter in Infinite was actually a sort of alternate-universe take on Project Nemesis that I really wanted to read more about… and then this book came out, which is the actual alternate universe Nemesis story from the Infinite series. And it was really good.
This year as well, Goodreads added some cool little visuals for the “My Year in Books” recap:
Sort of a random set of books to highlight, but hey. I found this interesting, too:
I’ve got an annual goal of 100 books, and it’s true that early in the year I tend to focus on shorter books early in the year just so I won’t need to rush at the end of the year. I hit 100 books in September, so my books in October, November, and December were just way, way longer.
Of those 111 books, 91 were audiobooks, 12 were physical books, and 8 were on Kindle. I’ve been working on the same physical book since August, but my time to sit down and read an actual book that I have handy has frustratingly evaporated. That sentence was originally written last year and is exactly true again this year.
Mostly a place where I write down things I repeat often so that instead of repeating them so often, I can just send a link.
Disclosure: I use Amazon referral links in some of my blog posts. That's mostly just a lightweight way to track and see if anyone's even clicking through. If you buy something through one of these links, I may get a bit of money back and achieve my dream of one day being able to buy the nicer set of kitchen scissors that Amazon sells instead of the bargain variety.
