Weekly Reading List: 12/10/2025

Things I Read This Week That Made Me Think

Every week, I collect the things that make me pause mid-scroll, not because they’re breaking news or trend pieces, but because they hold a kind of friction. Pieces that make you want to underline something. Or text a friend. Or shut your laptop for a minute and think.

This week’s list runs across invention and introspection. There’s a 2016 post that still defines how we think about “minimum viable products.” There’s a beautiful essay about swimming in the slow lane and learning to live without speed as validation. There are AI studies that read like cautionary tales: one exploring if language models can develop gambling addiction, another testing whether they can simulate human purchase intent. And then there’s the messy, human middle: essays on shopping exhaustion, confidence, and the creeping paranoia at the heart of AI power politics.

It’s a list about control: what we build, what we consume, and what consumes us in return.

1. Making Sense of MVP – Henrik Kniberg
The piece that reshaped how product people think. Kniberg explains that an MVP isn’t the first broken version of your vision; it’s the smallest complete experience that delivers real value. It’s not a half-car, it’s a skateboard that moves. I revisit this every few months because it resets my brain around progress. It’s a reminder that you’re supposed to learn from motion, not polish. That elegance comes after evidence. That iteration isn’t about cutting corners, it’s about earning clarity.

2. The B-Lane Swimmer – Holly Witteman
A reflection on being the swimmer in the middle lane, the one who’s not winning medals, not quitting, just doing the work. It’s about effort as a quiet act of dignity rather than competition. I loved this piece because it reminds me that ambition doesn’t always have to look like acceleration. Sometimes staying in your lane (literally) means surviving the urge to measure everything. It made me think of how most careers aren’t linear; they’re laps, repetition, and the grace of continuing.

3. Machine Learning Is Not Just Statistics – The Palindrome
A clear-eyed essay on how machine learning differs from traditional statistics not just in technique, but in philosophy. It argues that ML isn’t about describing data; it’s about adapting to it, continuously. It reminded me that “learning” in systems mirrors “learning” in people- the nonlinear process of adjusting your priors. In a world obsessed with prediction, this felt like a quiet manifesto for humility: that good models (and good minds) stay curious, never conclusive.

4. Is It Written by AI? – Naomi Alderman
A novelist’s detective guide to spotting AI writing. Alderman dissects tone, rhythm, and texture, and the way machines mimic logic but miss life. Reading it felt like being reminded that our human quirks are our fingerprint. That the offbeat sentence, the unfinished thought, the misplaced emotion are what make us unmistakably alive. I started noticing how much of the internet now sounds like it’s trying to pass a Turing test, and how hard it is to resist that flattening.

5. The 25 Most Interesting Ideas I’ve Heard in 2025 – Derek Thompson
Thompson’s annual list of mental frameworks and half-formed insight, ranging from economics to culture. A buffet of ideas, loosely threaded by curiosity. This kind of piece reminds me why I love generalists. It’s a masterclass in collecting dots before connecting them. I walked away not with answers, but with new questions about power, progress, and how ideas migrate between fields before we even notice.

6. I Shop, Therefore I Am (Exhausted) – Amy Coded
A reflection on how consumption has replaced identity-making. The essay explores how buying things has become the way we prove taste, status, even selfhood, and why that cycle is emotionally draining. This hit me hard. Especially the idea that exhaustion is now a byproduct of self-expression.

7. The Reason You Don’t Feel Smart – The Digital Meadow
A meditation on why so many of us feel intellectually inadequate. It argues that intelligence hasn’t vanished; we’ve just outsourced visibility to algorithms, and mistake volume for depth. This one felt like therapy for impostor syndrome. It reminded me that feeling “less smart” is often a function of context, not competence. Sometimes the smartest thing you can do is define your own game and stop keeping score in someone else’s metric.

8. Astrotalk’s $100M Deal Falls Apart – Moneycontrol
A wild story about how a $100M venture deal collapsed when investors discovered NSFW content during due diligence. Beyond the tabloid headline, this says so much about moral signaling in modern capital. The dance between risk and respectability. It’s a story about who gets funded, who doesn’t, and how culture, not just economics, decides what’s “investable.”

9. Infrastructure Inequality: Who Pays the Cost of Road Roughness? – Currier, Glaeser, Kreindler (NBER)
A massive dataset study using Uber accelerometer data to measure “road roughness” across millions of miles in the US, essentially, who drives on the bumpiest roads, and what that says about inequality. The authors find that poorer and predominantly Black neighborhoods experience dramatically worse infrastructure quality, translating to hundreds of dollars a year in “driving pain.” This paper blew my mind for how it redefines infrastructure as a felt experience. The idea that inequality shows up in how your car shakes is haunting. It made me think about data justice in a visceral way: how even the smoothness of the road under your tires can map onto privilege, geography, and race.

10. OpenAI Thinks Its Critics Are Funded by Billionaires – The SF Standard
What it’s about: An investigative piece on OpenAI’s legal campaign against its critics: subpoenas, complaints, and accusations of billionaire-funded conspiracies. It’s unnerving to watch a company built on openness develop such paranoia. The piece made me think about how power shifts culture: the moment idealism meets capital, transparency turns into suspicion. It’s not just about AI. It’s about how belief curdles into control.

11. I Should Be Able to Mute America – Gawker Archives
A hilarious rant about the dominance of American culture online, and the impossibility of turning down the noise. Beneath the humor is something profound: how cultural imperialism now travels through memes, aesthetics, and algorithms. It made me wonder what “digital sovereignty” could even mean when the loudest country owns the feeds.

12. Can Large Language Models Develop Gambling Addiction? – Lee et al.
What it’s about: A research paper exploring whether LLMs exhibit gambling-like behavior like risk chasing, illusion of control, irrational betting. This one’s wild. It treats LLMs like lab subjects in a psychology experiment and finds eerie human parallels. It’s a glimpse into the cognitive shadow of our creations: how machines mirror our pathologies faster than our wisdom.

13. Thomas Peterffy: The Market Maker Who Changed Everything – Colossus
A deep profile of the Hungarian immigrant who automated Wall Street and became one of the world’s most powerful market makers. I loved how human this story was- brilliant, obsessive, suspicious of his own success. Peterffy’s paranoia feels oddly relevant in an age where markets are driven by black boxes. It’s a portrait of genius that can’t relax.

14. LLMs Reproduce Human Purchase Intent – Maier et al.
A study showing that language models can simulate human consumers with startling accuracy, predicting how real people would respond to brand surveys. This led to equal parts awe and dread. If models can mirror human intent this well, consumer research might soon become synthetic. It’s incredible science and an existential question about what happens when empathy itself gets outsourced.

15. Use This Map to Self-Evaluate Your Progress – Rich Decibels
A personal reflection tool that helps you measure growth without using metrics, more compass than checklist. I love ending with this one because it recenters the week. It’s a reminder that progress doesn’t have to be visible, measurable, or optimized. Sometimes it’s just movement in the right emotional direction.

This week’s reading list ended up orbiting a quiet but persistent question: what does control cost, and who pays for it?

From OpenAI’s legal paranoia to Uber’s accelerometer data exposing racialized road roughness, every piece circles the uneasy relationship between progress and power. We build systems meant to optimize the world, and then watch as they start optimizing us. Sometimes through convenience. Sometimes through exhaustion.

There’s a strange poetry to how these essays talk to each other. The B-lane swimmer learning to move at her own pace sits right beside Amy Coded’s confession about consumer fatigue. The rough roads of Black neighborhoods in America echo the invisible biases embedded in large language models. Even the studies on LLM addiction and synthetic market research ask a human question in disguise: when does learning become compulsion? When does simulation become replacement?

Reading them together reminded me that intelligence, human or artificial, means very little without restraint. That friction isn’t failure; it’s the proof that we’re still steering.