Every few months, the world starts to feel louder than usual, not just in noise, but in speed.
Everyone’s launching, iterating, fine-tuning, scaling. We’re building machines that learn faster than we do, writing papers that summarize centuries of work in a few thousand tokens. And somewhere between the citations and the press releases, I start to wonder what we’re really chasing, and what we’re unlearning.
This week’s list isn’t about news or novelty. It’s about attention. About the kinds of reading that slow you down until the edges of things start to shimmer again. These pieces reminded me that learning isn’t a race toward comprehension. It’s an act of reverence for ideas, for nuance, for the strange ways we metabolize information into belief.
Some of these are scientific; some spiritual; some just beautifully absurd. But each of them, in their own way, asks what it means to stay human while the world keeps optimizing.
1. Mouse Studies — Asimov Press
A quiet meditation on the invisible lives sacrificed in the name of discovery. The writer traces the moral geometry of the lab (cages, needles, and all) and forces you to see what “necessary suffering” really looks like when stripped of euphemism. It’s not sentimental; it’s forensic. What I took away is that science’s beauty often hides its violence, and the real ethical question isn’t whether progress is worth the pain, it’s whether we’ve learned to flinch less than we should.
2. How I Master (Virtually) Anything — Ruben Hassid
Ruben’s essay is a blueprint for accelerated learning, but what lingers isn’t the framework; it’s his faith in curiosity as a discipline. He uses AI not to replace effort but to remove friction, turning knowledge into something you can sculpt. The way he reframes “mastery” as a sequence of 80% consumption and 20% insight extraction reminded me that attention, when structured well, can mimic genius. What I got from it wasn’t a productivity hack, but a quiet reassurance: mastery is just pattern intimacy, learned over time.
3. AI Agents & NotebookLM Customization — AI Maker
This guide starts as a tutorial and ends as a philosophy lesson. Watching someone design a personalized AI teacher, a machine that builds flashcards, prompts itself, and questions your understanding, feels like witnessing the re-invention of apprenticeship. It made me think of the Renaissance atelier: the student learning under the master, only now the master is silicon and endlessly patient. What I took away is that learning will soon become less about memorization and more about dialogue with our own tools.
4. Nobel Prize in Economics 2025 — Popular Summary
Mokyr, Aghion, and Howitt remind us that progress is not a straight line; it’s a self-eating loop. Their work on creative destruction reframes growth as a moral rhythm: every invention births an extinction. Reading this felt like zooming out on human ambition itself, our compulsive need to replace, improve, outdo. What I took away is that innovation isn’t just an engine; it’s an appetite. The question is whether we can feed it without consuming ourselves.
5. Why LLMs Can’t Discover New Science — Vishal Misra, Columbia
A lucid, almost poetic takedown of the myth of “AI discovery.” Misra argues that large language models compress the world into neat probabilistic manifolds, capable of mimicry, not imagination. It’s both humbling and terrifying: we’ve built machines that can summarize everything we’ve known, but none that can hunger for what we haven’t. What I learned is that creation begins where confidence ends, and that might remain uniquely human for a while.
6. Generative AI for Antimicrobial Discovery — Nature Microbiology
This paper reads like science fiction that’s already come true. Researchers trained a protein-based LLM, ProteoGPT, to generate new antimicrobial peptides, or molecules that can kill superbugs more effectively than existing antibiotics. It’s a stunning glimpse of AI as a collaborator, not just a calculator. What I took away is that we’re entering an era where the boundaries between discovery and invention blur, and yet, the awe we feel in response might be the most human part of all.
7. Money Chasing Deals? — Gompers & Lerner (1998)
A 25-year-old paper that could’ve been written yesterday. Gompers and Lerner dissect how inflows of capital distort valuations: how too much money, too fast, raises prices but not quality. It’s a sober reminder that liquidity doesn’t equal insight, and competition can dull rather than sharpen discipline. What I took away: markets, like people, can get drunk on abundance. The hangover always comes in the form of mediocrity.
8. Emotion Mapping — Gill Hill
Hill writes like a cartographer of inner weather. She teaches you how to name, trace, and plot feelings until they stop being fog and start becoming landscape. Her premise, that emotions don’t disappear when ignored, they just metastasize, felt uncomfortably true. What I learned is that emotional literacy isn’t indulgence; it’s infrastructure. You can’t build stability on unnamed things.
9. Joshua Kushner on Thrive Capital — Colossus
Kushner talks about investing like an anthropologist. He frames capital as a medium for human intention, something that compounds meaning as much as money. What I loved here was his calm conviction that long-termism isn’t optimism; it’s operational patience. What I took away: true investing, like true belief, is about staying interested longer than others can stay excited.
10. Everyone’s Pretending AI Isn’t Changing Everything — Hybrid Horizons
This one hit close to home. It argues that the real story of AI isn’t disruption. It’s denial. We build entire work cultures on sand, pretending our tasks, titles, and systems will somehow remain relevant. What I took away is that institutions rarely die from obsolescence; they die from decorum. The future won’t ask for permission before it arrives.
11. Between Cult and Culture — Finbarr Barry Flood, The Art Bulletin
Flood unravels the mythology of Islamic iconoclasm with breathtaking nuance. He argues that image destruction wasn’t mere hatred of form, it was a philosophical argument about representation, power, and faith. It made me realize how easily history flattens motive into stereotype. What I took away: destruction, too, can be a kind of authorship, a way of editing what a society chooses to remember.
12. Swipe Left 37 Times — Quartz
A mathematically hilarious, emotionally absurd piece. It lays out the “optimal stopping rule” for dating: reject the first 37% of people you meet, then pick the next best one. Rationally sound, spiritually bankrupt, and yet, hauntingly true to modern love. What I learned: we keep trying to apply logic to longing, as if heartbreak were an equation waiting to converge.
13. These Four Words Are Destroying Your Relationships — Darshak
“I don’t have time.” Darshak turns this everyday phrase into an emotional autopsy, showing how it corrodes connection by disguising avoidance as virtue. It reminded me how easily modern life rewards detachment, and how “busy” becomes a moral alibi. What I took away: time is never really missing; it’s just hiding behind fear.
14. An Existential Guide to Living the Beautiful Life — The Shadowed Archive
A lyrical, absurd, and profound ode to conscious living. The writer’s vignettes: eucalyptus water, the death of a shrimp-soul in the sink, a city breathing diesel into dawn, are surreal enough to hurt. It reminded me that beauty isn’t in what we curate but in what we notice before it disappears. What I took away: living beautifully is less about taste and more about tenderness, which, in turn, is the courage to keep noticing, even when it’s ugly.
Reading these pieces back-to-back felt like walking through a museum built in reverse: from algorithms to awe. Every essay, every paper, every note seems to be circling the same invisible question: what is all this intelligence for?
We’ve built tools that can learn in seconds what took us generations. We can model proteins, simulate economies, even mimic emotion. And yet, the things that make life worth living, grief, friendship, beauty, faith, patience, remain delightfully resistant to optimization.
Maybe that’s the point. Maybe progress isn’t about replacing the human, but about refining the conditions under which humanity can thrive. To me, the most hopeful thing about this moment isn’t that AI can write symphonies or cure diseases. It’s that, in response, more people are rediscovering the value of slowness. Depth. Attention.
We’re starting to remember that wonder is a form of wisdom, too.
The reflection on 'Mouse Studies' truly hit home, particularly the point about science's inherent violence often being obscured. It makes one wonder how we can maintain our ethical fliching reflex when 'progress' is optimized for speed. How do you cultivate this 'act of reverence' for ideas in such an accelerating world? Briliant perspective, thank you.