mapping the crazy AI world
“Most major technological innovations come into the world like electric arc lighting—wondrous, challenging, sometimes dangerous, always raw and imperfect,” Goldfarb and Kirsch write in Bubbles . “Inventors, entrepreneurs, investors, regulators, and customers struggle to figure out what the technology can do, how to organize its production and... See more
AI Is the Bubble to Burst Them All
AI and the Total Destruction of Trust
jphilll.comintentional friction keeps my thinking sharp and ensures that when I do engage with automation, I do so from a place of genuine understanding and deliberate choice.
every.to • In the AI Age, Making Things Difficult Is Deliberate
the pedagogical value of a writing assignment doesn’t lie in the tangible product of the work — the paper that gets handed in at the assignment’s end. It lies in the work itself: the critical reading of source materials, the synthesis of evidence and ideas, the formulation of a thesis and an argument, and the expression of thought in a coherent... See more
Nicholas Carr • The Myth of Automated Learning
as they communicate in ways that are literal, or strange, or narrow-minded, or just plain wrong, we will incorporate their responses into our lives unthinkingly.
Joshua Rothman • A.I. Is Coming for Culture | the New Yorker
1. Audit your skill stack. List the 3–5 core components of your role. Circle the one you’d be least confident doing solo. That’s your first gap.
2. Map the adjacent skills. Write down the two roles you rely on most but don’t do yourself (designer? analyst? ops?).
3. Zoom out to cross-functional human skills. Pick one “people” capability you... See more
2. Map the adjacent skills. Write down the two roles you rely on most but don’t do yourself (designer? analyst? ops?).
3. Zoom out to cross-functional human skills. Pick one “people” capability you... See more
How to Build a Career That Thrives Alongside AI
While AI is most effective at automating narrow, repetitive tasks, it’s less capable of stitching those tasks together into a coherent whole. A full-stack professional knows how to orchestrate —they use AI to handle discrete components, while maintaining oversight and strategic control across the entire workflow.
How to Build a Career That Thrives Alongside AI
You need depth, not least because it's essential for AI oversight. Only someone with domain fluency can evaluate a model’s outputs, catch subtle errors, and know when to override. And you need breadth because while AI excels at narrow, repetitive tasks, your edge becomes being able to understand adjacent domains.