mapping the crazy AI world
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 pie... 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 underuse... 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 underuse... 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.
How to Build a Career That Thrives Alongside AI
None of this is real and it doesn't matter - Raw Signal Group
rawsignal.ca
Actual humans, meanwhile, are treated more and more like infrastructure: not as citizens, but data-producing substrates, behavioral scaffolds for algorithmic systems.
Jac Mullen • Attention Machines and Future Politics
One very real future being pursued right now looks to turn LLMs into a universal operating system, and thus the friendly assistant — the weaver, the chatbot — would be the universal interface for all “smart” infrastructure, utilities, appliances, tools, household objects, automated machines, etc. Accordingly, one can easily imagine a version of the... See more
Jac Mullen • Attention Machines and Future Politics
growing fragmentation also brought a new opportunity: coordination. The more fragmented the system and the more diverse the incentives of the players, the greater the value in aligning them to work together. Coordination, once a deadbeat managerial function, is now the most valuable function in the modern economy.