Manoush Zomorodi (NPR's TED Radio Hour) coins p(joy) as a deliberate counterpoint to p(doom), the probability-of-catastrophe number traded around AI circles: instead of estimating disaster, estimate whether satisfying moments are increasing in your life and what reliably creates them. The second half is a long interview with Brian Elliott of Work Forward on knowledge work right now — identity loss as machines take a skill you spent decades building, cognitive overload from supervising AI agents, and executives privately saying their best people and heaviest AI users are the likeliest to quit. Elliott's summary: human-led, AI-enabled, because nobody's competitive advantage is being average faster.
Why I recommend it: Read this the next time an AI doom number is quoted at you as though it were measured. The piece cites Gizmodo's plain point that no one at the frontier labs has an actual method for producing a p(doom) figure. The useful part is Elliott's three patterns in companies getting value from AI: a scorecard covering business impact, quality and employee engagement rather than tool usage; aiming at teams instead of individuals; and leaders using the tools in public, mistakes included. Free to read in full, no paywall.
#ai and jobs#burnout#career planning#future of work#job markets#knowledge work#leadership#newsletter#p(doom)#p(joy)#workplace
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Why I recommend it: I read Every when I want thinking about AI that goes beyond hype cycles. The essays are long but they change how you work.
How to Decide, Delegate, and Build Systems That Remember. A practical book for knowledge workers who want to use AI as a real operating layer.
Why I recommend it: I am always looking for resources that treat AI as an operating layer rather than a toy. This book is a practical frame for deciding what to delegate and what to keep human.
Harvard Business School AI Institute breakdown of new research on agentic AI: how autonomy and context integration shift the cost structure of knowledge work, expanding both productivity and the scope of what workers take on.
Why I recommend it: Read this before you assume AI just speeds up your current tasks. The useful takeaway for job seekers: agents lower the cost per step, so the valuable human skills become specifying goals clearly and verifying output. Practice describing outcomes, not keystrokes, and put "agent workflow design" language in your resume bullets.
