TL; DR: AI Age Manager — Food for Agile Thought #565
Welcome to the 565th edition of the Food for Agile Thought newsletter, shared with 35,263 peers. This week, Camille Fournier calls middle management’s AI-era obituary premature, much as Gergely Orosz sees planning and tests outlasting handwritten code. The point that leaders confuse visibility with understanding fits AI transcripts, which Teresa Torres and Petra Wille fear can become weapons. Abundance misleads, too: more code isn’t more revenue for David Pereira and Rich Mironov, a refined backlog can mean the wrong product for Christopher Cummings, and Pavel Samsonov rejects synthetic users’ false certainty.
Next, Jillian Vordick and Stephanie Stamm find only 11% of businesses forecast AI spending accurately, and Kyle Poyar suggests how to make bills predictable. Clear plans are rare, too: Nick Graveline sees AI adoption stalling on storytelling, not tooling. Andrew Chen doubts agents inherently create network effects, yet as they do legwork, Andrej Karpathy sees human work shifting toward understanding, which anchors Alex Ewerlöf’s rejection of ‘coding is solved’: you can’t answer for code you don’t understand.
Lastly, Charity Majors ties psychological safety to uncomfortable learning, not comfort, and Maarten Dalmijn likewise raises the bar rather than designing for the least competent. Mark Levison blames situations instead: most ‘difficult’ colleagues are good people trapped by incentives or missing strategy. Jeff Gothelf sees this gap turning AI mandates into chaos and recommends spending one afternoon on goals and OKRs. Andi Roberts similarly reads matrix power beyond titles, mapping who can affect an outcome.
