Topic
11 entries
linkedin.com · via Mille Bojer
Eight practitioner principles from a 3-day transformative scenarios workshop with 36 participants. AI handled synthesis and pattern-finding in the background; humans kept full ownership, presence, and creative source-hood. The key move: AI outputs are inputs to human judgment, never final products — and because the work isn't attributed to a person, participants hold it more lightly and push back more freely.
cutlefish.substack.com · via John Cutler
Cutler on the question every team is now living: how to adopt AI for the company's benefit without quietly trading away the agency that made the team work. The operating-model companion to the agency argument this site keeps circling.
linkedin.com · via Jazz Rasool
Where AI-assisted coaching meets regulation — the governance layer forming around human-development work done with machines.
every.to · via Every
A coaching-shaped use of the model: reflection partner, not answer machine. The centaur move applied to inner work.
science.org · via Costello et al, Science
The optimistic counter-case: a well-aimed AI dialogue measurably shifted entrenched beliefs and it held. Agency designed in, not eroded — AI as interlocutor rather than oracle.
microsoft.com · via Microsoft Research
319 knowledge workers — the more they trusted the AI, the less critical thinking they did. The empirical anchor for why agency has to be designed in, not assumed.
oneusefulthing.org · via Ethan Mollick
The two ways to stay in charge of AI work — alternating (centaur) or interweaving (cyborg). The framing this whole site keeps coming back to.
arxiv.org · via Margaret-Anne Storey
AI pays down code debt while running up two new kinds — eroded shared understanding (cognitive) and lost rationale (intent). Agency loss as a measurable org-health property.
cutlefish.substack.com · via John Cutler
Cutler's sharpest take on the theme: AI's value depends on whether it supports multiplayer collaboration or accelerates single-player isolation. Uses 4E cognition and stigmergy — shared context and trace-based coordination compounding into collective capability.
ignorance.ai · via Charlie Guo
Nearly every AI tool is single-player: one human, one conversation, no shared context. Maps what changes when agents join the group instead of sitting in a private chat.
The technical reasons AI apps default to single-player — and what persistent, shared state would take to make them genuinely collaborative.