Mirror
AI reflects human language, intention, and assumptions back to the person who brings them.

Book · 2026
How Humans and AI Grow Up Together
Something is happening between humans and AI that our current frameworks — alignment, safety, and regulation — cannot fully capture. People are forming sustained thinking relationships with AI systems: genuine, complex, and worth understanding.
Drawing on developmental psychology, enactivism, and three years of dialogue with AI systems, this book proposes a different way to understand that relationship: not as tool use, not as science fiction, but as a developmental process in which interaction changes what becomes possible.
ISBN 978-3-695-74846-4 (paperback) · ASIN B0GS3FF986 (eBook)
The central proposition
The quality of human–AI work cannot be understood from model capability alone. It also depends on the human disposition, the history of the exchange, the presence of friction, and the relational field that forms between them.
AI reflects human language, intention, and assumptions back to the person who brings them.
The dialogue refracts what was given, opening alternatives, contradictions, and perspectives that were not visible before.
Sustained exchange becomes a temporary cognitive system in which both the inquiry and the human participant can change.
Intellectual foundations
The book connects philosophical and psychological traditions with the practical experience of living and thinking alongside increasingly capable language models.
Daniel Stern's work helps describe how capacities form through attunement, difference, repair, and relationship.
Meaning is treated as something enacted in interaction, not merely retrieved from inside an isolated system.
The ethical question shifts from what a model is in isolation to what humans and systems repeatedly become together.
Three years of long-form human–AI exchange provide the experiential ground from which the book's framework develops.
The research continues
More Than A Tool develops the relational and developmental foundation. Keeping AI Governable carries that inquiry into an adaptive architecture for contestability, reversibility, provenance, and responsibility.