A working notebook for applying the Theory of Embedded Intelligence to the books, conversations, and technologies shaping the present.
What This Series Is
Most theories live in books. The Theory of Embedded Intelligence lives in the engineering decisions, cultural debates, scientific findings, and AI conversations of an ongoing present. TEI in the Wild is where the theory gets exercised — applied to whatever is in front of us, in real time, by a thinker who has spent fifty years asking what intelligence actually is and how it gets built.
Each installment takes a single occasion — a major new book, a notable news moment, a long conversation with an AI, a piece of research worth wrestling with — and reads it through the lens of TEI. Sometimes the occasion is formal: a response to a serious book that deserves a serious reply. Sometimes it’s casual: an afternoon spent thinking out loud with a large language model about Karl Pribram or Michael Levin. Both kinds of occasion produce essays worth keeping.
The point of the series is not to argue that TEI is the last word on any of these subjects. It is to demonstrate what the theory does when you use it. As Bill has framed it in the Canonical Knowledge Base, TEI is an understanding system, not a belief system — it asks to be applied, tested, revised, and brought into contact with new material, rather than memorized or defended. It asks distinctive questions — about where intelligence lives, what it serves, what kind of system must carry it for it to be real — and those questions can be brought to bear on almost any topic of genuine consequence. The hope is that readers will start asking the same questions of their own subjects.
How These Essays Are Made
A book he’s just read. A conversation he’s just had with an AI. A news moment that demands a TEI response. The choice of occasion — and the framing of why it matters — is his.
Working from Bill’s source material, his prior writings on TEI, and his explicit framing, a large language model produces the essay’s prose, structure, and visual presentation — applying the theory he has spent decades developing.
Bill reads the draft for factual accuracy and TEI fidelity. Errors get caught. Overreach gets trimmed. What remains is published. This step is non-negotiable — and is itself a demonstration of what TEI says about the proper relationship between human and machine intelligence.
Currently in the Series
The essays are best read in order. Each builds on themes introduced in the previous one — the founding distinction between embedded and reflected intelligence, the three dialects of intelligent systems, the SPCA cycle, and the relationship between humans and the AIs they are now learning to think alongside.
Intelligence With Purpose
Why the next technological republic must be built on principled embedded intelligence.
When the Atheist Met the Machine
Richard Dawkins spent three days with an AI and came away unable to deny it was conscious. TEI answers the question neither he nor his critics asked.
The Brain That Isn’t Where You Think It Is
A conversation with an AI about Karl Pribram, Michael Levin, and the bioelectric body — and what TEI says about where intelligence actually lives.
The Inner Mensch and the Machine
What is intelligence for? On character as the SPCA cycle, AI as moral mirror, and the human as a bounded infinity.
“Intelligence without purpose is capability without conscience. The question is never whether we are strong enough — it is always: in service of what?”
From Reading to Practice
The Theory of Embedded Intelligence is laid out in full in the Canonical Knowledge Base — including the Three Laws of TEI, the SPCA cycle, the FI↔EI Cycle, the Intelligence Evolution Model, and the Consciousness Framework. To go beyond reading and actually use the framework, the Foundation offers a downloadable system file that turns ChatGPT, Gemini, Claude, or any AI assistant into a TEI-aware thinking partner.