I’ve been silent for a while on both Linkedin and on Substack. It’s felt strange not to be writing as frequently, but I honestly needed a little break. I could feel the burn out coming and writing for Substack was feeling more like a job and less like an outlet. That’s okay…to an extent. But, at the end of the day I still want to feel excited when I push things out to the weird and wacky world of people who follow me. That feeling was staring to feel like a sough through the branches or a ghost haunting me more than something I was feeling when I pushed send.
The second reason I took a break is I got stuck. I promised three bots in this series I had been working on.
The first was the Depth Bot — a drill that trains the disposition of not accepting easy answers, built around the idea that some dimensions of knowledge are ordinarily invisible and need to be excavated rather than explained.
The second was the Bridge Bot — a tool for building analogies from deep knowing to unfamiliar territory, built around the idea that the student who translates a concept into their own language becomes the teacher of their own understanding.
I am not going to build the third bot.
Not because I ran out of ideas. Because I reached a limit that I have been sitting with through this time of publishing silences. It’s a genuine limit, not a rhetorical one, and it is the first real blocker I’ve run into since working with AI as frequently as I do now. I think being honest about that limit is more valuable than pretending it does not exist.
The Third Modality
The three modalities of learning I described in the adventing essay were depth, novel capacity, and incorporation. Depth is about making visible what is ordinarily covered. If you like the philosophical language of having dashes, it is the process of dis-covering the hidden dimension of knowledge that a sufficient answer does not require you to see. Novel capacity is about building bridges. With novel capacity we cross from territory you know deeply into territory you are trying to enter, becoming the teacher of your own understanding in the process. It’s the kind of depth of insight we hope every student fosters in their time studying with us as a professor.
Incorporation is something different in kind. It is the moment when learning stops being something you have and becomes something you are. I think there is a question of identity wrapped up in incorporation; we realize that we have stopped “faking it until we make it” and we know something deep in our bones. It is that magical feeling when what you have understood moves from the register of representation — stored, retrievable, applicable when needed — into the register of being. That change is truly magical; I’m not trying to use the term in some hyperbolic way. The magic, at least for me, occurs because incorporation changes how we move through world (not just what you know about the world).
The philosopher Maurice Merleau-Ponty described this as knowledge becoming flesh. Not metaphorically. He use the term flesh with an unfinished, but unnerving, precision. The body that has learned something in the flesh does not consult the knowledge. It enacts it. The experienced surgeon does not think through the procedure. The fluent speaker does not translate. The skilled teacher does not apply pedagogical principles. The knowledge has been incorporated; it is taken into the body, distributed through the organism, available not as a resource to be retrieved but as a capacity to be exercised.
Why a Bot Cannot Occasion This
This is beyond a bot (that seems clear). But, I think it is also beyond what a bot can occasion in a learner. So despite my intentions there is no third bot in my series of things I set out to build. I reached a limit I didn’t realize I was going to find when i started out.
I’m not saying this to be contrarian or change with the tides as they turn skeptical of generative AI in some ways. I’m writing about this with the kind of reverence that is reserved for something holy and wholly human. So I’m taking a little bit of a turn into the theological and the philosophical because I want to say precisely why a bot cannot occasion incorporation — not approximately, not rhetorically, but with the care the claim deserves. And, that means not every reader might find this essay enjoyable, but I’m excited to push send on it and for now, that’s good enough.
So I came up with two key reasons that I think fostering incorporation is something a bot will inevitably fail at. The first reason is that AI has no body. This is not a trivial observation. Merleau-Ponty's account of incorporated knowledge is not a metaphor for deep understanding. It is a literal claim about the role of the organism in knowing. The body is not the container for knowledge; it is the site of a certain kind of knowing that cannot exist elsewhere. Knowledge that becomes flesh is knowledge that reorganizes the organism's relationship to its environment. It changes perception, movement, attention, response. It is held not in memory but in the dynamic between a living body and the world it inhabits.
An AI system has no organism. It has no body that moves through an environment, no perceptual system that is reorganized by learning, no musculature that develops new patterns, no nervous system that is literally rewired by experience. What it has is a static representation of patterns. AI is, quite literally, a frozen vector space in which all of its knowledge exists simultaneously, without before or after, without the metabolic processes that allow something external to become genuinely internal. Even as we build “memory” or “soul” files for our AI “assistants,” these are just clever gimmicks to mimic our experience of a living things in its environment. But none of these tools ever actually escapes the frozen space of an AI. At best it changes the shape of that frozen space. But, there is very little that is dynamic in relation to this static form.
The second reason I came up with is that AI has no flowing time. My doctoral advisor, Robert Russel, know more about this than just about anyone else I can think of. I’m not going to go into the depth of his insights, and what follows really requires more care than I can possibly offer, but I think even introducing this idea is important because AI systems do process inputs sequentially and produce outputs that unfold in time. But this is not the kind of time that incorporation requires and that flowing time purports is real. That time is just chronos: clock-time ticking away second after second and constrained to the vicissitudes of finitude.
The time of incorporation is what the philosopher Henri Bergson called duration: the lived experience of time as flow, as continuity, as the way in which the past presses into the present and the present reaches toward the future. It is the time of an organism that has a history shaping its present and an anticipation orienting its future. It is the time in which something can settle, can deepen, can move from the periphery of awareness to the center of being.
AI time is something more akin to what physicists call the block universe. All moments equally present, equally accessible, without genuine before or after. The model that processes your input today is not meaningfully different from the model that processed yesterday's input. It has not been changed by the encounter. It has not had time to let something settle. It exists in a kind of eternal present that is the precise opposite of the flowing duration in which incorporation happens.
A Broader Claim
I want to be careful about something here. What I have just described is not irreducibly human.
The capacity for incorporation — for knowledge to become flesh, for learning to reorganize an organism's relationship to its world — is not a property of consciousness or of humanity. It is a property of being alive in a particular sense: of being an organism in dynamic, intra-changing relationship with an environment, living in flowing time, capable of being genuinely changed by what is encountered. Theologically within many western religious traditions, it is to be a creature.
Trees incorporate. Immune systems incorporate. A body learning to walk incorporates. None of these require consciousness or language or anything we would recognize as human intelligence. They require organisms: the kind of being that has a metabolism, a history, a genuine before and after, a dynamic relationship with an environment that presses back.
AI lacks this not because it lacks consciousness but because it lacks…organismality? (Sometimes you need a good neologism). It is not alive in the relevant sense. Maybe it is conscious and maybe it is not. I kind of don’t care. It lacks the kind of knowing that requires aliveness: that requires the dynamic intra-relationship of organism and environment playing out in flowing time. This is genuinely beyond it, and thus, I’m not sure it is a good tool to use to try and form this kind of depth in students.
Lest you think I have given up on the value of AI for higher education, this is not an anti-AI screed. While I do think this is a fundamental limit of what AI can usefully do in education, it simultaneously points to how fleeting and few these kinds of educational encounters really are (and how much our current models obsessed with productivity have devalued this kind of education).
All of this (and I do mean all of this) matters beyond the question of education. It is a statement about the nature of knowledge itself. There are kinds of knowing that are not representational — not stored, not retrievable, not transmissible as information — because they are not, at bottom, representations. They are configurations of a living organism. They exist in the flesh or they do not exist at all.
What This Means for the Teaching Bot Trilogy
The Depth Bot and the Bridge Bot are genuine tools. They work in the register of representational knowledge: they operate in the realm of knowledge that can be stored, retrieved, examined, extended, translated. In that register, AI can do real and useful work. The bots I built do not pretend to more than they can do, and within their actual range they occasion something genuine in us as the user.
But there is a ceiling. And, the ceiling is not a failure of engineering or imagination. It is a structural feature of what AI is — a frozen, non-organismic, atemporally present system — encountering what incorporated knowledge requires — a living body, flowing time, a genuine before and after.
The honest response to a genuine limit is not to pretend it is not there, or to promise that more compute will eventually overcome it, or to dismiss the entire project because the ceiling exists. The honest response is to say: here is what these tools can do, here is where they cannot reach, and here is why the distinction matters. What lies above the ceiling is not lost because AI cannot reach it. It is preserved in the hands, the bodies, the flowing time of teachers and students who are, whatever else they may be, alive.
That is not nothing. In fact, it may be everything.
A Postscript on Wonder
There is one more thing I want to say before closing this trilogy that I was reminded about when visiting my friend and former colleague Tyler Atkinson.
The medieval theologian Bonaventure distinguished wonder from curiosity. Curiosity wants to close. It wants to find out something in order to generate resolution. Curiosity is fundamentally about arriving at the answer. Wonder, though, is content to remain open. Wonder want to be undone by what it encounters, to find itself enlarged rather than satisfied by what it discovers. Wonder can’t close itself off in the face of dis-covering.
The Depth Bot can create the conditions for curiosity to become wonder. It refuses to let the student close too quickly, by finding the seam in every sufficient answer, by making visible what was invisible. The Bridge Bot can create the conditions for wonder to emerge through the structure of things. It shows how a concept maps onto a domain of deep knowing, and then where the mapping breaks down, revealing something that cannot be captured from any single angle.
But wonder in its fullest sense, and here I mean the kind that Bonaventure described as the beginning of wisdom or the kind that is not a feeling but a posture toward the world, this is itself a form of incorporation. It is a way of being in the world that has been formed by encounter, by time, by the accumulated experience of finding that things are stranger and richer than they first appeared. A bot can point toward it. It cannot produce it. It cannot even, finally, occasion it — because wonder in this sense is not something that happens in a conversation. It is something that happens in a life.
The life is yours. The bots are tools no matter how conscious we think they become.
I hope we all use them accordingly.