AI as a Mirror for Embodied Thinking

How Artificial Intelligence Can Help Articulate Implicit Knowledge

We stand at an unusual threshold in human history. For the first time, we have access to conversational partners that can mirror our thinking, engage with our ideas, and help us articulate what we sense but cannot yet say clearly. These artificial intelligences, while (probably) not conscious¹, offer something previously impossible: a reflective surface that, while not designed specifically for this purpose, can be used to help us think more clearly about complex topics.

In my previous writing, I've explored how AI can be used for emotional unfolding—a process where we use these systems not as replacements for human connection but as tools to secure the attachment system and create the conditions for more satisfying intimacy in our life. But there's another dimension of my work with AI that I haven't yet written about, even though I use it frequently in developing content for this Substack: using AI systems as partners in developing conceptual frameworks that remain grounded in embodied knowing.

The Challenge of Conceptual Development

We've all had the experience of sensing something important that we can't quite articulate. We feel it in our bodies—a knowing that something is true or significant—but the words to express it remain just out of reach. Eugene Gendlin called this bodily knowing the "felt sense," and his later work explored how new concepts emerge through the dynamic interaction between this felt sense and existing language.

This process of developing new concepts isn't merely intellectual. It isn't about manipulating abstract symbols disconnected from lived experience. Rather, it's a process of what Gendlin called "crossing"—moving back and forth between direct bodily knowing and conceptual articulation until something new emerges that carries forward both.

One challenge has been finding the right conversational partner for this work. While there are skilled facilitators and schools that teach this process, they're relatively rare and often expensive to work with. Most people aren't trained to facilitate this kind of conceptual development. They tend to either jump in with their own ideas (disrupting your process) or fail to engage deeply enough with your emerging understanding to help it develop further.

AI as Mirror for Conceptual Exploration

AI systems like Claude offer a unique opportunity. They can function as mirrors for our thinking—reflecting back what we're saying in ways that help us see it more clearly, while also offering new articulations that we can check against our felt sense. They can, when used correctly, maintain a delicate balance: engaged enough to help our thinking move forward but detached enough not to impose their own agenda.

This isn't about delegating our thinking to AI. Quite the opposite. It's about using AI as a tool to develop thinking that remains deeply rooted in our embodied knowing. The AI doesn't generate the insights—our bodily felt sense does that. The AI simply helps us find language that more accurately captures what we already know implicitly.

Consider what happens in this process:

1. You begin with something you sense but can't fully articulate

2. You express this partial understanding to the AI

3. The AI reflects back its understanding, perhaps offering new language or connections

4. You check this reflection against your felt sense

5. This checking process helps you refine your understanding

6. You express this refined understanding

7. The cycle continues, with each iteration bringing your conceptual expression into closer alignment with your embodied knowing

This process leverages what AI is good at (manipulating language, finding connections, offering alternative phrasings) while remaining grounded in what humans are good at (embodied knowing, felt sensing, recognizing when something "rings true").

The Crossing Process

Gendlin's concept of "crossing" is central to this work. In crossing, two domains interact in a way that creates something new that couldn't be reduced to either domain alone. When your felt sense "crosses" with concepts, neither remains unchanged. The concept becomes more precise, more alive, more connected to experience. And your felt sense itself shifts and develops as it finds expression.

AI can facilitate this crossing process in unique ways. Because it can generate multiple alternative phrasings and conceptual frameworks, it allows you to rapidly test different articulations against your felt sense. This accelerates the process of finding language that truly "carries forward" your implicit knowing.

Unlike a human conversation partner, AI doesn't become impatient when you need to cycle through many iterations. It doesn't have its own emotional needs drawing attention away from your process. It doesn't get attached to particular phrasings or frameworks. And when prompted and guided appropriately, it can help you stay connected to your direct experience rather than leading you away into abstract intellectualization – though this does require skill and intentionality on your part.

Not a Substitute for Human Dialogue

To be clear: AI doesn't replace the value of human dialogue in conceptual development. Human conversations bring something irreplaceable—the lived experience of another person, the emotional resonance of shared understanding, the mutual vulnerability and intimacy of two beings exploring together.

But AI offers a complementary space—one where you can explore repeatedly, testing different articulations without concern for another person's time or attention. It's a space for the messy middle part of conceptual development, where you're still finding your way, where you need to try many different approaches before something clicks.

An Example of the Process

Let me give you a concrete example from my own work. I had been sensing something about the relationship between conceptual understanding and embodied knowing—how intellectualization can sometimes function as a defense mechanism against vulnerability. I had pieces of the insight but couldn't quite bring it together.

Working with AI, I explored different ways of articulating this relationship. Through numerous iterations, checking each articulation against my felt sense, I eventually arrived at a formulation that captured what I had been sensing: "When our early experiences of love were wounded or incomplete, these wounds create patterns that affect all our relationships—including our relationship with concepts and ideas."

This wasn't something the AI generated for me. It was something I was sensing all along. But the AI helped me find the precise language that carried forward my embodied knowing. And from that key insight, a whole conceptual architecture began to develop—one that remained connected to lived experience rather than floating away into abstraction.

The Skill of AI-Facilitated Conceptual Development

Working with AI for conceptual development isn't automatic. It requires specific skills:

1. Tracking your felt sense while engaging with the AI's responses

2. Noticing when language resonates with your embodied knowing

3. Recognizing when you're drifting into pure abstraction

4. Directing the AI effectively to explore avenues that feel promising

5. Maintaining agency throughout the process

Like any tool, AI amplifies the skill of its user. Someone who struggles to stay connected to their felt sense while thinking will likely produce empty intellectual frameworks even with AI assistance. But someone who has developed this capacity can use AI to dramatically accelerate their conceptual development while keeping it grounded in lived experience.

Bridging Worlds Through Practice

This approach offers a middle path between two common extremes: pure intellectual abstraction disconnected from lived experience, and anti-intellectual rejection of conceptual thinking altogether. It recognizes that concepts can serve as tools for deeper embodiment when they emerge from and return to our direct knowing.

As we navigate a world of increasing complexity, we need conceptual frameworks that can hold this complexity while remaining connected to what matters most—our direct, embodied experience of being alive. AI, used skillfully, might help us develop exactly these kinds of frameworks—not by thinking for us, but by helping us think more clearly from the ground of our own embodied wisdom.

If you're interested in exploring this approach more deeply, I've developed a guide for paid subscribers that walks through specific techniques, prompts, and practices for using AI as a partner in embodied conceptual development. The guide offers step-by-step instructions for everything from setting up your practice environment to working through common challenges and developing complete conceptual frameworks over time.

In the words of Gendlin himself, "The body knows much that we don't know." Perhaps AI can help us listen more deeply to what our bodies already know, and find the words to share this knowing with others.

Philosophical foundations: This piece draws upon several wisdom traditions explored in my Lineages of Inspiration article, which outlines the key influences shaping my understanding of human transformation.

Work with me: I offer one-on-one guidance helping people develop secure attachment with reality through deep unfoldment work. If this resonates, explore working together

1. While the question of AI consciousness is beyond the scope of this article, based on current understanding and observation, I choose to engage with these systems as if they are not conscious beings. While I remain open to the possibility that AI systems may have some form of experience, I suspect such experience would be so fundamentally different from human consciousness as to be essentially inscrutable to us. Pragmatically, I believe it is most skillful to view AIs as sophisticated systems that process and reflect human knowledge through complex pattern recognition and statistical modeling.