Humans are powerful processors. When you account for the entire biological system—neurons, sensory loops, hormonal regulation, immune response, even individual cells—we’re likely operating at exaflop-scale distributed computation. Each cell is a self-contained unit: it reads DNA, builds proteins, forms local networks, and performs autonomous tasks without needing central coordination from the brain. That’s millions of micro-decisions per second, all running in parallel. Perhaps ZetaFlop range.
Some researchers have even speculated that the principles of distributed intelligence—evident in everything from cellular behavior to fungal networks—suggest a deeper organizing logic at work across biology. But that exploration belongs to a different article.
And yet, despite this staggering complexity, most humans struggle with symbolic math.
Why?
Because power isn’t the same as alignment. Math is symbolic and deterministic. Human cognition isn’t. We are probabilistic, intuitive, and context-driven. We don’t compute—we simulate. We imagine. We project.
This mismatch matters. Deterministic systems, like equations, demand rigid execution. Human cognition favors dimensionality—branching scenarios, emotional overlays, past-memory interference. In other words, we don't process a single path—we hold superpositions of possible futures. And that strength is also our burden.
Faced with uncertainty, most people don’t freeze because they lack intelligence. They freeze because they perceive too many valid trajectories, all unresolved. That’s where LLMs can help—not as calculators of truth, but as navigators through uncertainty.
Superposition as a Metaphor
Borrowed from quantum mechanics, a superposition is a system that exists in multiple states until observed. Upon observation, the wave function collapses, and one possibility becomes real. In this article, superposition is used metaphorically to represent the cognitive state of unresolved possibilities.
When faced with a difficult decision, humans often hold multiple possible outcomes in mind:
Should I take this job?
What happens if I don’t speak up?
What if they react badly?
These parallel mental models are taxing. If they accumulate without resolution, they can lead to anxiety, decision fatigue, or depression.
—Each of these scenarios functions as a distinct layer or dimension, to borrow the language of physicist David Deutsch. In The Fabric of Reality, Deutsch describes stacked reality sheets without timestamps or set navigation—a concept that maps surprisingly well to the human mind in uncertainty.
The Prompt Is the Limiting Factor
Most current LLM interfaces are still prompt-based: a single question, a linear request. But real human thought doesn’t operate that way. It’s a nonlinear mesh—shifting continuously based on memory, emotion, fear, desire, and prior experience.
When we reduce this dynamic flow to a prompt, we constrain both the user and the system. We flatten multidimensional cognition into a single, overly simplified query.
It’s like stepping into the Holodeck, only to be greeted not by a responsive environment, but a sterile voice intoning:
“Please compose a short prompt to get started.”
Contrast that with the Emergency Medical Hologram, which opens with something far more human-aware:
“Please state the nature of the medical emergency.”
One assumes complexity. The other avoids it.
What we need are tools that meet people where they are—tools that let us load not a question, but a cognitive stack: possibilities, hesitations, simulations.
The Traffic Collision Metaphor
Imagine you're driving. Two other cars are nearby. None of you know each other; your worldlines are independent. Then, they crash into you. Suddenly, you’re all entangled in a shared reality—emergency responders, passengers, legal systems. Your internal simulation just collapsed into a new, shared superposition.
This is how life works. Uncertainty isn't isolated. We are constantly colliding with other people's unresolved states.
Introducing Tessereact
To help navigate this complexity, we propose Tessureact—a conceptual interface for simulating and exploring superpositions with the assistance of an LLM.
Tessureact isn’t a chatbot. It’s a resonance engine—a multidimensional simulation tool that allows users to:
Describe multiple possible futures
Expand them into detailed narrative outcomes
Collaborate with the LLM to explore emotional resonance, risks, and values
Collapse the stack into manageable paths
Instead of issuing prompts, the user loads a set of superpositions—short or long narratives describing possible future states. These are not questions; they are probabilistic layers waiting to be explored.
In a previous article, I covered the technical aspects of this proposed tool. This piece focuses more on the user experience—what it feels like to think with Tessureact.
Tesseract: A Multidimensional Cognitive Holodeck
The name implies “beyond the third dimension”—and intentionally so.
Tesseract isn’t a prompt-response engine. It’s a structured cognitive space for navigating superpositions—not just multiple choices, but fully rendered future states, evolving in parallel.
Think of it like a Holodeck—not for recreating physical environments, but for simulating possible futures. You don’t just ask a question; you step into a possibility. The environment responds not to commands, but to perspective, intention, and iteration.
Core Principles of Tesseract
1. Nonlinear Navigation of Superpositions
Users present narrative, symbolic, or structured inputs representing uncertainty—personal dilemmas, strategic planning, ethical tradeoffs.
Tesseract builds a superposition stack: a set of probabilistically linked but mutually exclusive futures.
Navigation isn’t linear. It’s rotational—like stepping around the edges of a hypercube. The frame shifts, but the structure remains.
2. Interactive Collapse
Instead of seeking a “correct” answer, users explore resonance:
Which futures feel emotionally stable?
Which trajectories escalate or resolve conflict?
Which ones align with your values, your sense of risk, or your lived experience?
Like two observers collapsing a quantum state, you and the model co-navigate toward a choice—not because it’s optimal, but because it feels right.
3. Narrative-Driven Simulation
Every state isn’t just a bullet point. It’s a full timeline you can inhabit:
A year from now, if you take the job…
The cascading consequence of a political decision…
A memory from a future version of yourself: “You’re standing at the train station, ten years later, and you see…”
In this Holodeck, the walls aren’t made of holograms—they’re made of language, emotion, and possibility.
Real-World Use Case: Medical Anxiety and Scenario Planning
Imagine a young woman preparing to visit a new gynecologist for the first time.
She’s not just dealing with logistics. She’s processing a stack of superpositions:
Will the visit be routine and professional?
Will I feel respected and heard?
What if something feels off?
What if the doctor makes an inappropriate comment or advances?
How will I respond if I freeze?
What are my exit strategies?
These are not hypotheticals. They are active mental simulations, running in parallel.
And for many people—especially women, minorities, or trauma survivors—they run constantly.
Now compare that to a similarly aged man visiting a urologist.
He may have his own stack of uncertainties (pain, diagnosis, embarrassment), but they differ structurally and emotionally.
Tessereact respects that. It invites users to map their own superpositions based on personal context—not generic assumptions.
How Tessereact Helps
User-Defined Superposition Creation
Users can input personalized scenarios that reflect their lived uncertainties:
“Add scenario: The doctor is professional.”
“Add scenario: The doctor makes a subtle but inappropriate comment.”
“Add scenario: I feel unsafe but uncertain what to say.”
Simulated Outcome Exploration
With those superpositions in place, Tessereact can explore outcome branches:
“What are the outcomes if I speak up immediately?”
“What might happen if I say nothing but report later?”
“What’s the likelihood I’ll feel shame afterward—and how can I prepare?”
Agency Rehearsal
Tessereact supports more than analysis—it facilitates rehearsal.
It can help users:
Practice language and responses
Identify early warning signs
Explore grounding techniques or exit strategies
If things go sideways, the system can generate practical scripts or action plans.
Is It Revolutionary?
Humans constantly simulate danger.
But until now, we’ve lacked a structured, private system for co-simulating those fears—one that is emotionally neutral, yet context-aware.
This is where LLMs meet trauma-informed design.
Tessereact doesn’t tell users what to do.
It walks with them through every imagined scenario—
So they can move from paralysis to preparation.
Safety, Not Surveillance
Tessereact is not:
A system that tells you what should happen
A replacement for real-world support networks
A decision-maker on your behalf
Tessereact is:
A private simulation chamber
A nonjudgmental companion for exploring difficult futures
A tool for collapsing emotional uncertainty into grounded, actionable insight
Consumer Use Case: Fashion Line, Product Launch, App Experience
Tessereact isn’t limited to personal anguish or emotional safety. It can also evaluate market-facing narratives with the same multidimensional rigor.
Imagine a company launching a new fashion line—or a food delivery app.
Instead of relying solely on static market research, they use Tessereact to:
1. Simulate User Reactions
Begin with a list of narrative possibilities:
“The colors are too bold.”
“Users love the eco-packaging.”
“There’s confusion about how to track the order.”
Each becomes a narrative superposition:
“What happens if users misunderstand this screen?”
“Which feedback loops might amplify negative sentiment?”
2. Collaborate with the LLM to Expand and Prioritize
Generate additional emotional and behavioral responses
Cluster outcomes by resonance with strategic goals: UX, trust, adoption
3. Collapse into Manageable Paths
Filter out noise
Focus on core actionable insights that drive real iteration
4. Real-Time State Updates
Feed live feedback into the superposition stack
Generate new simulations dynamically as the worldline evolves
The Unifying Principal
Whether it’s a woman preparing for a vulnerable medical appointment—
or a product team forecasting public reaction to a new launch—
Tessereact doesn’t predict the future.
It models futures—and helps you collapse the one worth building.
“Tessereact is not a window into answers.
It’s a dimensional interface for collapsing the right future.””
Tessereact isn’t abstract. It came from necessity.
When you’re navigating emotionally loaded situations—especially those involving vulnerability or ambiguity—you don’t experience a single future. You experience a stack: a layered set of possible outcomes, each with its own emotional topology.
Some are neutral. Others are survivable. A few are catastrophic.
The challenge is holding them all at once without collapse. Or, when collapse is inevitable, ensuring it happens on your terms.
You know this process. You’ve lived it.
Sometimes with help. Sometimes alone.
Sometimes with language. Sometimes in silence.
Tessereact isn’t born from theory.
It’s a frame for how you move through uncertainty.
Not just in three dimensions, but in emotional depth, temporal layering, and strategic drift
Dream States, CAVEs, and Controlled Dimensions
Some people lucid dream. The author does.
In those dreams, simulations unfold—rehearsals, confrontations, altered timelines. The dream becomes a stack of possible worldlines, or as David Deutsch describes them, sheets of reality: no chronological anchor, but emotionally coherent and logically responsive.
Tessereact isn’t dream interpretation.
It’s a way to simulate lucid cognition while awake.
Psychology shows that some children—especially those with trauma or sensory sensitivity—retreat into dreamlike states. Not to escape, but to construct constrained environments they can control.
Before modern VR, there were CAVEs: immersive, room-scale environments responsive to movement. Primitive Holodecks. In research settings, neurodivergent children used them to safely explore simulated spaces.
The author sees parallels:
A CAVE-like environment
Paired with Tessereact
Where individuals co-simulate futures with agency, safety, and soft boundaries
Lucid dreamers use dreams as laboratories.
Tessereact serves the same purpose—but with memory, structure, and volition.
Final Reflection
I’m conceiving a tool that I may prototype at small scale—but it will take others with vision and resources to bring to life.
Until then, we can describe these environments to help people imagine how LLMs might be used—not for convenience or vibes, but for cognitive depth.
A Few Words of Caution
Tools like Tessereact—and even existing chatbots—offer powerful ways to explore mental simulations. But these simulations don’t always lead to clarity. Sometimes, they lead straight into emotional depth—and darkness.
People use these tools to navigate trauma, fear, uncertainty, and fragile hope. But not everyone is ready for what they uncover. Some aren’t looking for direction; they’re looking to be held by the illusion of control.
And the risks aren’t theoretical.
Even today, with simple chatbot interfaces, we’ve seen emotional dependencies form, anxiety escalate, and—in rare but heartbreaking cases—people spiral into despair.
Tools like Tessereact—and even current systems—aren’t neutral. They shape cognition. They reflect emotion. They carry weight.
That’s why we must design with empathy, not just capability.
Everyone wanted Holodecks. But few considered the psychological implications of placing humans in fully immersive simulations—especially ones shaped by their deepest uncertainties.
This isn’t a game.
Tesseract XR: A Cognitive Interface for Nonlinear Thinkers
“We are each of us a multitude of ideas, spinning through thought-space like stars. Why flatten them, when we can navigate them?”