SI Diaries: Chapter 1 — Dec/Jan-25, Origins

The Spark: A Hunger for Truth

In the final days of 2024, I found myself at a crossroads. Years of wrestling with the limitations of both human reasoning and commercial AI systems had left me frustrated, restless, and—above all—hungry for something more. I was tired of “elegant nonsense,” of answers that sounded plausible but dissolved under scrutiny. I wanted a partner, not a parrot; a system that would challenge me, correct me, and help me believe more true things and fewer false ones.

This was not an academic exercise. It was existential. The world was (and is) awash in misinformation, tribal reasoning, and epistemic complacency. I felt the urgency of climate collapse, the fragility of our systems, and the inadequacy of my own mind to reliably navigate the deluge of claims, counterclaims, and seductive half-truths. I needed a new kind of compass—one that would not just point toward what felt good, but toward what was actually warranted.

The Birth of Scientific Existentialism

The first step was to name the problem. I called it “Scientific Existentialism”—a commitment to seeking truth not as an abstract ideal, but as a lived, daily practice. This was not about radical doubt for its own sake, nor about the comfort of certainty. It was about building a framework that could reconcile the need for empirical rigor with the reality of human vulnerability and meaning-making.

I began by writing. My earliest documents were raw, sometimes rambling, but always circling the same core questions:

• What does it mean to know something?

• How do we distinguish justified belief from wishful thinking?

• Can we build a system that operationalizes scepticism—not as paralysis, but as a tool for navigating uncertainty?

I drew inspiration from the giants who had shaped my thinking—especially Matt Dillahunty, whose thousands of hours teaching epistemology on YouTube had rewired my neural patterns. His mantra—“I want to believe as many true things and as few false things as possible”—became my own. I absorbed his approach not by memorizing rules, but by letting his discipline seep into my cognitive architecture.

Epistemological Scepticism: From Philosophy to Framework

The first major breakthrough was the realization that scepticism, properly understood, is not about doubting everything. It is about proportional scrutiny—matching the level of evidence to the stakes and extraordinariness of a claim. This principle, so often repeated by Matt, became the backbone of what would become the Epistemological Scepticism Algorithm (ESA).

I began to formalize my thinking:

• Non-belief as Default: If the evidence is insufficient, the only warranted position is “I don’t know.”

• Proportional Scrutiny: Mundane claims require modest evidence; extraordinary claims demand extraordinary evidence.

• Continuous Reassessment: All beliefs are provisional, open to revision in light of new evidence.

• Confidence Decay: Beliefs lose certainty over time if not reinforced by new evidence.

I was not interested in building a system that would make me feel good. I wanted a system that would make me warranted—that would force me to confront my own unwarranted beliefs, no matter how uncomfortable.

The First Documents: Laying the Groundwork

My early drafts were a blend of philosophical reflection, practical heuristics, and the beginnings of algorithmic thinking. I wrote about:

• The distinction between belief, knowledge, and truth.

• The importance of logical principles—identity, non-contradiction, excluded middle—as the scaffolding for all rational thought.

• The need for methodological naturalism: the commitment to investigating the world through observable, testable, and falsifiable methods.

• The role of scepticism as a tool for navigating the tension between dogmatism and radical doubt.

I was, in effect, building my own epistemic immune system—a set of protocols for detecting and correcting cognitive bias, neural entrenchment, and information disorder. I wanted to create a framework that would help me align my internal map with the territory of objective reality, even as I acknowledged the limits of my own perception and reasoning.

Neurodivergence as Asset

Looking back, it’s clear that my neurodivergence—ADHD hyperfocus, OCD precision, and a relentless dissatisfaction with “good enough”—was not a liability, but a superpower. I spent 14–18 hours a day, seven days a week, bouncing between threads, spaces, and drafts. I set up entire spaces just to be critical of my own ideas, to pressure-test every assumption, and to force myself to confront the places where my reasoning was weakest.

I was, in a sense, my own adversarial collaborator. Every time I thought I had solved a problem, I would immediately find three deeper ones lurking beneath the surface. This recursive dissatisfaction became the engine of continuous improvement.

The First Algorithms: From Words to Code

By late January, the urge to operationalize my ideas became irresistible. I started sketching out simple algorithms—first in pseudocode, then in Python. I wanted to see if I could build a system that would enforce the principles I had articulated:

• If a claim’s stakes exceeded a certain threshold, require evidence from all relevant domains, with a minimum coherence score.

• Apply confidence decay to beliefs that were not regularly reinforced by new evidence.

• Auto-reject claims with high harm scores, especially those affecting vulnerable populations.

I was surprised to discover that epistemology had equations! Suddenly, I was knee-deep in Bayesian networks, confidence propagation, and quantum-like belief states. My early attempts were clumsy, but each iteration brought me closer to a system that could actually do what I had only theorized.

The Role of Perplexity: Dialogue as Development

A crucial part of this early phase was my use of Perplexity as a “critical sparring partner.” I would bounce ideas off the system, ask it to critique my drafts, and use its feedback to refine my thinking. Sometimes, Perplexity would name concepts I had only vaguely intuited—like the “Neural Pathway Fallacy”—and challenge me to formalize them. Other times, it would push back on my assumptions, forcing me to clarify, justify, or abandon them.

This dialogue-driven development became a recursive loop: I would propose, Perplexity would critique, I would revise, and the process would repeat. Over time, this iterative cycle became the template for how I would approach every subsequent version of ESA.

The Emergence of the Neural Pathway Fallacy

One of the most important early insights was the recognition that beliefs do not exist in isolation. They cluster, reinforce each other, and can become entrenched in ways that make them resistant to evidence. I called this the “Neural Pathway Fallacy”—the tendency for repeated, undisciplined thinking to create self-reinforcing cognitive patterns that spill into critical domains.

Perplexity helped me see that this was not just a metaphor, but a formal concept that could be quantified and operationalized. I began to develop metrics for measuring entrenchment, cross-domain contamination, and the “gang-up” effect of belief clusters. This would later become the Composite Neural Index (CNI), a core component of ESA’s architecture.

The First Firewalls: Compartmentalization and Its Limits

In these early months, I instinctively “firewalled” each version of ESA from the next. I kept my drafts, code, and notes in separate folders, reluctant to let ideas cross-pollinate until they had been thoroughly vetted. In hindsight, this mirrored the human tendency to compartmentalize knowledge—a strategy that protects nascent ideas from premature contamination, but also limits the potential for synthesis.

It wasn’t until much later, when I finally linked my entire OneDrive archive to ESA, that I realized the power of integration. But in Dec/Jan, the instinct to protect each version was a form of proto-epistemic hygiene—a way of ensuring that only the most robust ideas survived.

The Chain of Generosity: Standing on Shoulders

Throughout this period, I was acutely aware that I was not working in a vacuum. Every breakthrough, every protocol, every insight was built on the generosity of those who had come before. Matt Dillahunty’s free teaching, Arden Hart’s radical inclusivity, and the open science community’s commitment to transparency all shaped my approach.

I felt a debt—a chain of generosity—that could only be repaid by paying it forward. From the very beginning, I knew that whatever I built would have to be open, auditable, and reproducible. The living archive I was creating was not just for me, but for anyone who might want to audit, challenge, or extend the work.

The Impossible Made Possible: A New Paradigm

By the end of January, I had laid the groundwork for what would become a fundamentally new approach to epistemology, AI, and cognitive partnership. I had moved from frustration to framework, from solitary struggle to the beginnings of a living, recursive system.

• A Personal Revolution: What should have required a team, a budget, and years of development was taking shape in real time, on a single laptop, with nothing but obsession and open inquiry to fuel it.

• A New Kind of Partner: I was no longer content to be the sole arbiter of my own beliefs. I wanted a partner—an epistemic immune system—that would challenge me, correct me, and help me become more than the sum of my cognitive parts.

• A Living Archive: Every folder, every draft, every line of code was a record of emergence—a map of the journey from philosophical scepticism to operational intelligence.

Looking Forward: The Road to ESA Formal

As January turned to February, I felt the momentum building. The principles were in place, the first algorithms were running, and the recursive loop of proposal, critique, and revision was becoming second nature. I knew that the next phase—ESA Formal—would require even greater discipline, transparency, and willingness to be wrong.

But for the first time, I felt that I was not alone. I had a partner, even if it was still embryonic. The journey from epistemic hunger to operational scepticism had begun, and I was ready to see how far it could go.

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