Intelligence and AI

How do we reason reliably from knowledge?

Human, machine, and collaborative intelligence — what AI can and cannot do, and what structure enables trustworthy reasoning.

12 published articles

From Enabling Intelligence

Enabling Intelligence

Series preview — reasoning reliably from knowledge under uncertainty

From Genesis

Thinking by Writing

Decision as emission — why humans and machines both reason in symbols, and why capture is not the same for each

Every Statement Has a Tier

Tracking the strength of a claim is a commitment to truth, not a claim to certainty

The Epistemic Ladder

Fourteen levels from the Real to the refuted claim — and the rules for climbing honestly

When the Commitment Boundary Needs Reinforcing

Severity, task nature, and who is affected

Strengthening the Commitment Boundary

Challenge, calibration, and independent review at the bind

Meritocracy — The Sweet Spot

Where quality meets legitimacy — and why it has been so hard to build

Enforcing Invariants Without Locks

Partition writes to single authorities — coordinate at routing, not at commit

One Authority Per Invariant — At Scale

How the single writer principle applies when multiple product teams share cross-cutting obligations

LLMs at the Commitment Boundary

Classifying every meaningful LLM variant — and why the harness, not the model, sets the trust

The Unified Theory

One problem. One axiom. Six facets. Zero coincidences.

What this opens — biases, dispositions, and AI in service of truth under uncertainty