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Information

How does recorded data become structured, interpretable fact?

Schemas, statements, and triples (subject, predicate, object) — structuring data into facts without mistaking capture for synthesis.

15 published articles

From Synthesizing Knowledge
00
Synthesizing Knowledge
Series preview — how explicit information becomes something we can act on
From Genesis
03
Capturing Truth — and the Schema-Evolution Myth
How truth gets into a system in the first place, and why doing it wrong shows up as schema churn
08
Thinking by Writing
Decision as emission — why humans and machines both reason in symbols, and why capture is not the same for each
09
The Moment of Commitment
Where derivations become decisions and accountability crystallises
11
When Facts Are Wrong
Corrections, amendments, and compensating transactions
14
Why Atomicity Matters
How far an artifact sits from the irreducible — and why that governs what may depend on it
15
Why Uncertainty Matters
How confidently an artifact reflects the truth — at the moment you actually use it
17
The Facets Composed
Six orthogonal facets, one question: how much may I trust this?
18
What Information Theory Says
The formal underpinning of the facets
27
One Authority Per Invariant
The principle that makes distributed systems consistent makes organisations accountable
28
Enforcing Invariants Without Locks
Partition writes to single authorities — coordinate at routing, not at commit
29
One Authority Per Invariant — At Scale
How the single writer principle applies when multiple product teams share cross-cutting obligations
30
LLMs at the Commitment Boundary
Classifying every meaningful LLM variant — and why the harness, not the model, sets the trust
31
Event Sourced Science
Why the ML reproducibility crisis is an architecture problem
34
The Unified Theory
One problem. One axiom. Six facets. Zero coincidences.