What is a System of Truth?
A system that preserves context, evidence, authority, decisions, and outcomes across changing tools and workflows.
Resources
Field notes for building systems of truth.
Explore the core methods behind governed industrial intelligence—from decision framing and evidence lineage to authority architecture and controlled learning.
Core reading
Architecture before automation.
The governed decision loop
Why observation, reasoning, authorization, action, and learning must form one reconstructable flow.
Capability is not authority
A practical distinction for human, workflow, and machine participation in consequential decisions.
Implementation field guide
Six questions before you begin.
01
Frame the decision
Define the decision owner, consequence, cadence, and current failure mode.
02
Bind the evidence
Identify sources, context, validity, latency, and lineage requirements.
03
Model authority
Make roles, constraints, thresholds, approvals, and escalation explicit.
04
Design the loop
Connect observation, reasoning, authorization, execution, and outcome.
05
Simulate safely
Test edge conditions, uncertainty, abstention, containment, and recovery.
06
Expand by proof
Extend to adjacent decisions only when evidence and governance hold.
Architecture notes
Reference patterns for serious operating environments.
These patterns establish a shared language for discussing evidence, decision rights, reasoning boundaries, and lifecycle control with operational, engineering, security, digital, and executive teams.
A
Evidence lineage
Source, transformation, context, identity, version, assumption, and outcome.
B
Delegation envelope
Purpose, scope, permission, threshold, escalation, expiry, and recovery.
C
Replay record
The minimum evidence needed to reconstruct and challenge a decision.
Start with consequence
Turn the field guide into a first decision architecture.
Choose a decision where fragmented evidence, unclear authority, or slow coordination materially affects the outcome.
Start the conversation