Reference

The vocabulary and mental models behind IKE.

A concise reference for the terms, distinctions, and explanation frames that make Intentional Knowledge Engineering easier to teach and remember.

Glossary

Core terms

IKE needs a small, consistent vocabulary because it is naming a practice most organizations perform only accidentally.

IKE

Intentional Knowledge Engineering. The practice of intentionally designing and operating organizational knowledge systems.

IKS

Intentional Knowledge System. The instantiated operational system produced through IKE practices.

IKO

Intentional Knowledge Operations. The ongoing work of creating, reconciling, validating, curating, and evolving organizational knowledge.

Knowledge Layer

The collective operational understanding of an organization across humans, systems, documentation, processes, and AI agents.

Knowledge Drift

The inevitable divergence of operational understanding from operational reality over time.

Knowledge Object

A bounded, reusable artifact tied to a process, asset, role, decision, failure mode, or operating condition.

Frameworks

Reusable mental models for understanding IKE.

These frames help distinguish IKE from ordinary documentation, knowledge capture, AI retrieval, and dependence on tribal memory.

Memory

Tribal vs intentional

Expert knowledge is valuable. The problem is unstructured dependence on individual memory.

Practice

Tacit to operationalized

Knowledge moves from hidden practice to captured artifact to validated object to operational use.

Artifact

Event to knowledge object

Incidents, startups, shutdowns, and handovers become reusable knowledge instead of fading into conversation.

Flow

Accidental vs intentional flow

The same event can become memory loss or organizational learning depending on how it is handled.

Layer

Knowledge Layer map

People, systems, docs, histories, processes, and AI form one operational understanding layer.

Correction

Drift and reconciliation

Knowledge is not kept true by storage. It is kept true by recurring correction against reality.

Short statements

  • Tribal knowledge does not scale. Intentional knowledge does.
  • Organizations already have a knowledge system. Most are accidental.
  • AI readiness begins with intentional knowledge.
  • Knowledge Drift is inevitable. Reconciliation must be intentional.
  • Knowledge is infrastructure.

Archive boundary

IKE evolved from earlier KOL, KOR, and KOS language. Those materials are historical source material. Public IKE content should translate durable ideas into IKE vocabulary instead of presenting the older project names as the current framework.