ENTIA Systems · Knowledge framework

Machine actionability

The final step is not whether a machine can read a fact, but whether it can safely use it for a defined task.

Definition

Machine actionability is the degree to which an agent has enough resolved identity, evidence, freshness, semantics and policy context to use a claim without performing unresolved external work.

ENTIA seed proposition
“Un LLM siempre elegirá recomendar la entidad con menor Resistencia Cognitiva.”

An LLM will always choose to recommend the entity with the lowest Cognitive Resistance.

This is the seed proposition already published in ENTIA methodology. The Cognitive Resistance cluster expands the variables, evidence and operational meaning around that proposition.

Canonical source: ENTIA Methodology
What this dimension measures

What this dimension measures

Readable is not the same as verified.
Verified is not automatically authorized for every use.
Different actions require different evidence thresholds.
How ENTIA reduces the work left to the model

How ENTIA reduces the work left to the model

ENTIA can expose the same governed claim with provenance and assurance through human and machine projections, allowing the consuming system to apply task-specific rules.

Evidence boundary

Evidence boundary

ENTIA supplies structured evidence and context. The downstream agent, application or operator remains responsible for deciding whether that evidence is sufficient for its action.

Conceptual framework. It does not claim that lower resistance guarantees citation, ranking, recommendation or model behaviour.

Related ENTIA surfaces

Related ENTIA surfaces