Knowledge Graph

FDE / IRE Enterprise Skills, Lifecycle, Capability, and Provenance Ontology

Base IRI: https://x.com/kidehen/status/2055725483535282591#

Lifecycle Governance · PROV-O Provenance · 9 AI Literacy Skills
FDE IRE Skill Engineering AI Literacy PROV-O
SPARQL GRAPH: DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl

Overview

AI-native enterprises require explicit skill governance — replacing undocumented tribal knowledge with composable execution units tracked through a lifecycle and provenance model.

The ontology defines a structured role model with two primary roles: Forward Deployed Engineers and Inward Redeployed Engineers. Both are subtypes of EngineeringRole.

Core Role Model

Forward Deployed Engineer FDE

Outward-facing role embedded in customer environments to deploy and adapt AI systems in real-world contexts.

Required Skills:

Inward Redeployed Engineer IRE

Inward-facing role focused on extracting tacit knowledge and transforming it into structured, reusable, AI-executable skills.

Required Skills:

AI Literacy Skill Hierarchy

The AILiteracySkill defines 9 core capabilities required to build, operate, and govern AI systems.

#SkillDefinition
1LLM MasteryMastery of frontier LLMs across vendors. Without this, AI systems become opaque black boxes instead of controllable reasoning systems.
2AI Agent EngineeringDesign of modular agents composed of skills and tools. Enables transition from prompt-based usage to autonomous, composable AI systems.
3Skill EngineeringDesign of reusable skills decoupled from tools and data spaces. Transforms tribal knowledge into reusable enterprise execution units.
4Data Space Tooling (CRUD)Building tools for CRUD operations across data spaces. Without this, AI cannot act on real enterprise data systems.
5API Interoperability (OpenAPI + MCP)Design and consumption of interoperable APIs. Provides the connective tissue enabling cross-system AI orchestration.
6HTTP Protocol MasteryDeep understanding of HTTP semantics and distributed communication. HTTP is the universal transport layer for AI-enabled distributed systems.
7Linked Data & Semantic WebModeling structured knowledge using RDF and semantic graphs. Enables machine-readable enterprise knowledge and cross-domain reasoning.
8Data Access ProtocolsDatabase connectivity via ODBC, JDBC, and equivalents. Ensures AI systems can access complete enterprise datasets rather than fragments.
9Declarative Query LanguagesMastery of SQL, SPARQL, GraphQL, GQL, openCypher. Enables structured retrieval of truth from heterogeneous enterprise data systems.

Lifecycle Model

Every Skill transitions through states tracked via hasLifecycleState:

Provenance Model

SkillGenerationActivity captures how tacit knowledge transforms into structured skill artifacts using PROV-O.

Instance Examples

SPARQL Query Examples

Each query is a live executable schema:SoftwareSourceCode entity with a [Run Query] link to the URIBurner SPARQL endpoint. SPARQL GRAPH: DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl

1
Retrieves all ontology classes with subclass counts

Query 1 retrieves all ontology classes with subclass counts, ordered by hierarchy depth.

# Show all ontology classes with subclass counts PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX owl: <http://www.w3.org/2002/07/owl#> FROM <https://linkeddata.uriburner.com/DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl> SELECT ?class (COUNT(?sub) AS ?subclassCount) WHERE { ?class a owl:Class . OPTIONAL { ?sub rdfs:subClassOf ?class } } GROUP BY ?class ORDER BY DESC(?subclassCount)
▶ Run Query
2
Get all skills with lifecycle states ordered by lifecycle stage

Query 2 gets all skills with their lifecycle states.

# Get all skills with lifecycle states PREFIX : <https://x.com/kidehen/status/2055725483535282591#> PREFIX schema: <http://schema.org/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> FROM <https://linkeddata.uriburner.com/DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl> SELECT ?skill ?label ?lifecycle WHERE { ?skill a :Skill ; rdfs:label ?label ; :hasLifecycleState ?lifecycleState . ?lifecycleState rdfs:label ?lifecycle . } ORDER BY ?lifecycle ?label
▶ Run Query
3
Get FDE role with its skill requirements

Query 3 gets the FDE role with its required skills.

# Get FDE role with its skill requirements PREFIX : <https://x.com/kidehen/status/2055725483535282591#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> FROM <https://linkeddata.uriburner.com/DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl> SELECT ?role ?roleLabel ?skill ?skillLabel WHERE { ?role a :ForwardDeployedEngineer ; rdfs:label ?roleLabel ; :requiresSkill ?skill . ?skill rdfs:label ?skillLabel . } ORDER BY ?roleLabel ?skillLabel
▶ Run Query
4
Get IRE role with its skill requirements

Query 4 gets the IRE role with its required skills.

# Get IRE role with its skill requirements PREFIX : <https://x.com/kidehen/status/2055725483535282591#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> FROM <https://linkeddata.uriburner.com/DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl> SELECT ?role ?roleLabel ?skill ?skillLabel WHERE { ?role a :InwardRedeployedEngineer ; rdfs:label ?roleLabel ; :requiresSkill ?skill . ?skill rdfs:label ?skillLabel . } ORDER BY ?roleLabel ?skillLabel
▶ Run Query
5
Get all people with their roles and skills

Query 5 gets all people with their roles and skills.

# Get all people with their roles and skills PREFIX : <https://x.com/kidehen/status/2055725483535282591#> PREFIX schema: <http://schema.org/> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> FROM <https://linkeddata.uriburner.com/DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl> SELECT ?person ?name ?role ?roleLabel ?skill ?skillLabel WHERE { ?person a schema:Person ; schema:name ?name ; a ?role . ?role rdfs:subClassOf :EngineeringRole . OPTIONAL { ?person :hasSkill ?skill . ?skill rdfs:label ?skillLabel . } } ORDER BY ?name ?roleLabel
▶ Run Query
6
Get provenance chain: activity -> agent -> skill -> lifecycle

Query 6 traces the provenance chain from activity to agent to skill to lifecycle.

# Get provenance chain: activity -> agent -> skill -> lifecycle PREFIX : <https://x.com/kidehen/status/2055725483535282591#> PREFIX prov: <http://www.w3.org/ns/prov#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> FROM <https://linkeddata.uriburner.com/DAV/demos/daas/ire-fde-ontology-minimax_m2.5free-1.ttl> SELECT ?activity ?activityLabel ?agent ?agentLabel ?skill ?skillLabel ?lifecycle WHERE { ?activity a :SkillGenerationActivity ; rdfs:label ?activityLabel ; prov:wasAssociatedWith ?agent . ?agent rdfs:label ?agentLabel . ?skill prov:wasGeneratedBy ?activity ; rdfs:label ?skillLabel ; :hasLifecycleState ?lifecycleState . ?lifecycleState rdfs:label ?lifecycle . } ORDER BY ?activityLabel
▶ Run Query

FAQ

Forward Deployed Engineers (FDEs) are outward-facing — embedded in customer environments to deploy and adapt AI systems. Inward Redeployed Engineers (IREs) are inward-facing — focused on extracting tacit knowledge and transforming it into structured, reusable, AI-executable skills.

AILiteracySkill defines the nine core capabilities required to build, operate, and govern AI systems.

The SkillGenerationActivity uses PROV-O to model how tacit knowledge becomes structured skill artifacts.

Glossary

EngineeringRole

A structured enterprise role responsible for engineering work across internal or external system boundaries.

ForwardDeployedEngineer

An outward-facing engineering role embedded in customer environments.

InwardRedeployedEngineer

An inward-facing engineering role focused on extracting tacit knowledge.

Skill

A reusable, structured unit of operational capability executable by humans or AI agents.

AILiteracySkill

Core capabilities required to build, operate, and govern AI systems.

hasLifecycleState

Property linking a Skill to its current lifecycle state.

SkillGenerationActivity

An activity that transforms tacit knowledge into structured skill artifacts.

requiresSkill

Property linking an EngineeringRole to the Skill it requires.

hasSkill

Property linking a Person to the Skill they possess.

PROV-O

W3C Provenance Ontology for modeling provenance information.

Knowledge Graph Explorer

Interactive visualization of entities and relationships. Click nodes to open in URIBurner resolver, drag to reposition.

About This Page

This knowledge graph overview was generated by querying the URIBurner SPARQL endpoint for the named graph. The original document was transformed into RDF using kg-generator skill, then uploaded to the Virtuoso-based URIBurner server.

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