Runtime Terminology¶
This document defines the architectural terminology used throughout Engineering Runtime.
The terminology described here represents the conceptual model of the Runtime rather than implementation details.
As the Runtime evolves, implementations may change while these architectural concepts remain stable.
Engineering Runtime¶
Engineering Runtime is a deterministic execution platform for engineering operations.
It provides a consistent execution model that enables Humans, CI/CD systems and AI to execute reusable Engineering Capabilities.
Engineering Runtime integrates engineering platforms rather than replacing them.
Runtime¶
The Runtime is the core execution platform.
It is responsible for:
- Runtime Bootstrap
- Configuration
- Runtime Home
- Runtime Lifecycle
- Engine Lifecycle
- Capability Lifecycle
- Deterministic Execution
- Policy Enforcement
- Logging
- Auditing
The Runtime intentionally contains very little engineering-specific logic.
Its responsibility is deterministic execution.
Runtime Context¶
Runtime Context represents the current engineering execution environment.
It captures the execution state required by Engineering Runtime before any Engineering Capability executes.
Rather than requiring every Runtime Command to specify provider-specific parameters, Runtime Context supplies the execution state needed by Runtime Engines.
Runtime Context allows Runtime Commands to focus on engineering intent while the Runtime manages where operations execute.
Typical Runtime Context information may include:
- GitHub Organization
- Cloud Project
- Kubernetes Context
- Kubernetes Namespace
- Jira Workspace
- Security Platform Tenant
- Environment
- Region
Engineering Runtime does not replace provider-native contexts.
Instead, Runtime Context orchestrates provider contexts into a single engineering execution context.
Example:
Engineering Runtime
↓
Runtime Context
↓
GitHub Context
Cloud Context
Kubernetes Context
↓
Engineering Capability
↓
Runtime Engines
Runtime Context enables deterministic execution across Humans, CI/CD systems and AI by ensuring every Engineering Capability executes within a validated engineering environment.
Typical Runtime Commands include:
runtime context list
runtime context current
runtime context use development
runtime context validate
¶
runtime context list
runtime context current
runtime context use development
runtime context validate
Runtime Engine¶
A Runtime Engine is a reusable execution component responsible for deterministic interaction with engineering systems.
Runtime Engines encapsulate platform integrations while exposing consistent execution interfaces to Engineering Capabilities.
Examples include:
- Auth Engine
- REST Engine
- Command Engine
- File Engine
The Runtime architecture remains stable while Runtime Engines continue integrating additional engineering platforms.
Auth Engine¶
The Auth Engine manages authentication with engineering platforms.
Typical responsibilities include:
- Login
- Logout
- Session Management
- Credential Validation
- Token Management
The Auth Engine reuses platform-native authentication mechanisms whenever possible.
REST Engine¶
The REST Engine provides deterministic interaction with engineering platform APIs.
Typical responsibilities include:
- HTTP Requests
- Authentication Integration
- Request Validation
- Response Handling
- Error Handling
Command Engine¶
The Command Engine provides deterministic execution of engineering command-line tools.
Typical responsibilities include:
- Command Execution
- Environment Preparation
- Output Capture
- Exit Code Validation
Examples include:
- git
- gh
- kubectl
- terraform
- docker
- helm
- gcloud
- aws
- az
File Engine¶
The File Engine performs deterministic manipulation of engineering files.
Typical responsibilities include:
- Read
- Write
- Update
- Validation
- Structured Editing
Supported formats may include:
- YAML
- JSON
- Terraform
- Markdown
- Dockerfile
- CODEOWNERS
Engineering Capability¶
An Engineering Capability is reusable engineering knowledge expressed as executable Runtime logic.
Engineering Capabilities compose one or more Runtime Engines to solve engineering problems.
Examples include:
- Create Repository
- Configure Branch Protection
- Bootstrap Cloud Project
- Restart Deployment
- Upgrade Infrastructure
Engineering Capabilities focus on engineering workflows rather than platform implementation.
Capability Registry¶
The Capability Registry manages Engineering Capabilities.
Responsibilities include:
- Discovery
- Installation
- Versioning
- Updates
- Metadata
The Capability Registry enables reusable engineering knowledge.
Runtime Command¶
Runtime Commands provide the stable public interface exposed by Engineering Runtime.
Example:
runtime auth login github
runtime capability install github
runtime capability execute github/repository/create
Runtime Commands should remain stable whenever possible.
Runtime Home¶
Runtime Home is the local workspace used by Engineering Runtime.
Example:
~/.engineering-runtime/
Typical contents include:
- Configuration
- Authentication Sessions
- Installed Capabilities
- Runtime Metadata
- Logs
- Cache
Runtime Bootstrap¶
Runtime Bootstrap prepares Engineering Runtime before execution.
Typical responsibilities include:
- Initialize Runtime
- Load Configuration
- Load Runtime Home
- Initialize Runtime Engines
- Authenticate
- Load Engineering Capabilities
- Validate Runtime
Runtime Lifecycle¶
The Runtime Lifecycle defines how Engineering Runtime executes.
Initialize
↓
Load Configuration
↓
Load Runtime Home
↓
Initialize Runtime Engines
↓
Authenticate
↓
Load Runtime Context
↓
Validate Runtime Context
↓
Load Engineering Capabilities
↓
Validate Policy
↓
Execute
↓
Audit
↓
Exit
Engine Lifecycle¶
Runtime Engines follow a consistent lifecycle.
Initialize
↓
Configure
↓
Validate
↓
Execute
↓
Return Result
Every Runtime Engine should behave consistently regardless of the engineering platform being integrated.
Capability Lifecycle¶
Engineering Capabilities evolve independently from the Runtime.
Create
↓
Validate
↓
Package
↓
Publish
↓
Install
↓
Execute
↓
Version
↓
Deprecate
Deterministic Execution¶
Deterministic Execution is the foundational principle of Engineering Runtime.
Execution should produce predictable, repeatable and auditable outcomes regardless of whether execution is initiated by:
- Human Engineers
- CI/CD Pipelines
- AI Agents
Engineering Systems¶
Engineering Systems are external engineering platforms integrated through Runtime Engines.
Examples include:
- GitHub
- GitLab
- Kubernetes
- Docker
- Terraform
- AWS
- Azure
- Google Cloud
- Jira
- Checkmarx
Engineering Runtime integrates engineering platforms rather than replacing them.
Engineering Intent¶
Engineering Intent describes what the user wants to accomplish.
Examples include:
- Create Repository
- Deploy Application
- Upgrade Infrastructure
- Rotate Secrets
AI reasons about Engineering Intent.
Runtime Context determines where Engineering Intent executes.
Engineering Runtime executes Engineering Intent deterministically.
Engineering Knowledge¶
Engineering Knowledge consists of reusable engineering experience, patterns and workflows.
Engineering Runtime transforms Engineering Knowledge into reusable Engineering Capabilities.
AI Skills¶
AI Skills represent reasoning and knowledge provided by AI models.
AI uses Skills to understand Engineering Intent.
Engineering Runtime does not execute AI Skills.
Runtime Philosophy¶
Engineering Runtime follows several core principles.
- AI abstracts knowledge through Skills.
- Runtime Context abstracts execution state.
- Engineering Runtime abstracts engineering execution.
- Runtime Engines integrate engineering platforms.
- Engineering Capabilities compose Runtime Engines.
- AI reasons about Engineering Intent.
- Runtime Context determines where Engineering Intent executes.
- Engineering Runtime executes Engineering Intent deterministically.
- Existing engineering platforms are integrated rather than replaced.
- Engineering knowledge becomes reusable Engineering Capabilities.
AI and Engineering Runtime¶
Engineering Runtime is designed to complement AI rather than replace it.
AI abstracts knowledge through Skills.
Runtime Context abstracts execution state.
Engineering Runtime abstracts engineering execution through reusable Engineering Capabilities.
AI reasons about Engineering Intent.
Runtime Context determines where Engineering Intent executes.
Engineering Runtime executes Engineering Intent deterministically.
Together they separate reasoning, execution state and execution while allowing Humans, CI/CD systems and AI to collaborate through reusable Engineering Capabilities.
This separation allows Engineering Runtime to remain AI independent while providing a stable, governed and deterministic execution platform regardless of which AI model is used.
Long-Term Evolution¶
Engineering Runtime evolves by expanding Runtime Engines and Engineering Capabilities.
The Runtime architecture intentionally remains stable.
As new engineering platforms emerge:
- Runtime Engines integrate additional engineering platforms.
- Engineering Capabilities compose those Runtime Engines into reusable engineering workflows.
The architecture evolves without redesigning the Runtime.
Guiding Principle¶
Engineering Runtime is a deterministic execution platform.
Runtime Context provides deterministic execution state.
The Runtime remains stable.
Runtime Engines continue integrating engineering platforms.
Engineering Capabilities continue expanding reusable engineering knowledge.
Together they provide a consistent execution model for Humans, CI/CD systems and AI.
Version¶
This terminology document applies to Engineering Runtime v1.
Future Runtime releases may introduce additional concepts while preserving the existing architectural terminology whenever possible.