Runtime Agent¶
Introduction¶
A Runtime Agent enables Artificial Intelligence to collaborate with an Engineering Runtime.
Rather than executing engineering operations directly, the Runtime Agent translates engineering intent into deterministic runtime requests.
This separation allows organizations to adopt any AI system while maintaining a consistent engineering execution platform.
Responsibilities¶
The Runtime Agent and Engineering Runtime have different responsibilities.
Runtime Agent¶
Responsible for:
- Understanding engineering intent
- Discovering Capability Packages
- Resolving capabilities from the Capability Registry
- Selecting the appropriate capability
- Building runtime requests
The Runtime Agent does not perform engineering execution.
Engineering Runtime¶
Responsible for:
- Bootstrap
- Authentication
- Runtime Context Resolution
- Policy Evaluation
- Deterministic Execution
- Audit
The Engineering Runtime performs engineering operations regardless of which Runtime Agent initiated the request.
Execution Model¶
Engineer
↓
Natural Language
↓
Runtime Agent
Understand Intent
↓
Discover Capability Packages
↓
Resolve Capability
↓
Engineering Runtime
Bootstrap
Authentication
Runtime Context
Policy
Execution
Audit
↓
Engineering Platforms
Runtime Independence¶
Engineering Runtime remains independent of AI providers.
Runtime Agents can be implemented for:
- Claude
- ChatGPT
- Gemini
- GitHub Copilot
- Cursor
- Enterprise AI Platforms
- Future AI Systems
Regardless of the provider, every Runtime Agent communicates with the same Engineering Runtime.
Capability Discovery¶
Runtime Agents discover engineering capabilities through the Capability Registry.
Rather than embedding engineering knowledge inside prompts, Runtime Agents load published Capability Packages.
This keeps engineering knowledge synchronized with Runtime releases while allowing capabilities to evolve independently.
Local Development¶
Engineer
↓
Engineering Runtime
No Runtime Agent required.
CI/CD¶
Pipeline
↓
Engineering Runtime
No Runtime Agent required.
AI-Assisted Engineering¶
Engineer
↓
Runtime Agent
↓
Engineering Runtime
The Runtime Agent becomes another engineering consumer of the Engineering Runtime.
Design Principles¶
Runtime Agents understand engineering intent.
Capability Packages define reusable engineering capabilities.
Capability Registry enables capability discovery.
Engineering Runtime performs deterministic execution.
Engineering Platforms perform engineering work.
Benefits¶
Separating Runtime Agents from Engineering Runtime provides:
- AI independence
- Vendor independence
- Enterprise governance
- Deterministic execution
- Consistent engineering workflows
- Easier AI adoption
- Lower migration cost
Reference contract¶
A dedicated Runtime Agent contract for AI coding agents (Claude, Cursor, and similar) lives in the engineering-runtime-ai-agent repository: human-readable rules plus hooks that restrict shell execution to the runtime binary so engineering work cannot bypass the Engineering Runtime.
Looking Ahead¶
As AI systems continue to evolve, Runtime Agents can be added or replaced without changing the Engineering Runtime.
This allows organizations to adopt new AI technologies while preserving a stable engineering execution platform.
Conclusion¶
A Runtime Agent should be viewed as an intelligent engineering interface rather than an execution platform.
Its responsibility is to understand engineering intent and collaborate with the Engineering Runtime.
The Engineering Runtime remains responsible for authentication, runtime context, policy evaluation, deterministic execution and auditing.
This separation enables humans, CI/CD pipelines and AI systems to share the same governed engineering execution model.