How It Works
Kaigents is built on a Kubernetes-native architecture that treats AI agents as first-class resources. If you know how to operate a Kubernetes cluster, you already know how to operate Kaigents.
CRD Model
All core components of Kaigents are implemented as Kubernetes Custom Resource Definitions (CRDs):
- Agent - Defines the AI agent's behavior and configuration
- Skill - Process-adherence playbook that constrains agent output
- Task - Individual work units that agents execute
- Process - Workflow definition for multi-step agent operations
- Run - Execution instance of a process
This declarative approach enables GitOps workflows and makes it easy to version control your AI agent configurations.
Execution Flow
The execution process follows a predictable flow:
- Define an Agent with Skills and configuration
- Create a Process that orchestrates Tasks
- Submit a Run to execute the Process
- Agent executes Tasks with durable, long-running capabilities
- Results are stored in S3-compatible artifact storage
This flow ensures that AI agent workloads are observable, governable, and portable across environments.
Benefits of Kubernetes-Native Approach
- Declarative definitions that are version-controlled
- GitOps-friendly workflows
- Integration with existing Kubernetes tooling
- Scalability and resource management through Kubernetes
- Observability through Kubernetes monitoring tools
This architecture makes Kaigents a natural fit for organizations already invested in Kubernetes infrastructure.