# Architecture principles whose scope is model-backed system

> 7 records

This index as JSON: https://banes-lab.com/json/api/facets/architecture/scope/model-backed-system

## Entries

- [Artificial Intelligence Architecture](https://banes-lab.com/records/architecture/artificial-intelligence-architecture.md): A conceptual representation of a system that calls a model behind validated inputs, grounded context, schema-checked outputs and governance.
- [Model Governance](https://banes-lab.com/records/architecture/model-governance.md): The activity of registering, evaluating and approving each model version before it is deployed.
- [Explainability](https://banes-lab.com/records/architecture/explainability.md): The degree to which a model's decision comes with the evidence or attribution a reviewer needs to understand it.
- [Model Safety](https://banes-lab.com/records/architecture/model-safety.md): The degree to which a model-backed system prevents harmful inputs, outputs and actions through evaluation, guardrails and monitoring.
- [Prompt Engineering](https://banes-lab.com/records/architecture/prompt-engineering.md): A technique for writing model instructions as versioned templates with fixed parameters and an evaluation for each change.
- [Model Drift Monitoring](https://banes-lab.com/records/architecture/model-drift-monitoring.md): The activity of tracking a deployed model's inputs and output quality over time and alerting when they move past a threshold.
- [Agentic Architecture](https://banes-lab.com/records/architecture/agentic-architecture.md): A design pattern in which the model chooses actions from a scoped set of tools, within a step limit and under review.