Cluster
Trust
The trust cluster covers principles that build user confidence through inspectability, progressive disclosure of system agency, and explicit handling of hand-offs, approvals, and blockers.
Key Facts
- Cluster
- Trust
- Principles
- 3
- Linked examples
- 6 implementation library examples
- Principle titles
- Apply progressive disclosure to system agency; Establish trust through inspectability; Make hand-offs, approvals, and blockers explicit
Principles in this cluster
- Principle 4Apply progressive disclosure to system agencyProvide the minimum information necessary by default, while enabling users to inspect additional detail when confidence, understanding, or intervention is required.Different users, and the same user in different contexts, require different levels of transparency. The default experience should remain clear and efficient, while deeper inspection should remain available when justified.
- Principle 7Establish trust through inspectabilityUsers should be able to examine how a result was produced when confidence, accountability, or decision quality is important.Trust is not established through assertion alone. It is established by enabling proportionate verification. Particularly in high-impact contexts, users must be able to inspect evidence, actions, and changes.
- Principle 8Make hand-offs, approvals, and blockers explicitWhen the system cannot proceed, the reason should be immediately visible, along with any action required from the user or another dependency.In agentic systems, failure frequently arises not from incorrect reasoning but from unclear responsibility. Users must know when a task is paused, why it is paused, and what will resume progress.
Implementation examples
- Intelligence: The "brain" that processes information and makes decisions using LLMs.This component handles context understanding, instruction following, and response generation.script · intermediate
- Memory: Stores and retrieves relevant information across interactions.This component maintains conversation history and context to enable coherent multi-turn interactions.script · intermediate
- Tools: Enables agents to execute specific actions in external systems.This component provides the capability to make API calls, database updates, file operations, and other practical actions.script · intermediate
- Validation: Ensures LLM outputs match predefined data schemas.This component provides schema validation and structured data parsing to guarantee consistent data formats for downstream code.script · intermediate
- Control: Provides deterministic decision-making and process flow control.This component handles if/then logic, routing based on conditions, and process orchestration for predictable behavior.script · intermediate
- Recovery: Manages failures and exceptions gracefully in agent workflows.This component implements retry logic, fallback processes, and error handling to ensure system resilience.script · intermediate