The AI Taxonomy.
Terms  /  Human-Agent Relationship  /  Informed Delegation
07 · Human-Agent Relationship

Informed Delegation

Intentional handoff of work to an agent with clear scope, checkpoints, and the ability to inspect and override.

Informed Delegation is the healthy version of the human-agent working relationship. The human knows what they're delegating, sets clear boundaries, establishes checkpoints for review, maintains the ability to understand and override the agent's work, and verifies results at meaningful intervals. It's not about doing less — it's about delegating intelligently, with full awareness of the risks and full access to the agent's process.

Example
A developer delegates a refactoring task to an agent with the following structure: "Refactor the user module from callbacks to async/await. Scope: only the user module, don't touch other modules. Checkpoints: show me each function before and after. Constraints: maintain the public API, don't change test expectations. Verification: run the test suite after each function and show me the results." The developer reviews at each checkpoint, catches one issue early, and the final result is exactly what they wanted. They delegated the work but retained control.

More in Human-Agent Relationship

Human-Code Divergence

The gap created between a user and their codebase when an agent mediates all development.

Cognitive Load

The mental burden placed on the human when working with AI systems.

Agency Erosion

Gradual loss of human decision-making authority as agents take over more workflow without checkpoints.

Skill Atrophy

Decay of human technical skills from prolonged delegation to agents.

Automation Dependency

Reliance on agents to the point where the human can't perform the task without them.

Trust Without Verification

Accepting agent output without review — a precondition for Execution Hallucination going undetected.

Confidence Decay

The gradual erosion of user trust as a system repeatedly loses context, hallucinates, or fails to follow through.

Capability Illusion

The user believes the AI can do more than it actually can, leading to over-delegation and undetected failures.