Intelligent AI Delegation

Key points

• The paper distinguishes task decomposition, which divides work into smaller pieces for allocation, from intelligent delegation. Intelligent delegation also transfers authority and responsibility, clarifies roles and boundaries, aligns intent, and establishes mutual trust.
• The proposed framework has five pillars: dynamic assessment that continuously monitors the other party's current state, adaptive execution that revises plans as circumstances change, structural transparency that makes processes and outcomes inspectable, scalable market coordination that connects many participants at low cost, and system resilience that prevents cascading failures.
• The central principle is contract-first decomposition, which means first breaking work into verifiable units. Subtasks whose outputs are difficult to verify or overly subjective should be decomposed further until they admit checks such as unit tests or formal proofs.
• Selecting a delegate requires separating publicly visible reputation from trust criteria defined by the delegator. Authority should be limited to what the task requires and narrowed further under subdelegation, with progress monitoring, completion verification, and an accountability trail recording who delegated what to whom.
• The paper argues that MCP lacks mechanisms for fine-grained authority delegation, A2A has no field for attaching proof of completion, AP2 lacks conditional settlement, and UCP is designed for commerce and therefore needs extensions for general task delegation. The proposal is conceptual and is not implemented or experimentally validated in the paper.

Paper links

External research summaries. These are not HDATF publications or measured product results.