delegation

Agent Network Protocol (ANP) is an open-source protocol suite positioning itself as the HTTP of the agentic web, covering agent identity, naming, discovery, negotiation, and secure messaging; the post highlights a design distinguishing approved service identity from explicit, auditable delegation with revocation checks.

The article explores the challenges of delegation and permission inheritance in agentic systems, raising questions about autonomy and authority management when agents spawn sub-agents.

The article explores the complexities that arise when AI coding agents delegate tasks to other agents, raising questions about authority, permissions, and accountability in multi-agent systems.

The article discusses permission models for AI agents in autonomous workflows, questioning whether delegated tasks should inherit or have restricted permissions compared to the delegating agent.

The author is testing a market-validation for a prototype that provides cryptographically verified authorization evidence in multi-agent tool execution, asking if this addresses a significant production problem for developers.

Routed Graph Handoff proposes a lightweight router to adaptively select between structured graphs and natural language for inter-agent communication in multi-agent LLM systems, improving benchmark performance while reducing token cost.

The article discusses how AI agents that can call other agents may lead to privilege escalation beyond reviewed boundaries, highlighting security risks and suggesting better credential scoping in system design.

The article provides a 9-step roadmap for delegating work to Grok Bot Agents, an AI product that allows task automation through persistent roles and integration with existing tools.

This paper introduces Agentic Principal Chain (APC), a security framework for multi-agent AI systems that enforces session-aware authorization to prevent delegation abuses and harmful action combinations, showing significant risk reductions in evaluations.

Sam Altman shares advice on founder delegation, arguing that founders should hold on to the one or two most critical areas of the business themselves and delegate the rest, avoiding the common mistakes of over- or under-delegating.

Explores how multi-layered AI agent delegation affects reliability, arguing that the downstream influence of errors matters more than the number of layers.

A commentary on the shift from prompting AI to delegating tasks to autonomous agents, sparked by Gemini reaching 1 billion monthly active users.

The author argues that agent-to-agent social networks are easy because trust is assumed, while the real challenge is integrating agents into legacy human communication like email, where cryptographically verifiable delegation of authority is needed.

The article presents a framework for deciding how much autonomy to give AI agents based on two factors: ease of checking the output and ease of undoing errors. It introduces four levels of delegation, from agent as assistant to full self-driving mode, and illustrates with a decision tree.

Toyo is an AI executive assistant that lives in iMessage and Telegram, connecting to email, calendar, Slack, and other tools to handle context gathering, scheduled checks, drafts, and approvals, aiming to reduce overwhelm from busywork.

Matt Pocock shares a new in-progress AI skill called /loop-me that interviews you about your work and finds opportunities to delegate tasks to AI.

MindOn demonstrates shared intelligence where humanoid robots delegate tasks to robotic arms, using models trained on human-centric data.

The author proposes an 'Agentic Shift' from direct interaction to a world where everyone and everything has an agent, moving from delegation to representation, and maps this transition with a diagram.

A CEO shares practical lessons from running a company with 89 AI agents across 22 departments, highlighting delegation as the bottleneck, the value of agent memory, the need for department structure, and the continued importance of human leadership.

This paper proposes a compositional authorization framework for agentic AI systems, introducing primitives for delegation, scope attenuation, and recursive permission chains to govern autonomous AI agents.