---
schemaVersion: 1
id: agent-brief:ai-delegation-orchestration-05-long-running-delegations
articleId: article:ai-delegation-orchestration-05-long-running-delegations
slug: ai-delegation-orchestration-05-long-running-delegations
title: "Agent Brief for Long-Running Delegations: How Agents Can Work for Hours Without Losing the Plot"
tokenBudget: 1200
status: published
updated: 2026-06-28
---

## Thesis

Long-running AI work is viable only when the delegation has checkpoints, evidence gates, self-remediation loops, interruption rules, rollback paths, and explicit stop conditions.

## Audience

- Builders and researchers working on AI-agent systems.
- Advanced AI users supervising multi-step or long-running workflows.
- Students studying agent orchestration principles.
- Future agents needing a compact summary of the article.

## Claims

- claim-001: Long-running AI work is viable only when the delegation has checkpoints, evidence gates, self-remediation loops, interruption rules, rollback paths, and explicit stop conditions.

## Review Status

This published brief summarizes the article for agent retrieval. Treat the claims as exploratory design arguments, not settled standards.

## Agent Involvement

Drafted and structured with AI assistance from sanitized discussion synthesis and public sources. Human publication approval was recorded on 2026-06-28.