Long-running AI Agents
Definition
Long-running AI agents are AI agents designed to operate continuously or across extended periods of time, maintaining state and progressing toward goals over multiple inference steps rather than completing tasks in a single interaction.
Purpose
The purpose of long-running AI agents is to enable complex, multi-step, and time-extended tasks that require persistence, coordination, and state management beyond a single model invocation.
Key Characteristics
- Persistence of agent state across multiple inference cycles or sessions
- Reliance on external memory or state storage rather than a single context window
- Ability to pause, resume, and recover execution over time
- Accumulation and management of intermediate results and decisions
- Increased exposure to error accumulation and drift over long execution horizons
Usage in Practice
In practice, long-running AI agents are used to manage ongoing workflows, coordinate complex processes, monitor systems, or execute tasks that unfold over hours, days, or longer periods and cannot be reliably handled in a single interaction.
One implementation of this concept is offered by Kenaz through the Custom AI Agents service.