Stage 6: Long-Lived Autonomous Agents
Agents that persist for days to months, not minutes.
Task
Run agents that persist for days to months, maintaining state, memory, and goals across sessions and failures.
Why This Matters
Scientific campaigns unfold over weeks or months. Long-lived agents accumulate knowledge, adapt strategies, and pursue open-ended discovery—fundamentally different from stateless scripts or single-session tools.
Details
| Aspect | Value |
|---|---|
| CAF Components | Lifecycle management, persistent state, failure recovery |
| Where it runs | Any (with durable storage) |
| Scale | Days to months of continuous operation |
| Status | Emerging |
Architecture
Code
| Example | Description |
|---|---|
| AgentsCheckpoint | Checkpoint/resume patterns for workflows that span sessions |
Prerequisites
Before building long-lived agents:
- AgentsConversation — Memory patterns for stateful agents
- AgentsPersistent — Checkpoint and resume with Academy
Next Steps
After mastering long-lived agents:
- Agent Workflows — Dynamic workflow construction
- Multi-Agent Coordination — Coordinating persistent agents
Related Topics
- Governed Tool Use — Policy enforcement (important for autonomous agents)
- Federated Agents — Running persistent agents across institutions