Making Agents Durable
State management, retries, and stop conditions
Making Agents Durable
Production agents need to handle failures, maintain state, and know when to stop.
Durability Patterns
State Management
Agent saves progress to disk or database. If it crashes mid-task, it resumes from last checkpoint.
Agent saves progress to disk or database. If it crashes mid-task, it resumes from last checkpoint.
Retries
Tool calls can fail (network error, rate limit). Agent retries with exponential backoff.
Tool calls can fail (network error, rate limit). Agent retries with exponential backoff.
Stop Conditions
Prevents infinite loops. Agent has max steps, max time, or explicit done criteria.
Prevents infinite loops. Agent has max steps, max time, or explicit done criteria.
Error Handling
When a tool fails, agent logs error, decides if it's recoverable, and either retries or fails gracefully.
When a tool fails, agent logs error, decides if it's recoverable, and either retries or fails gracefully.
Export Your Agent
After configuring your agent in the playground, you can export the configuration as JSON. This config can be:
- Version controlled in Git
- Deployed to a cloud function or container
- Modified and tested in different environments
- Shared with your team
Next Steps: Take what you've learned and build a real agent. Choose a framework (LangChain, CrewAI, custom), add real tools, deploy on a schedule or webhook, and let it run autonomously.
Example Agent Config
{
"trigger": "cron",
"schedule": "0 9 * * *",
"goal": "Generate daily metrics report",
"tools": ["queryDatabase", "generateChart", "sendEmail"],
"maxSteps": 20,
"timeout": 300,
"retries": 3
}Congratulations! You now understand self-invoked automated agents. Go build something powerful.