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Agents have the power to take real-world actions — which means they can also cause real-world harm. Without guardrails, an agent might delete critical files, send embarrassing emails, spend thousands of dollars on API calls, or get stuck in an infinite loop. This lesson covers input/output validation, action sandboxing, human-in-the-loop patterns, rate limiting, and preventing runaway agents.
| Risk | Example |
|---|---|
| Data loss | Agent deletes production database records |
| Financial damage | Agent makes unlimited API calls, costing thousands |
| Security breach | Agent exfiltrates sensitive data via a tool call |
| Reputation damage | Agent sends incorrect emails to customers |
| Infinite loops | Agent calls the same tool repeatedly with no progress |
| Prompt injection | Malicious input causes agent to bypass instructions |
Validate all inputs before they reach the agent:
from pydantic import BaseModel, validator
import re
class AgentInput(BaseModel):
task: str
user_id: str
max_steps: int = 10
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