Ask HN: How do you authorize AI agent actions in production?
I'm deploying AI agents that can call external APIs – process refunds,
send emails, modify databases. The agent decides what to do based on
user input and LLM reasoning.
My concern: the agent sometimes attempts actions it shouldn't, and
there's no clear audit trail of what it did or why.
Current options I see:
1. Trust the agent fully (scary)
2. Manual review of every action (defeats automation)
3. Some kind of permission/approval layer (does this exist?)
For those running AI agents in production:
- How do you limit what the agent CAN do?
- Do you require approval for high-risk operations?
- How do you audit what happened after the fact?
My concern: the agent sometimes attempts actions it shouldn't, and there's no clear audit trail of what it did or why.
Current options I see: 1. Trust the agent fully (scary) 2. Manual review of every action (defeats automation) 3. Some kind of permission/approval layer (does this exist?)
For those running AI agents in production: - How do you limit what the agent CAN do? - Do you require approval for high-risk operations? - How do you audit what happened after the fact?
Curious what patterns have worked.