⚠️ Example
An AI agent with access to your tools can already:
- delete your production users table
- send emails to real customers
- trigger payments or workflows
In most systems today — these actions just execute.
No checkpoint. No approval.
We’ve crossed a line.
AI is no longer just generating text.
It’s starting to take actions.
await deleteUser(userId);
await sendEmail(customer);
await transferFunds(amount);
If the agent decides to do it — it just runs.
That’s fine in a demo.
It’s not fine in production.
Where things break
Once AI touches real systems, you’re exposed to:
- accidental destructive actions
- prompt injection leading to unintended behavior
- over-permissioned tools
- zero auditability of decisions
You don’t need a malicious AI.
You just need:
a slightly wrong decision, at the wrong time
The missing layer
Every action should be checked before it runs.
Not after.
Not in logs.
Before execution.
What Runplane does
Runplane sits between your AI and real-world execution.
Every action becomes:
- ✅ ALLOW
- ❌ BLOCK
- ⏸ REQUIRE APPROVAL
Example
Without control:
await deleteUser(userId);
With Runplane:
await runplane.guard(
"delete_user",
"production-db",
{ userId },
async () => {
return deleteUser(userId);
}
);
Now:
- destructive actions can be blocked
- risky actions can require approval
- everything is logged and auditable
Where this fits
If you're building:
- AI agents
- MCP tools
- automation workflows
- internal copilots
- API-driven systems
You already have this risk.
You just haven’t hit it yet.
Try it
There’s a free developer tier:
https://runplane.ai/auth/sign-up?mode=developer
You can plug it into a real flow and immediately see:
- actions being blocked
- approvals being triggered
Final thought
We’re moving from:
“AI suggests actions”
to:
“AI executes actions”
Execution without control is risk.
AI has hands now.
You should decide what it’s allowed to touch.
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