An AI Agent Shouldn’t Be Able to Approve Its Own Work As AI agents become more autonomous, there’s a subtle problem that starts to matter who checks the agent before an important action becomes final? Imagine a business agent receives an invoice, decides that it looks legitimate and then has permission to release the payment itself. The workflow is fast but the same system is effectively making the decision and approving its own decision. For low risk actions, that might be acceptable. For a $50,000 transfer probably not. A better application can separate decision making from authority. The agent can analyze the invoice and recommend payment while another policy, verification step or human approval determines whether the transaction is actually allowed to execute. With the kind of programmable workflows @RialoHQ enables that could look like: Agent evaluates invoice → Recommends payment → Risk/value checked → Required approval obtained → Execute The interesting part is that approval doesn’t need to be identical for every action. A $20 software bill could execute automatically while a $50,000 transfer could require stronger verification. An unusual recipient could trigger another rule entirely. That gives autonomy room to scale without giving one agent unlimited control over the whole process. As agents start handling real assets and business operations making them smarter is only part of the challenge. Sometimes the safest architecture is simply making sure the system that proposes an action isn’t always the system that gets the final say.