---
title: "Comment by Steven Mock on \"Self-Adaptive Enterprise Automation Using Generative AI Agents\" | Hashnode"
description: "The part that matters most here is the human-approval gate for financial or sensitive decisions. Self-correction sounds good in theory, but in a real operation"
url: "https://hashnode.com/posts/self-adaptive-enterprise-automation-using-generative-ai-agents/6aeebb448d3392882e32ff49/comment/6aeec95cdc68ccee77d3ea3e"
---

[Discussion](https://hashnode.com/posts/self-adaptive-enterprise-automation-using-generative-ai-agents/6aeebb448d3392882e32ff49)

Comment [Self-Adaptive Enterprise Automation Using Generative AI Agents](https://hashnode.com/posts/self-adaptive-enterprise-automation-using-generative-ai-agents/6aeebb448d3392882e32ff49)

[Steven Mock](https://hashnode.com/@stevenmock)

[Nov 7](https://hashnode.com/posts/self-adaptive-enterprise-automation-using-generative-ai-agents/6aeebb448d3392882e32ff49/comment/6aeec95cdc68ccee77d3ea3e)

The part that matters most here is the human-approval gate for financial or sensitive decisions. Self-correction sounds good in theory, but in a real operation an agent quietly fixing its own mistake is exactly how a small error becomes a costly one. The honest metric in your evaluation list is how often a person still has to intervene — if that number is not falling, the system is not really learning. Start with one narrow workflow, not a full platform, and let the feedback loop prove itself there first.