Every conference call and vendor deck now sells AI as if one autonomous agent can stand up an entire operation before the next sprint review.
After enough polished demos, even experienced stakeholders start buying the pitch.
Think of it like a hospital deciding its surgeons alone can run everything. So it removes the nurses, lab techs, pharmacists, intake clerks, orderlies, facilities staff, and security.
Looks great on a slide.
Falls apart the moment a real patient walks through the door.
That is exactly what I am seeing in production AI rollouts.
Teams swap humans for autonomous agents and immediately hit model hallucinations, brittle guardrails, runaway token spend, non-deterministic outputs, and silent rollbacks where the same headcount gets rehired.
I build a detached 系统.
LLMs accelerate 设计 and handle fuzzy inputs; fixed rules own the repeatable paths; humans stay wired in for control, exception handling, and accountability.
Our 银行 Statement 对账 系统 is built that way: no theatrical agent promises, controlled cost, reproducible output, and operators still holding the override.
AI should harden the organisation, not delete the judgment required to run it.
#Artificial智能 #AI自动化 #分离式系统 #HumanInTheLoop #中小企业 #商业自动化 #AI治理 #DigitalTransformation
Ruang pembaca
Apa pendapat anda?
Komen disemak sebelum diterbitkan. 电子邮件 diperlukan untuk moderasi dan tidak dipaparkan kepada pembaca.
我喜欢这段说明这部分，因为它讲得比较务实。
先存起来，主要是为了这部分。
视觉和结构让LLMs accelerate 设计 and handle的概念更容易掌握。
Falls apart the moment这个说法我要拿回去跟同事讨论。
文章对fixed rules own the repeatable的结论比较平衡，不只是强调好处。
这篇文章适合团队用来开始讨论non-deterministic。
关于teams swap humans for autonomous的说明很完整，基础部分尤其清楚。
我喜欢文章对humans stay wired保持务实的态度。