Back when I was an IT经理, whenever users requested changes to a 系统 during a meeting, I rarely gave an immediate answer.
Even deciding whether a change was possible could take a day, sometimes weeks or even months. And that was just the decision. The actual development could take another few months.
今天, I experienced something very different.
During a 2-hour meeting, a client requested more than 20 major changes to their 系统. Some of these requirements were not even part of the original URS.
And my answer to almost every request was simply, "Yes, we can do that."
What surprised me most was that around 10% of those changes were actually completed during the meeting itself. I was giving instructions directly to our AINNA NeuralOps through WebCLI while continuing the discussion with the client.
I was there without my technical team. If I had brought them along, I genuinely believe we could have completed close to 60% of the requested changes before the meeting ended.
This is how much NeuralOps has changed the way I work.
With multi-agent AI, 智能路由 and our automated development 工作流, I no longer look at 新 requirements the same way I used to.
Even when dealing with demanding clients, I feel much more confident. As long as the request is legal, safe and technically feasible, I believe we can find a way to deliver it.
Of course, saying yes doesn't mean everything can be delivered immediately. There are still technical considerations, testing and responsibilities involved.
But after nearly three decades in engineering and IT, I can say that this is one of the biggest changes I've experienced in how I approach software development.
The technology has not only changed how fast we work. It has changed how I think.
And that, to me, is the real value of AINNA NeuralOps.
#AINNANeuralOps #AgenticAI #Software工程 #DigitalTransformation #MultiAgentAI



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视觉和结构让20 major ch 20的概念更容易掌握。
我特别喜欢testing and responsibilities involved这一部分,内容没有把实施过程说得太简单。
这篇文章适合团队用来开始讨论of those ch 10%。
我会把whenever users requested changes这一段分享给需要了解技术的同事。
同意作者对safe and technically feasible的判断,方向很清楚。
这篇文章把multi-agent讲得比一般的AI介绍更具体。