更早 in my career, when I sat on the IT management side, I rarely gave users an immediate answer when they asked for a 系统 change in a meeting.
Even deciding whether a change was feasible could take a day, sometimes weeks or months. And that was only the decision. The actual development could take another few months.
今天 looked very different.
In a two-hour working session, a client requested more than 20 major changes to their 系统. Some of those requirements were not even in the original URS.
My answer to almost every request was some version of, 'Yes, we can do that.'
What surprised me most was that roughly 10% of those changes were actually completed during the meeting itself. I was issuing instructions directly to our AINNA NeuralOps through WebCLI while continuing the discussion with the client.
I was there without my technical team. If they had been in the room, I genuinely believe we could have completed close to 60% of the requested changes before the meeting ended.
That 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 as isolated tickets. I look at them as executable units that can be routed, validated and pushed through the pipeline.
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 does not mean everything can be delivered immediately. There are still architecture constraints, integration work, testing and operational ownership involved.
But after nearly three decades in engineering and IT, I can say this is one of the biggest changes I have 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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总结部分让智能路由 and our automated development的重点更加清楚。
这篇文章把今天 looked讲得比一般的AI介绍更具体。
关于更早 in my career的实际落地部分最吸引我。