Back in 2003, I was a MEMS 设计 Engineer in the semiconductor industry, experimenting with web applications by combining scripts. Back then, people like me were called script kiddies.
I was sent to Dresden, Germany, to learn MEMS chip calibration from a PhD engineer whose research had helped create thousands of jobs worldwide.
The programmer who accompanied me eventually resigned because of the technical complexity. I had no choice but to learn low-level programming, I²C protocols, 系统 integration and LabVIEW myself.
Fast forward to 2026.
A 系统 that once required six months of development could now, I believe, be delivered in just seven 天数 using our own AINNA NeuralOps 架构 and WebCLI, with significantly greater capabilities.
The real breakthrough isn't just faster coding. It's how AI 智能体 fundamentally change the economics of software development.
Less development time. 更低 engineering overhead. Faster deployment. Greater scalability.
After 23 years, I've realised something.
The next generation of technology companies won't necessarily be defined by the size of their engineering teams, but by how much they can deliver with the resources they have.
And that's exactly what we're building at AINNA.
#AgenticAI #AINNANeuralOps #AI基础设施 #Software工程 #DeepTech #创新
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文章对i've realised someth 23提供了很好的起点，值得继续跟进。
看第二遍才注意到更低 engineering overhead的细节。
Back in 2003这个说法我要拿回去跟同事讨论。
关于experimenting with web applications的实际落地部分最吸引我。