The legacy of the electric motor is not textile factories that are 30% more efficient because we point-replaced steam engines. It's the assembly line. The workforce "lost" the skills to operate the textile factories, but in turn, the assembly line made the workflow of goods production vastly more efficient. Industrial abstraction has been so successful that today, a small number of factories (e.g., TSMC) have become nearly-existential bottlenecks.
That is the aspiration of AI software tools, too. They are not coming to make us 30% more efficient, they are coming to completely change how the software engineering production line operates. If they are successful, we will write fewer tests, we will understand less about our stack, and we will develop tools and workflows to manage that complexity and risk.
Maybe AI succeeds at this stated objective, and maybe it does not. But let's at least not kid ourselves: this is how it has always been. We are in the business of abstracting things away so that we have to understand less to get things done. We grumbled when we switched from assembly to high-level languages. We grumbled when we switched from high-level languages to managed languages. We grumbled when we started programming enormous piles of JavaScript and traveled farther from the OS and the hardware. Now we're grumbling about AI, and you can be sure that we're going to grumble about whatever is next, too.
I understand this is going to ruffle a lot of feathers, but I don't think Thomas and the Fly team actually have missed any of the points discussed in this article. I think they fully understand that software production is going to change and expect that we will build systems to cope with abstracting more, and understanding less. And, honestly, I think they are probably right.
That is the aspiration of AI software tools, too. They are not coming to make us 30% more efficient, they are coming to completely change how the software engineering production line operates. If they are successful, we will write fewer tests, we will understand less about our stack, and we will develop tools and workflows to manage that complexity and risk.
Maybe AI succeeds at this stated objective, and maybe it does not. But let's at least not kid ourselves: this is how it has always been. We are in the business of abstracting things away so that we have to understand less to get things done. We grumbled when we switched from assembly to high-level languages. We grumbled when we switched from high-level languages to managed languages. We grumbled when we started programming enormous piles of JavaScript and traveled farther from the OS and the hardware. Now we're grumbling about AI, and you can be sure that we're going to grumble about whatever is next, too.
I understand this is going to ruffle a lot of feathers, but I don't think Thomas and the Fly team actually have missed any of the points discussed in this article. I think they fully understand that software production is going to change and expect that we will build systems to cope with abstracting more, and understanding less. And, honestly, I think they are probably right.