I want to make clear that I agree with the author that the current way in which AI is being used to make a 10x improvement in efficiency is NOT going to work, and it is for exactly reason stated:
> 10x-ing requires deep conceptual understanding – exactly what GenAI lacks. Writing lines of code without that understanding can only help so much.
IMHO, the real opportunity with AI, is to get developers less critical in being the only ones who translate conceptual understanding of the business problem into code and get developers more focused on the domain they should be experts in which, imho, is the large scale structure of the system and how that maps to actual computes.
What I mean by that... developers, are, on average, not good at having deep conceptual understanding of the business domain... and maybe have that understanding in the computational domain. All of the 10x developers I have ever met are mostly that because they do know both the business domain (or can learn it really quick) and the computational domain so they can quickly deliver value because they understand the problem end-to-end.
My internal model for thinking about this is we need developers thinking about building the right "intermediate representation" of a problem space and being able to manage the system at large, but we need domain experts, likely supported by AI assistants, in helping to use that IR to express the actual business problem. That is a super loose explanation... but if you have been in the industry awhile, you probably have felt the insanity of how long it can take to ship a fairly small feature because of a huge disconnect between the broader structure of the system (with microservices, async job systems, data pipelines, etc, which we can think of as the low-level representation of the sytem at large) and the high-level requirement of needing to store some data and process it according to some business specific rules.
I have no idea if we actually can get there as an industry... it is more likely we just have more terrible code... but maybe not
> 10x-ing requires deep conceptual understanding – exactly what GenAI lacks. Writing lines of code without that understanding can only help so much.
IMHO, the real opportunity with AI, is to get developers less critical in being the only ones who translate conceptual understanding of the business problem into code and get developers more focused on the domain they should be experts in which, imho, is the large scale structure of the system and how that maps to actual computes.
What I mean by that... developers, are, on average, not good at having deep conceptual understanding of the business domain... and maybe have that understanding in the computational domain. All of the 10x developers I have ever met are mostly that because they do know both the business domain (or can learn it really quick) and the computational domain so they can quickly deliver value because they understand the problem end-to-end.
My internal model for thinking about this is we need developers thinking about building the right "intermediate representation" of a problem space and being able to manage the system at large, but we need domain experts, likely supported by AI assistants, in helping to use that IR to express the actual business problem. That is a super loose explanation... but if you have been in the industry awhile, you probably have felt the insanity of how long it can take to ship a fairly small feature because of a huge disconnect between the broader structure of the system (with microservices, async job systems, data pipelines, etc, which we can think of as the low-level representation of the sytem at large) and the high-level requirement of needing to store some data and process it according to some business specific rules.
I have no idea if we actually can get there as an industry... it is more likely we just have more terrible code... but maybe not