> So double down on languages that are more represented in training data?
The pragmatic answer to that is: this appears to be highly effective.
What I have in mind is something else, however. Consider the safety nets we try to build with, for example, elaborate type systems. These new analysis tools can operate on enormous contexts and infer and enforce "type" with a capacity far greater what a human mind can hope to approach. So perhaps there is little value to complex types. Instead, a simple type system supported by specification will be the superior approach. seL4 is an example of the concept: C, but exhaustively specified and verified.
In my experience good type systems help human programmers and AI agents alike. AI can only infer "type" probabilistically and haphazardly. It is far from able to enforce anything. A good type system helps both humans and AI agents by correcting their mistakes sooner.
The pragmatic answer to that is: this appears to be highly effective.
What I have in mind is something else, however. Consider the safety nets we try to build with, for example, elaborate type systems. These new analysis tools can operate on enormous contexts and infer and enforce "type" with a capacity far greater what a human mind can hope to approach. So perhaps there is little value to complex types. Instead, a simple type system supported by specification will be the superior approach. seL4 is an example of the concept: C, but exhaustively specified and verified.