> generate 100 solutions cheaply without coordination between them and pick the winner with a relatively fast eval
While it might get workable results, this seems like a miserable way to work with code. You spend the vast majority of time thinking about the problem domain of working with agents instead of your project, and for mediocre output. You are transforming your role into a dumpster diver of code.
The approach that proves to be fastest in the long run is to stay close to the code. Lay out the base structure, and use an LLM to check your work and fill in the gaps. The beauty of this approach is that it scales very well with the size of the project. When the LLM has plenty of high quality examples to follow, they start to write the same code that you would. Where it diverges, create documentation.
Perhaps the single best property of LLMs is their ability to consume and apply examples and documentation.
While it might get workable results, this seems like a miserable way to work with code. You spend the vast majority of time thinking about the problem domain of working with agents instead of your project, and for mediocre output. You are transforming your role into a dumpster diver of code.
The approach that proves to be fastest in the long run is to stay close to the code. Lay out the base structure, and use an LLM to check your work and fill in the gaps. The beauty of this approach is that it scales very well with the size of the project. When the LLM has plenty of high quality examples to follow, they start to write the same code that you would. Where it diverges, create documentation.
Perhaps the single best property of LLMs is their ability to consume and apply examples and documentation.