alt Hacker NewsSomething like this has been on my mind for a while. When using LLMs for coding I believe it is a significant benefit, if the amount of lines to be reviewed by humans is as small as possible. An app, which is not much more than a configuration in a dense, custom made DSL with minimal coding to specify business logic would be the simplest artifact that a human can review quickly and an LLM can manipulate with ease (provided there's good docs / linting / errors / maybe even a finetuned model at some point).
Everything which just works "by convention" or by "opinionated defaults" (allowing a tightly coupled but very feature rich framework) helps to reduce the noise / lines that needs to be reviewed.
While this approach might not be optimal for every project, I'm certain the opinionated defaults can work for many endeavours. And the reduction of complexity might be one important aspect, which can make an "agentically engineered" project sustainable.
>Everything which just works "by convention" or by "opinionated defaults" (allowing a tightly coupled but very feature rich framework) helps to reduce the noise / lines that needs to be reviewed.
This is exactly why I've gone back to Ruby with Sinatra or Rails for my personal side projects, despite Ruby's horrid performance.
As long as you are content to remain on e.g. Rails' "Happy Path", then I've found agents do a fantastic job because there's lots of Ruby in the training set and there's less surface area where a context mismatch/hallucination can end up going off the rails. Pun only partially intended.