An AI development team is training a language model to function as a detective's assistant, tasked with generating plausible theories by connecting disparate pieces of evidence from a complex case file. The goal is for the model to produce a well-reasoned chain of logic, not just a correct final conclusion. Which training feedback strategy would be most effective in developing this specific capability?

A team is training a language model to generate creative poetry. The primary goal is to produce poems that are emotionally resonant and artistically novel. For this specific task, a training approach that rewards the model for each correct grammatical step and adherence to a predefined poetic structure will always be more effective than an approach that rewards the model based on a human's holistic rating of the final poem.