Abstract: Systems and methods for using multiple machine agents to generate document drafts. Exemplary implementations may: (a) prompt a generative machine agent to generate an initial document draft; (b) receive the initial document draft from the generative machine agent; (c) prompt a discriminative machine agent to generate a first set of inferences based on the initial document draft; (d) receive the first set of inferences from the discriminative machine agent; (e) prompt the generative machine agent to generate an iterated document draft; (f) receive the iterated document draft from the generative machine agent; (g) prompt the discriminative machine agent to generate an iterated set of inferences; (h) determine whether the iterated set of inferences meets inference criteria; (i) responsive to the iterated set of inferences not meeting inference criteria, loop over operations (e) through (i) to generate and assess a further iterated document draft; and/or other exemplary implementations.

Abstract: Systems and methods for generating legal document drafts for individual cases based on case content and exemplary segments of legal documents. Exemplary implementations may: store case content for individual cases, obtain first case content for a first case from electronic storage, provide the first case content and/or user-provided context values as input to a large language model, provide one or more prompts to the large language model that configure the model to generate a first document draft, obtain output from the large language model including the first document draft, provide the first document draft to a user, and/or other exemplary implementations.