Recent advancements in the field of large language models have made it possible to use language models for advanced reasoning. In this paper we leverage this ability for designing complex project plans based only on knowing the current state and the desired state. Two approaches are demonstrated - a scrum based approach and a shortcut plan approach. The scrum based approach executes an automated process of requirements gathering, user story mapping, feature identification, task decomposition and finally generates questions and search terms for seeking out domain specific information to assist with task completion. The shortcut approach looks at most recent snapshot of the current and desired state and generates the next most reasonable task to do in order to get to the desired state as quickly as possible. In this paper we automate everything using a novel concept of "Language Programs". These are programs written in natural language designed to process input data through the language model. Guidance language is used for all LLM programs. All demo source code for this paper is available at https://github.com/autoscrum/autoscrum

翻译：近期大型语言模型领域的进展使得利用语言模型进行高级推理成为可能。本文基于仅需知晓当前状态与目标状态，利用这一能力设计复杂项目计划。我们展示了两种方法：基于Scrum的方法与快捷计划方法。基于Scrum的方法执行自动化流程，包括需求收集、用户故事映射、功能识别、任务分解，最终生成用于寻求领域特定信息以辅助任务完成的查询与搜索词。快捷方法则聚焦当前状态与目标状态的最新快照，生成为实现目标状态需尽快执行的下一项最合理任务。本文借助“语言程序”这一新概念实现全面自动化，该类程序以自然语言编写，旨在通过语言模型处理输入数据。所有LLM程序均采用Guidance语言。本文演示源码可通过https://github.com/autoscrum/autoscrum获取。