Software product development spans multiple stages within the software development lifecycle (SDLC). While LLMs have primarily supported code development and engineering productivity, AI is increasingly being applied to earlier phases, such as requirements definition.
Enterprise software development includes several SDLC stages. Below potential ideas on how to leverage AI and automation in each of the SDLC stages:
AI can improve efficiency in requirements definition and the creation of product requirement documents (PRDs). PRDs link end-user or market needs to engineering execution; with product managers typically responsible for PRD creation and maintenance.
An example of GenAI and LLMs supporting product managers is ChatPRD (https://www.chatprd.ai/ ), a tool designed to assist with requirements generation and documentation.
ChatPRD uses a traditional SaaS delivery model with web and mobile interfaces and a subscription-based approach. It also offers a conversational interface within ChatGPT (https://chatgpt.com/g/g-G5diVh12v-chatprd-ai-for-product-managers) to support discovery activities and streamline onboarding.
New tools and features are continually emerging to support various stages of the SDLC.
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