Accelerating Product Management with AI
Creating software products involves several steps. There has been plenty of coverage regarding LLMs’ capabilities to write code and augment a software engineer’s productivity. We’ll review the impact of AI in an earlier phase of the SDLC: requirements.
We shared ideas on software engineering changes in productivity: https://alten.capital/blog/productivity-increases-with-ai-coding-assistants and https://alten.capital/blog/exponential-software-engineer-productivity. To create enterprise-level software products that add value to users and organizations, several steps in the software development lifecycle are relevant. A summarized list below with an AI/automation bias:
Discovery: analyzing market data, user feedback, and competitive intelligence
Requirements: automating documentation, identifying gaps, generating user stories
Design: creating mockups, suggesting UI patterns, accessibility checking
Development: code generation, automated testing, bug detection
Deployment: automated DevOps, performance monitoring
Maintenance: predictive maintenance, automated issue triage
Requirements definition and the generation of the product requirements document (PRD) are also areas where AI can accelerate efforts. We can think of the PRD as the linkage between end-user/end-market requirements and the engineers’ development efforts. A product manager is typically responsible for creating and maintaining PRDs.
An example of where GenAI and LLMs are being used to assist PMs is ChatPRD (https://www.chatprd.ai/). As these solutions mature, product managers will also start to see productivity gains in their work.
The ChatPRD website is clearly the traditional way to deliver functionality from a SaaS vendor (web, mobile, subscription). But ChatPRD also took the offering a step forward and created a conversational interface embedded in ChatGPT (an app https://chatgpt.com/g/g-G5diVh12v-chatprd-ai-for-product-managers) to facilitate discovery and reduce onboarding friction.
Several tools (and new features within existing products) will continue to emerge to support each step of the SDLC.
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