Axel Sooriah Product Management Evangelist, Atlassian
PMs are more anxious about how to solve problems using AI in their products than losing their jobs to AI.
The AI revolution is transforming how product teams discover opportunities, align priorities, and deliver customer value. Yet many teams struggle to move beyond experimentation and embed AI in their everyday workflows. In this session, we’ll focus on the big-picture strategies and hands-on tactics that make AI a true force multiplier for your end-to-end product process. You’ll walk away with concrete methods to claim time back that you can invest in critical activities like product discovery—from automating the creation of discovery artifacts to increasingly exposing your broader team to customer knowledge —while preserving cross-team collaboration and strategic clarity.
The anxiety about AI is real for PMs. However, PMs are more anxious about how to solve problems using AI in their products than losing their jobs to AI.
Here are 3 ways you can go from anxiety to agency and make AI impactful in your work while learning new skills as product builders.
Automate discovery and build context libraries
A context library is a curated set of product knowledge (strategy, customer insights, specs, ways of working) that AI tools can reference
It ensures AI delivers relevant, high-quality, and consistent outputs instead of generic answers.
Alex demoed how to easily build context libraries using Claude, an MCP server, and Confluence.
The demo used a fictitious example of a product management team building a FinTech app
Context libraries can be particularly helpful when you want higher-quality outputs from your AI Tools.
Alex demoed how to apply context libraries to automate tasks like desk research.