Description
AI agents are starting to become part of day-to-day project management work. In this video, we explore how Project Managers, Scrum Masters, and Product Owners can use Atlassian Rovo agents inside Jira to support backlog refinement, epic discovery, user story creation, and requirement analysis.
I demonstrate how an agent can be configured in Atlassian using instructions, skills, knowledge sources, and web search. We first look at a Backlog Builder Agent that improves Jira stories and epics using project context from Confluence. Then we create a new Fitness App Insight Agent that performs market research, compares benchmark apps, suggests epic ideas, and creates Jira work items.
The goal of this session is not to show AI as magic, but to help project professionals understand how agents actually work, where they help, where they still fail, and what kind of governance, testing, and human approval is needed before using them in real project environments.
In this video, you will learn:
- How Atlassian Rovo agents work inside Jira
- How to define agent instructions and skills
- How agents use Jira, Confluence, and web search as context
- How to improve user stories and epics using AI agents
- How to create a market research agent for requirement discovery
- What limitations you may face while using AI agents in Jira
Chapters
00:00 Introduction: Using AI Agents in Jira for PMs
01:29 Defining Agent Instructions
05:48 Invoking the Agent Inside a Jira Project
15:41 How to Create Your Own Atlassian Agent
20:36 Reviewing the Newly Created Agent Configuration
22:14 Invoking the New Fitness App Insight Agent
22:40 Asking the Agent to Research a Calories Trend Feature
23:59 Creating the Epic Directly in Jira
25:42 Key Takeaways for Project Managers
26:35 Future Role of Agents in Project Management Work