AI PRODUCT MANAGER Skills for Agile: AI Product Management

Learn market research by analyzing user comments and reviews to uncover what users want, their frustrations, and problems to solve using deep, multi-source ChatGPT analysis and structured output.

Analyze user comments and reviews to identify common frustrations like intrusive ads, poor navigation, and crashes. Leverage deep research and AI insights to prioritize personalization, content breadth, and streamlined UX.

Learn to conduct AI-assisted competitive analysis for market research, identify strengths, weaknesses, and differentiation gaps, and uncover opportunities early in product discovery without designing features.

conduct a deep competitive analysis by comparing real-time updates, wide coverage, personalization, and ai-driven insights to identify strengths, weaknesses, and opportunities for differentiation in sports apps.

Turn validated research into a clear product vision that defines the target users, the problem, and AI-enabled value, guiding backlog, roadmap, and outcomes over features.

Learn to translate a product vision into a focused, outcome-driven strategy using ChatGPT, defining target segment, core problem, differentiators, measurable outcomes, and AI positioning.

Learn to build a goal-driven product roadmap from strategy to execution, using AI to group themes and prioritize outcomes over features, starting with core data and personalization.

Craft an outcome-based roadmap for passion sports as an agile product manager, detailing quarterly goals, measurable metrics, and high-level features to validate demand, boost engagement, and drive revenue after retention.

Create targeted personas from research and feedback for the Passion Sports app, using ChatGPT to define segments and guide backlog prioritization for faster understanding.

Create and populate persona templates to guide backlog and roadmap decisions for a passion sports app, using AI to generate images and define primary and supporting goals.

Create an AI-assisted, MVP-focused product backlog for a daily multi-sport app using the three R's of user stories to align with vision, personas, and learning.

Generate an outcome-focused product and release goal for the football app minimum viable product, with measurable success indicators: 30% week-one retention, 40% three-times-a-week active users, and 60% onboarding completion.

Learn to order a product backlog of user stories by impact, value, and strategic alignment, using AI guidance to align with the roadmap and release goals.

Learn how to set up Jira from scratch using the Atlassian site, create a passion project, sign up, and choose a scrum template for agile software development.

Explore Jira basics by starting at the backlog and board. Learn how the timeline roadmap tracks sprints and outcomes, and manage product backlog items through your team's workflow.

Generate a CSV backlog from ChatGPT and import it into Jira, mapping epics with fields like epic name, summary, description, priority, and labels in UTF-8.

Import your backlog from a CSV into Jira by first creating epics, then importing stories, mapping epic name and work type, and switch to the old experience for the import.

Learn to generate and refine acceptance criteria using Rovo AI in Jira, turning a backlog into detailed real time football scores criteria, including performance, edge cases, and nonfunctional requirements.

Learn to organize user stories into sprints using velocity-driven and capacity-driven planning. Use historical velocity and task hours to forecast and validate sprint commitments for agile product management with AI.

Learn to define an outcome-focused sprint goal using ai, aligning stories with the release goal and vision for the passion sports app.

Learn how to use AI responsibly in agile teams, balancing machine-assisted backlog refinement and sprint planning with human judgment, ethics, privacy, and sustained collaboration.

Learn to set up Fireflies to transcribe meetings and push notes to Jira, configure site and project, choose issue types, and test the integration for streamlined workflows.

Add Confluence to an existing Jira site via settings or the switcher, select Confluence, and use the same site name to begin with pages during the 30-day trial.

Explore Confluence top and side menus to switch between Confluence and Jira, access Home, Mission Control, spaces, and templates, and leverage automation, calendars, and analytics for agile product management.

Set up meeting transcription with Fireflies.ai by connecting Confluence and Jira, configuring the correct space, and publishing transcriptions as pages to Confluence and Jira for agile product management.

Develop AI product manager skills for agile by learning to transcribe meetings and create Jira and Confluence actions with Fireflies for backlog grooming.

Learn how to create and set up your n8n account to start building workflows, including choosing a plan, entering company details, and inviting teammates.

Explore the canvas to design a workflow from trigger to goal using nodes, AI features, and app actions, then manage history and step execution.

Automate turning project ideas into Jira-ready plans using an AI agent that converts spreadsheet data into agile or waterfall epics and phases.

Automate project planning by configuring an AI planning agent to read data from Google Sheets, determine agile or waterfall delivery, and generate Jira-ready epics and timelines.