Abstract

Product teams spend countless hours transforming ideas into delivery artifacts—meeting notes become requirements, requirements become backlog items, backlog items become sprint plans, and progress updates are shared across stakeholders. While modern tools help manage this process, much of the work remains manual, fragmented, and repetitive.

What if an AI agent could participate as a member of the product team?

In this session, we explore how Hermes Agent, combined with Jira, Confluence, Slack, Git platforms, and MCP-enabled tools, can create an AI-first product workflow that spans the entire product lifecycle. Rather than relying on predefined automations, Hermes can understand intent, gather context, select the appropriate tools, and execute multi-step workflows across systems.

Through a live demonstration, we'll follow a real product request from initial discussion to delivery-ready artifacts. We'll show how an agent can transform conversations into structured requirements, generate and refine Jira stories, coordinate documentation, communicate progress, and support decision-making throughout the delivery process.

We'll also discuss:

•⁠ ⁠The shift from workflow automation to agentic execution

•⁠ ⁠How MCP enables agents to discover and use enterprise tools safely

•⁠ ⁠Designing human-in-the-loop approval processes

•⁠ ⁠Lessons learned when introducing AI agents into product organizations

Takeaway

Attendees will leave with a practical understanding of how agentic systems can augment product teams, reduce operational overhead, and enable a more AI-first approach to product delivery—while keeping humans firmly in control of product decisions.