I led the GenAI Innovation Team’s Productivity Solutions group to deliver the Engineering GPT Documentation Specialist, an AI Assistant that automates documentation from Jira ticket data. I drove project milestones, led team check-ins, delivered leadership presentations, and designed conversation workflows and a scalable AI persona to accelerate writer workflows, now live and in KPI measurement.

Overview

I led the GenAI Innovation Team’s Productivity Solutions group to deliver the Engineering GPT Documentation Specialist, an AI Assistant that automates release note drafting by pulling and summarizing Jira ticket data. Acting as both team lead and content designer, I drove project milestones, led team check-ins, and presented progress to leadership while designing the conversation workflows and scalable persona powering this tool. This solution streamlines documentation workflows and sets the stage for future AI-driven content automation projects.

The Problem

Writers needed a faster, more efficient way to draft accurate, consistent release notes. Challenges included:

  • Manual review of Jira tickets, requiring constant navigation between Jira and Confluence

  • Lack of a centralized solution for generating first-draft release notes

  • Inconsistent formatting and tone, increasing editing time and review cycles

  • No clear KPI baseline for measuring time spent on release notes workflows

The Solution

I guided the team through a structured, milestone-driven process to create the Engineering GPT Documentation Specialist:

  • Roadmap and milestone planning: Defined deliverables, timelines, and reporting to keep the team aligned and accountable

  • KPI collection: Measured baseline time required to draft release notes manually, providing data to track AI impact

  • Collaborative prototyping: Facilitated prompt testing and conversation workflow design with writers to refine outputs

  • Content design strategy: Consolidated research into a unified AI persona that delivers clear, formatted release note drafts from Jira ticket numbers

  • Team leadership: Led regular check-ins, drove collaboration, and ensured equal participation across writers and technical stakeholders

  • Executive engagement: Delivered presentations to leadership to align on goals, showcase prototypes, and secure ongoing support

The Outcome

The Engineering GPT Documentation Specialist is now live as a release notes AI Assistant and in KPI measurement to track time savings and quality improvements. Early outcomes include:

  • First-draft release notes generated in seconds, accelerating turnaround times

  • Increased writer efficiency, freeing time for strategic content work

  • Strong positive reception from leadership and writers, with a roadmap to scale the AI Assistant to “What’s New” content and other documentation tasks

Project Roles:

  • Team Lead

  • Content Designer

Previous
Previous

Driving Content and Interaction Design for Informatica's GenAI Hub

Next
Next

Designing an AI Agent to Automate Product Documentation Editing