JULIE HODGEEnterprise AI Transformation Leader
Julie Hodge

Featured Case Studies

Problem → What Julie built → Result

Time-to-Value Application

Problem
Teams had no fast, shared way to see where value was stalling across customer engagements.
What Julie built
Julie prototyped the UI in v0, moved development into Codex, connected enterprise data and source control, debugged using AI coding agents, and deployed to AWS.
Result
A working AI-enabled application that surfaces time-to-value signals — built hands-on, end to end.
Prototype → productionAI coding agentsDeployed to AWS
Field→
Requirements→
Jira→
Product & Eng→
Release

Product-to-Field AI Operating Model

Problem
Field insight and product roadmaps were disconnected, so the right AI capabilities were slow to ship.
What Julie built
Established a closed loop: field feedback → requirements → Jira / backlog → product & engineering → release.
Result
A durable operating model connecting the field to the roadmap for continuous AI delivery.
8 AI-native products600+ field / Jira requirements
Traditional Delivery
→
AI-First Delivery

AI-First Delivery Methodology

Problem
Traditional delivery could not keep pace with what AI made possible.
What Julie built
Redesigned the methodology from traditional delivery to an AI-first delivery model across the organization.
Result
A new way of working adopted across a large, distributed delivery team.
Under six months100+ deliverables30+ contributors
Pilot
Champions
Adoption
Measure
Scale

Enterprise AI Adoption

Problem
AI pilots existed, but adoption was not reaching scale or sticking.
What Julie built
Built a staged model: pilot → champions → adoption → measurement → scale, with enablement and governance throughout.
Result
AI adoption extended across a global, 300+ person organization.
300+ customer-facing professionalsGlobal operating model