Success isn't measured in what's delivered.It's measured in what changes because of it.
Across consumer tech, insurance, and HR software, with more on the way.
A closer look at what changed, and how.
Training that kept pace with tools that never sit still.
A fast-moving engineering org was adopting AI dev tools faster than training could keep up. The team behind the tools was buried in requests, and course content went stale almost as fast as it shipped. Usage lagged the investment.
I built a model that moved at the speed of the tools. Core fluency went into self-serve courses linked to live documentation, so they stayed current without constant rewrites. Faster-changing advanced topics ran through a train-the-trainer network that pushed updates to teams quickly. Non-company-specific learning was designed to run as self-launched cohorts, so the learning team never became the bottleneck.
The investment finally showed up in the work. AI tool adoption roughly doubled, the courses cleared 90% satisfaction, and the scalable models launched into pilot and design.
A training org built from scratch that sped up how fast new engineers got productive.
A 2,000-person global engineering organization across the U.S., Canada, and India, onboarding and upskilling with no dedicated function to do it well.
As a founding member of the team, I built the function end to end: onboarding and upskilling programs, a mentorship system, and refresh cycles to keep everything current.
90%+ satisfaction and a measurable drop in time to productivity, across three continents.
Making AI approachable for an org that had never touched it.
AI was new to a traditional engineering organization of experienced developers, with pressure from ownership to show results across several products.
I co-created training on the internal AI tooling and the fundamentals, how the tools work and where they help. Then I drove adoption the way it sticks: through manager enablement and internal communication, so the push came from inside the org, not just from a course.
AI went from unfamiliar to in regular use across engineering and adjacent teams. Even the developers who started with zero AI experience were using it by the end.