AI-Assisted Development Team Adoption
Led the rollout of AI coding tools across a 15-person engineering team, establishing workflows, guidelines, and measurable productivity gains.
Technologies Used
Key Features
Project Overview
Introduced AI-assisted development tools and workflows to a 15-person engineering team, moving from skepticism to measurable productivity gains.
The Challenge
The engineering team was curious about AI coding tools but lacked structure. Individual experimentation was scattered—some engineers loved it, others dismissed it. Leadership wanted measurable impact, not anecdotes.
What I Did
Designed and led a phased adoption program:
- Pilot Selection: Started with 3 senior engineers on well-scoped tasks to build internal credibility and gather real data
- Workflow Design: Created guidelines for when AI tools help (boilerplate, tests, documentation) and when they don’t (architecture, security-critical code)
- Custom Prompts: Built a shared library of project-specific prompts that encode team conventions and architectural patterns
- Measurement: Tracked cycle time, PR throughput, and bug rates before and after adoption—not vanity metrics, but business outcomes
Outcome
After 3 months, the team showed a measurable reduction in time-to-merge for standard feature work. More importantly, engineers reported spending less time on repetitive tasks and more time on architecture and design decisions. The guidelines and prompt library became a living resource that the team continues to evolve.