To effectively introduce AI to engineering teams, it is essential to set clear objectives, employ a structured approach, and track progress using data-driven insights. This ensures a smooth adoption process, enhancing productivity, code quality, and the overall developer experience.
Engineering leaders considering the rollout of GenAI tools like Copilot can use Flow to scientifically validate the investment and identify potential pitfalls. Flow helps teams align on realistic outcomes, set a minimum 90-day pilot timeframe, and structure the adoption process effectively.
For the rollout, implement GenAI tools across entire teams and establish test and control groups to compare results. Maintain consistent conditions across both groups, considering variables such as work types, geographies, employment status, and experience levels, to ensure accurate assessments.
Measure improvements using the Team Health Insights report, focusing on metrics like coding days, impact, and deployment frequency. Engage the team in discussions about the results to gain insights and determine GenAI’s overall impact. Use Flow metrics to build a solid, objective business case if deciding to move forward.
