How to Measure Generative AI Coding Impact and Integration
Read time: ~3 mins
Introduction
GenAI tools hold the promise of significantly boosting efficiency, especially in a tight economy with limited headcount. Tools like GitHub Copilot could enable your team to move faster and deliver more. However, these tools also present challenges that could impact code quality. Balancing these pros and cons is crucial.
In this white paper, we’ll explore practical steps to safely and effectively integrate GenAI tools into your workflow while boosting teams learning culture and sense of belonging.
A data-driven approach to integrating GenAI tools
"The vast majority of executives are pushing engineering leaders to adopt GenAI, but then these leaders ask me, “Where in the data does it show that GenAI is actually improving software development? How can I prove that our investment is actually paying off?"'
-David Farah, Field CTO, Flow
1. Start with a goal
Zeroing in on an improvement-focused goal will position your team to get specific about how your GenAI tool can help drive this improvement and how it should be added to your processes.
2. Establish guardrails
Creating, understanding, and enforcing your guard- rails starts with understanding your business needs and regulatory requirements. Remember that a rule without an enforcement mechanism is just a suggestion that’s going to be ignored.
3. Take an incremental approach to your rollsouts
Lead your organization in adopting an incremental, experimental approach in which you work on one small improvement at a time and then move on to the next. Focus on and prioritize those improvements that will generate the most value across the board.
4. Measure Results
Measurement before and after each improvement is an absolute must. Establish a baseline metric by which to measure value created, measure improvement on that metric as the team goes to work, and then analyze the final results to determine value created by your improvement and to identify the next improvement to be worked on.
This data-driven approach can free your software development organization from the risks of GenAI tool implementation and let them methodically, confidently receive the benefits of the technology. This approach is especially powerful when paired with Pluralsight Flow.