How to build an enterprise LLM application: Lessons from GitHub Copilot

Developing and scaling an application using large language models (LLMs) involves a structured approach that GitHub employed while creating GitHub Copilot, following a three-stage process inspired by the "Nail It, Then Scale It" framework. This process consists of identifying an impactful problem space, delivering a smooth AI product experience, and preparing the application for general availability. The GitHub team focused on enhancing developer efficiency by integrating AI into existing workflows without altering them, initially targeting coding functions in IDEs. Iterative development and user feedback were crucial, with GitHub employing A/B testing and experimenting with features like neighboring tabs. The team also addressed challenges such as optimizing costs and ensuring responsible AI use by incorporating security measures and community feedback. GitHub Copilot's journey from technical preview to general availability illustrated the importance of a focused problem, rapid iteration, and leveraging user insights, leading to significant productivity gains and user satisfaction among developers.