Microsoft Shares Lessons Learned on Building AI Copilots
InfoQ Homepage News Microsoft Shares Lessons Learned on Building AI Copilots
Researchers at Microsoft and GitHub Inc. have conducted an in-depth study into the challenges, opportunities, and needs associated with building AI-powered product copilots. The research involved interviews with 26 professional software engineers from various companies responsible for developing these advanced tools.
The race to embed advanced AI capabilities into products is on, with virtually every technology company looking to add these features to their software; however, many problems remain. Orchestrating multiple data sources and prompts can increase the risk of failure cases while testing LLMs is difficult due to their inherent variability. Developers also struggle to keep up with best practices in this rapidly evolving field, often resorting to social media or academic papers for guidance. Safety, privacy, and compliance are major concerns that require careful management to avoid potential damage or breaches.
"A one-stop shop for integrating AI into projects remains a challenge. Developers are seeking a place to get started quickly, transition from a playground to an MVP, connect their various data sources to the prompts, and then move the AI components into their existing codebase efficiently," Austin Henley wrote. "A prompt linter could provide quick feedback. Developers also asked for a library or "toolbox" of prompt snippets for common tasks. Additionally, tracing the effect of prompt changes would be of huge value," Henley continued.
