AI Tools Struggle While Modernizing Ubuntu’s Error Tracker: Developer Reports “Plain Wrong” Code
Artificial intelligence is increasingly used to update and modernize legacy software, but a recent Ubuntu development effort shows that AI-generated code is still far from flawless. Last week, Canonical engineers experimented with Microsoft GitHub Copilot to help modernize the Ubuntu Error Tracker, specifically focusing on bringing its Cassandra database usage up to today’s standards.
While the idea sounded promising—and many open-source supporters celebrated the potential time savings—real-world results were mixed. According to Canonical engineer Skia, Copilot did assist with several updates, but it also produced code that simply didn’t work.
In the Ubuntu Foundations Team’s weekly update, Skia explained that the AI lacked access to a real database environment and wasn’t provided the full schema in the prompt. Because of that, some of Copilot’s output included inaccurate or unusable functions. A few pieces of code were described as “plain wrong,” though the engineer noted that the overall proportion of incorrect results was relatively small.
Despite these issues, the AI-driven approach did provide value. Reviewing and refining Copilot’s suggestions still saved development time compared to rewriting every component manually. The process highlights both the potential and current limitations of AI in software maintenance—especially when dealing with legacy systems and incomplete context.
As AI tools continue to evolve, developers may increasingly rely on them for modernization tasks. However, Ubuntu’s experience serves as a reminder that human oversight remains essential to ensure accuracy, reliability, and long-term maintainability in critical open-source infrastructure.
0 Comments