Neon's engineering team has been leveraging Cursor to enhance their coding efficiency across languages such as TypeScript, Go, Rust, and Python, finding particular success with features like Cursor Tab for context-aware suggestions and Agent Mode for scaffolding and debugging. Cursor has proven helpful in understanding unfamiliar code and modernizing legacy systems, while its swift adoption of new models is appreciated. However, limitations exist, including issues with context awareness, incorrect suggestions, and reliability challenges in large files. The team suggests that Cursor could become indispensable with improved context sensitivity, integration with project-specific details, and a more comprehensive feedback loop. Despite its shortcomings, Cursor has already delivered value by reducing ramp-up time and accelerating repetitive tasks, although the team is not yet using it for end-to-end production code. Neon, a serverless Postgres database, effectively supports AI IDEs like Cursor, emphasizing the tool's potential when integrated into their workflows.