AI coding assistants are reshaping how research software is built and maintained, but most guidance targets industry, not research cyberinfrastructure (CI). 

During this webinar, Komal Thareja, a Senior Research Software Engineer at RENCI at the University of North Carolina at Chapel Hill, will fill that gap with hands-on demonstrations tailored to CI roles, using real examples from NSF Major Facility projects. Topics include scaffolding scientific workflows, generating APIs from OpenAPI specs, building publication dashboards, and creating presentation materials. Designed for PIs/managers, developers, and students, the session highlights workflows you can adopt immediately, common AI failure modes, prompt techniques that improve results, and security considerations for using AI with research code. No prior AI experience required.

Key Takeaways for attendees:

• Role-specific AI workflows for research CI, drawn from real NSF Major Facility projects
• Practical guidance for PIs/managers, developers, and students
• What AI gets wrong in research software—and how to recover
• Prompt engineering techniques that improve scientific software outcomes
• Security best practices for using AI with research code and infrastructure

Register for the Event