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Scientific Agentic Engineering

BSSw Fellowship License: MIT License: CC BY 4.0 Website

Methodology and framework for integrating AI agents into scientific software development workflows.

About

This project develops practical guidance for scientific software teams adopting AI coding agents. It addresses a gap in the community: while AI tools are rapidly being adopted, there is little principled methodology for integrating them responsibly into scientific workflows where correctness, reproducibility, and domain expertise matter.

Author: Victor Weeks, NSF National Center for Atmospheric Research (NSF NCAR)

Project Deliverables

  • Framework — Principles and patterns for responsible AI-agent integration in scientific software
  • Tutorials — Hands-on guides with interactive examples (coming October 2026)
  • Community Catalog — Curated collection of tools, patterns, and case studies (coming October 2026)
  • Workshops — Recordings and materials from community events (coming April 2027)

License

  • Code (layouts, components, scripts): MIT
  • Content (documents, tutorials, guides): CC-BY-4.0

Acknowledgment

This work is supported by the Better Scientific Software Fellowship Program, funded by the U.S. Department of Energy and the National Science Foundation.
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