Week 8: Generative AI in research and coding

Author

Affiliations

Jelmer Poelstra

CFAES Bioinformatics Core, Ohio State University

Dept. of Plant Pathology, Ohio State University

Week starts on

October 12, 2026

Page last modified

October 14, 2026

1 Overview

This week, we will cover background on generative AI (genAI), how to use it responsibly and effectively in research and coding, and how to write good prompts for chat-based genAI tools.

2 Learning goals

This week you will learn:

Generative AI in research and coding

Basic background of generative AI (genAI) and large language models (LLMs)
About Ohio State’s genAI tools, and genAI use in this course and in research
How chat-based and agentic AI differ
Example prompts and outputs with Gemini, including Deep Research
How to write effective prompts
Tips and pitfalls when using genAI, especially for coding
What to use (and not use) genAI for, and why it rewards expertise

3 Readings

Sen Gupta (2025): PhD training needs a reboot in an AI world
King et al. (2026): Ten simple rules for effective use of generative AI for code development in environmental science

4 Exercises & assignments

None this week. If you have time to spare, and want to explore more, see the further resources below.

5 Further resources

Key OSU resources:
- Department of Plant Pathology’s GenAI policy for grad students (PDF on Canvas)
- Ohio State’s AI landing page
- Responsible use of AI
- AI in Research Guidelines
Lenharo (2026): Is AI ruining our skills? Early results are in — and they’re not good
Dewar (2026): Large Language Models for Science and Research: A Practical Guide
8-minute video: Large language models explained briefly
Claude Academy : Multiple free short “courses” (series of videos, mostly) by Anthropic on using AI.
For more, see the AI section of the Resources page.

References

Dewar, James M. 2026. Large Language Models for Science and Research: A Practical Guide. Version 1.1. Zenodo. https://doi.org/10.5281/zenodo.19371506.

King, Rachel A., Laurel Abowd, Carlo W. Broderick, et al. 2026. “Ten Simple Rules for Effective Use of Generative AI for Code Development in Environmental Science.” PLOS Computational Biology 22 (8): e1014627. https://doi.org/10.1371/journal.pcbi.1014627.

Lenharo, Mariana. 2026. “Is AI Ruining Our Skills? Early Results Are in — and They’re Not Good.” Nature 655 (8121): 15–16. https://doi.org/10.1038/d41586-026-01947-1.

Sen Gupta, Alex. 2025. “PhD Training Needs a Reboot in an AI World.” Nature 647 (8088): 27–28. https://doi.org/10.1038/d41586-025-03572-w.