Bioinformatics pipelines, code libraries, and other tools are ubiquitous in microbiology. Even armed with documentation and preexisting online resources, learning how to use these tools can be overwhelming to trainees who may be unfamiliar with computational vocabulary and concepts. Additionally, teaching these methods can be overwhelming to instructors who need to anticipate errors, bugs, and other obstacles they may encounter. Generative AI tools such as ChatGPT have the potential to smooth the learning process by providing real-time student-specific feedback and creating examples from which to learn. I will present a learning activity where students will use ChatGPT to identify the cause of an error and generate synthetic examples of error-producing inputs in a bioinformatics sequencing pipeline. This will demonstrate that instead of simply fixing bugs, generative AI has the potential to help students develop broader pattern-recognition skills and deeper understanding of the tools they use.
