Prompt Engineering for English
LLMs are fundamentally language models, trained on the texts your field studies and making the kinds of rhetorical moves your field critiques. English majors are unusually well-positioned to both build with them and interrogate them.
Where this is showing up in English
- Writing tools like Sudowrite, NovelCrafter, and Lex are being used (and fought over) by working novelists, screenwriters, and journalists.
- Digital humanities research — including the HathiTrust Research Center and the ongoing NLP for Digital Humanities (NLP4DH) conference — combines classical corpus methods (Voyant, MALLET) with modern LLMs for close reading at scale.
- JSTOR Labs and Semantic Scholar have launched LLM-powered scholarly search that's changing how literary research is done.
- Ongoing debates — the Authors Guild v. OpenAI lawsuit, the NYT v. OpenAI case, MLA's guidance on AI in writing — are actively shaping what authorship, voice, and fair use mean in a generative-AI world.
Projects you could build in this course
- A tool that performs close reading or stylistic comparison across a corpus of texts
- A writing assistant tuned to a specific style guide, genre, or author's voice
- A RAG system over a literary archive or scholarly corpus for research queries