Preparing study materials from a recorded lecture is a good example of work that generative AI has simplified substantially in a short time. Two years ago, I manually moved the recording, transcript, slides, and three core prompts between separate tools. Today, one instruction can turn a recording and its slides into a checked summary, material discussed beyond the presentation, a glossary, and a finished PDF for students.
Open models have made artificial intelligence more accessible, but useful deployment still depends on data, integration and honest evaluation. It was a pleasure to bring this practical perspective to the general public at Inovujeme Plzeň 2026 Next Level and to appear alongside such a strong group of speakers. I thank SIT Port for the organisation and for creating a lively workshop setting at TechTower.
Historical archives contain valuable evidence, but scanned documents are difficult to search when their metadata is incomplete or inconsistent. At the C4DHI Anniversary Workshop, I presented a workflow that uses large language models to extract structured metadata from scanned NATO archival documents. The talk focused on noisy OCR, multilingual records and the need to preserve evidence for human review.
Complex research tasks do not fit into a single prompt: they need tools, intermediate checks and an inspectable sequence of steps. These workshop materials introduce agentic AI as a workflow for digital humanities and archival research. They connect an Oxford research stay, CLARIN collaboration and practical work with NATO archival documents.
