Last year I kept seeing the same pattern in agtech and “AI assistant” demos: a chatbot wrapped around a generic model, a handful of PDFs, and a disclaimer nobody reads.
I'm a developer, not an agronomist. But I'm working on two related projects — a grounded RAG platform (grounded-llm, private repo) and its first production-shaped domain pack: a horticulture assistant built on hundreds of articles from the Russian journal Plodovodstvo i vinogradstvo Yuga Rossii (apple, pear, plum — on the order of ~500 source articles, not five blog posts).
I didn't want another “ChatGPT for gardeners.”
I wanted answers that behave like someone who actually read the literature — and admits when the literature doesn't cover the question.
That gap turned into months of engineering. I'm sharing the story in public; the full corpus and codebase stay private.
