By BrainSoft | 31 October 2026
By BrainSoft | 5 28 October 2026
Almost every LLM feature starts the same way: someone writes a prompt, it works on three examples, and then it falls apart on the fourth. The reflex is to reach for fine-tuning. Sometimes that is right. Often it is a way to spend two weeks and a few hundred dollars to fix a problem that a better prompt and a validation loop would have caught in an afternoon. ...
A client asked us to wire an LLM to their internal docs last year. About 200 markdown files, a few PDFs, a wiki export. Not a huge corpus. The instinct is to reach for a managed vector database and a framework, but for a knowledge base this size you can build the whole retrieval loop yourself in an afternoon and understand every part of it. That matters when answers come ...
Someone on the product side has seen a demo and now wants the app to summarise tickets, or draft replies, or pull structured data out of messy PDFs. The app is three years old, has real users, and nobody wants to hear the word "rewrite". Fair. You do not need one. You need a boundary. Add the LLM as a separate service behind one narrow inte ...
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