Modern classifiers and Jev: what actually changes?
From TF-IDF and ModernBERT to GLiClass, LLMs, and TypeSafe's Jev: how they define tasks, produce answers, and handle uncertainty.
AI in the day-to-day work of building software. The useful parts, the expensive parts, and the decisions in between.
From TF-IDF and ModernBERT to GLiClass, LLMs, and TypeSafe's Jev: how they define tasks, produce answers, and handle uncertainty.
A screenshot of Hugging Face's security.txt asks AI agents to go play CyberGym instead. Finally, a use for all those expensive prompt engineering courses.
About 1.5 million characters of prompts and tool definitions appeared online. I went through the files. The permission guidance is funny, the tool documentation mostly makes sense, and somebody has to maintain all of this.
A small change, long Jira ticket, and an AI reviewer that keeps reading. Where the tokens go, why more context makes the review worse rather than better, and why I would give independent services their own repos.