The state of modern IT and security https://lgkm.org/topics/ai/ 2026-10-29T00:00:00Z Simon Bennett https://lgkm.org/notes/ai-supply-chain-third-parties/ 2026-10-29T00:00:00Z

An AI feature is assembled from parts other people made: a hosted model, downloaded weights, editor plugins, tool servers and SaaS connectors. Each is a supplier with access, and the incidents of the last two years came through exactly those parts. Most third-party registers list only the first.

https://lgkm.org/notes/jev-use-cases/ 2026-10-27T00:00:00Z

Jev is a new kind of AI model that writes no text. It reads something and answers typed questions with a choice, a score or a yes/no probability, in a fraction of a second and for a fraction of a cent. That makes it a good first sorter for alerts, data labels and agent actions, and a poor final judge.

https://lgkm.org/notes/which-language-model-for-which-job/ 2026-10-27T00:00:00Z

Large language models now come in four kinds, not one: frontier models for the hardest work, workhorses for most of it, small fast models for volume, and open-weight models you run yourself. The names change every month and the kinds do not, so choose by job, test one size down, and write policy about kinds rather than names.

https://lgkm.org/notes/agents-are-the-new-insiders/ 2026-10-19T00:00:00Z

An AI agent that can read mail, call APIs and change records is a privileged insider that can be talked into things. Treat it like one: an owner, the least access that works, and a record of what it did.