The interesting challenge with AI assistants inside technical tools is grounding the responses in real system signals. If the model is just interpreting natural language prompts, it tends to produce generic advice. But if the assistant is tied directly to system telemetry or query results, it becomes much more useful.

In experiments I’ve been running, the pattern that seems to work best is deterministic signals first, then a constrained AI layer that interprets those signals rather than inventing analysis.