2 posts tagged with "attention"

The retrieval logs are clean. Recall@10 against your hand-labeled query set has not regressed in months. The answer-quality dashboard says faithfulness is holding above 90%. Then a customer pastes a question into your support agent, the gold passage is right there at position 7 of 12 in the assembled prompt, and the model answers as if it were never retrieved.

The retrieval team will tell you the chunk was there. The prompt team will tell you the prompt was correct. Both are technically right. The model attended to the first thousand tokens, attended to the last thousand tokens, and skimmed the middle band where the answer lived. Your pipeline is hitting a positional attention bias that neither team owns, neither dashboard tracks, and neither benchmark catches.

The first generation of AI assistants waited politely. You typed, they answered. The second generation does not wait. It watches your calendar, scans your inbox, reads your repo activity, and surfaces "you should know about this" interruptions before you have asked for anything. The pitch is compelling and the demos are mesmerizing. The retention curves, once these features ship, are not.

There is a number nobody puts on the launch slide: the user has a daily ceiling on unsolicited AI updates, and it is roughly three to five across all sources combined. The proactive agent that ships its tenth notification of the week is the same agent the user mutes by Friday and uninstalls the following month. This is not a UX polish problem. It is the architectural blind spot of the entire proactive-AI category, and it deserves a name: the notification budget.