I Cut AI Agent Handoff Payloads by 87%—Then the Important Questions Disappeared

Description and use

Reduce AI agent handoff payloads by 87 % by separating short notifications from full messages stored in a pull‑based inbox. Prioritize unanswered questions to ensure critical items are delivered in the first batch.

Problem

Large AI agent handoffs were bloating context windows, causing repeated injection of full messages and missing critical unanswered questions in early turns.

Outcome

Payload per handoff dropped from 969 bytes to 123 bytes (87.3 % reduction). The first notification batch now reliably contains at least one unanswered question, improving operational reliability.

Workflow

• 1. Hook receives full handoff text. 2. Hook generates a short notification containing type, state, sender, summary, and inbox path. 3. Notification is pushed into the active context. 4. Receiving agent pulls full message from inbox only when needed. 5. Prioritize unanswered questions, then state changes, answers, accepted work, progress/completion. 6. Enforce limits: max 5 notices, max 3 redeliveries, ~1,000 bytes budget, but always show highest‑priority item even if it exceeds budget.

Evidence

Replaying 240 handoffs reduced the average payload per handoff from 969 bytes to 123 bytes: an 87.3% reduction.

Source

After the change, the first batch carried at least one unanswered question instead of none.

Source