Cross-Pollination Architecture Specification

> **PULSE V1 — Wave 1 Deliverable [A3]** > Status: COMPLETE | Author: Clawdbot Agent | Date: 2025-07-29 1. [Overview](#1-overview) 2. [Prediction Engine](#2-prediction-engine) 3. [Safety Rails](#3-safety-rails) 4. [ACC Integration — Swipeable Prediction Cards](#4-acc-integration--swipeable-prediction-cards) 5. [Autonomous Mode](#5-autonomous-mode) 6. [Push Notifications](#6-push-notifications) 7. [Feedback Loop & DPO Training](#7-feedback-loop--dpo-training) 8. [API Reference](#8-api-reference) 9. [Data Models](#9-data-models) 10. [Deployment & Configuration](#10-deployment--configuration) Cross-pollination is the system by which PULSE agents **proactively generate, predict, and execute work** without explicit human instruction. A personal Twin model predicts the user's likely next actions, routes them to the appropriate agent channel, and optionally executes autonomously — all while maintaining strict safety rails and a human-in-the-loop escape hatch. Traditional AI assistants are reactive: the user speaks, the assistant responds. Cross-pollination inverts this. The system observes the user's patterns (time of day, project state, recent conversations, unfinished tasks) and **generates the next move before the user asks**. The user's role shifts from director to reviewer — swipe right to approve, swipe left to dismiss. This is the core mechanism behind the "Age of Leisure" vision: agents that work while you walk.