Building a Daily Briefing Agent
Morning digest: news + calendar + email summary delivered automatically.
What Is a Daily Briefing Agent?
A daily briefing agent runs at a scheduled time each morning, gathers information from multiple sources (calendar, email, news), synthesizes it with an LLM, and delivers a personalized summary. It is the classic example of a scheduled personal agent.
Briefing Architecture
The briefing pipeline has five stages:
- Trigger: 8am cron job fires the agent
- Fetch: gather calendar events, unread emails, news headlines (in parallel)
- Synthesize: LLM creates a cohesive briefing from all data
- Personalize: adapt tone and content to user preferences
- Deliver: send via email or Slack DM
from dataclasses import dataclass, field
from typing import List, Dict, Any
@dataclass
class DailyBriefingData:
date: str
calendar_events: List[Dict] = field(default_factory=list)
unread_emails: List[Dict] = field(default_factory=list)
news_headlines: List[Dict] = field(default_factory=list)
weather: Dict = field(default_factory=dict)
briefing_text: str = ''
delivery_status: str = 'pending'
print('Daily briefing data structure defined')All lessons in this course
- Always-On Agent Design Patterns
- Proactive Notification and Alert Systems
- Context Persistence Across Sessions
- Building a Daily Briefing Agent