AI Learned My Email Habits
Summary
An email triage agent has been developed and deployed to autonomously manage both work and personal emails. This agent operates daily, archiving non-essential correspondence based on learned user preferences. The training process involves granting the agent access to emails and a blank "memory" page it can edit. The agent proposes emails for archiving, and the user provides corrections, which the agent uses to generate a set of archiving rules. Initially, the user corrected the agent for a few days, but after a couple of weeks, the agent achieved sufficient accuracy to operate without requiring user approval, automatically archiving emails.
Key takeaway
For AI Engineers developing personal automation tools, consider implementing an iterative feedback loop where users correct agent proposals. This method allows the agent to generate robust rules and achieve autonomous operation, significantly reducing manual oversight and enhancing user productivity in tasks like email management.
Key insights
An email triage agent can learn user preferences to autonomously archive non-essential emails.
Principles
- Iterative correction refines agent rules
- Autonomous operation is achievable
Method
Grant email access and editable memory to an agent. Agent proposes archives; user corrects. Agent generates rules from corrections. Repeat until autonomous.
In practice
- Train agents with user feedback
- Automate email archiving
- Reduce daily email load
Topics
- Email Automation
- AI Agents
- Preference Learning
- Email Triage
- Automated Archiving
Best for: AI Engineer, Software Engineer, AI Student
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