AI Agent Email: Keep Untrusted Messages Inside Clear Boundaries
Design an email assistant around read-only access, explicit authority, reviewable drafts, and recovery steps so incoming messages cannot quietly expand its role.
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Automation & AI
Build a small workflow you can inspect and control.
Email automation becomes easier to maintain when its first job is small. A rule might apply a label, a script might prepare a local report, or a model might propose a category. Define the allowed input and the desired output before connecting more tools or adding the ability to send messages.
Use the articles in this collection to plan the boundaries around that job. API and CLI workflows need clear retry behavior and a record of completed work. AI-assisted workflows also need a way to handle ambiguous messages and instructions embedded inside the content they read. A review queue is often a useful first destination for the output.
Start with the API and CLI guide for the operating pattern. Follow with the agent safety article to define authority, then use the triage article to design labels and evaluation examples. The smaller bot and model guides below help translate those principles to a specific kind of workflow without assuming a particular commercial integration.
Articles in this collection
LLM Email Triage: Design Labels, Reviews, and Recovery
Create a practical LLM triage system with a small label set, structured results, realistic evaluation cases, a manageable review queue, and reversible changes.
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Email API and CLI Automation: Build a Reliable Workflow
Plan an email automation workflow with clear event handling, safe retries, useful logs, and a dry run that reveals mistakes before changes reach a real inbox.
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