Building AI Agents for Google Workspace

Why Google Workspace is the highest-leverage starting point

Google Workspace is where most knowledge work already lives. Email, calendars, shared drives, and documents are the connective tissue of every team. An AI agent that operates inside Workspace can save hours per person per week the moment it ships — no migrations, no behavior change required from the team.

Four agents we teach inside the Bootcamp

• Inbox triage agent: classifies, labels, drafts replies, and routes high-priority threads to Slack or SMS.
• Scheduling agent: parses meeting requests, checks calendars, proposes times, and books on confirmation.
• Drive librarian: renames, tags, and files new uploads into the right folder structure with consistent naming.
• Docs drafter: turns voice notes or bullet briefs into formatted proposals, SOPs, and meeting recaps in Docs.

A simple architecture that scales

Use a workflow runner (n8n, Zapier, or Make) for triggers and Workspace API access, an LLM for reasoning and drafting, and a structured prompt that defines the agent's role, guardrails, and output format. Store the agent's task list and memory in Sheets or Notion so non-engineers can audit and tune behavior without touching code.

Guardrails that matter in a real business

Agents that touch email and calendars need explicit human-in-the-loop checkpoints for anything that leaves the company, spends money, or schedules with executives. Start every agent in suggest-only mode for the first week, then graduate the safe paths to auto-send once you have evidence the agent behaves.