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Building an AI agent is like onboarding a new teammate. You connect the systems it needs, teach it how your business works, test the result, and then deploy it with the right level of oversight. In V3, this happens across a few focused surfaces:
  • Agents define who is responding and how that agent is deployed.
  • Knowledge stores facts the agent can retrieve.
  • Skills store reusable process and tool-use instructions.
  • Tools let the agent take actions and access live systems.
  • Operator helps your team configure and inspect the workspace.
  • Sandbox lets you test a specific agent before customers see the result.

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The Loop

  1. Connect - Add channels, integrations, Knowledge sources, and tools.
  2. Teach - Write Persona, Skills, Guardrails, Knowledge, and behavior settings.
  3. Test - Validate the agent in Sandbox, regenerate proposed replies, and inspect Activity.
  4. Deploy - Publish the agent, choose triggers, and tune automation controls.
Repeat the loop whenever you add a new channel, change a policy, add a tool, or see a repeated escalation.

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From Copilot To Autopilot

Copilot means the AI drafts replies for human approval. Autopilot means the AI can send confident replies automatically and escalate the rest. Moving toward autopilot is not a single switch. It is a sequence of narrow expansions:
  • Add the facts the agent needs.
  • Add the Skills that explain how to handle recurring situations.
  • Give the agent only the tools it needs.
  • Test common and edge-case messages.
  • Publish changes and monitor real activity.

Connect

Add sources, integrations, and tools.

Teach

Write Knowledge, Skills, Persona, Guardrails, and Behavior.

Test

Validate behavior before publishing.

Deploy

Publish and control automation safely.