AI / A CONCEPT NOTE
External Integrations
connecting AI agents to real-world APIs and SaaS platforms
Overview · mechanism
pitfall · examples
01 / THE SHORT VERSION
The idea in a few sentences.
External integrations are the bridges between your AI system and the outside world — Slack for notifications, Jira for ticket creation, GitHub for code changes, Stripe for billing, or any REST/GraphQL API. The agent doesn't just generate text; it calls real services to take action. Each integration needs authentication (OAuth, API keys), error handling, and rate limit awareness.
02 / FOLLOW THE MECHANISM
How an agent calls an external service
Agent decides
the LLM determines it needs to create a Jira ticket based on the user's request.
Tool definition
the integration's schema describes the endpoint, required fields, and auth method.
Executor
makes the authenticated API call: POST /rest/api/3/issue with the JSON payload the agent generated.
Response handling
the API response (ticket ID, error, rate limit) is fed back to the agent for its next decision.
04 / COMMAND NOTES
Read the command, then the result.
Inspect the flags and arguments before trying an example. Snippets can need local setup, replacement values, or resources in your own environment.
post a message to Slack via API
curl -X POST -H 'Authorization: Bearer $SLACK_TOKEN' -d '{"channel":"C01234","text":"Agent alert"}' https://slack.com/api/chat.postMessage05 / CHECK YOURSELF
Could you explain External Integrations to a teammate?
Try it out loud in two sentences: what it is, and the one detail that changes the picture. If you stall, the gap is the part to reread.
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