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Operations Guide

AI API Integration Checklist Framework for Production Systems

60% of AI projects fail due to integration obstacles. This framework provides a 24-item checklist across 6 phases with risk assessment and validation criteria for production API integrations.

Direct answer

60% of AI projects fail due to integration obstacles. This framework provides a 24-item checklist across 6 phases with risk assessment and validation criteria for production API integrations.

Fast path

  1. Planning: Obtain API credentials, review documentation, estimate traffic/costs, check compliance.
  2. Development: Implement auth layer, request handlers, error handling, caching, input sanitization.
  3. Testing: Write unit tests (>80% coverage), integration tests, load testing, security penetration.

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Implementation Steps

  1. Planning: Obtain API credentials, review documentation, estimate traffic/costs, check compliance.
  2. Development: Implement auth layer, request handlers, error handling, caching, input sanitization.
  3. Testing: Write unit tests (>80% coverage), integration tests, load testing, security penetration.
  4. Deployment: Create deployment checklist, configure rate limiting, enable audit logging, staging deploy.
  5. Monitoring: Set up latency monitoring, error rate alerts, cost tracking dashboards.
  6. Maintenance: Schedule key rotation (90 days), quarterly security review, documentation updates.

Related Guides

Use these adjacent playbooks to keep the same workflow connected across discovery, conversion, and execution.

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