Why your AI workflow fails: 3 Common Mistakes in n8n and how to fix them.”

Описание: How To Make Your n8n AI Workflows Production-Ready And Reliable

Learn how to make your n8n workflows truly production-ready with secure webhooks, API authentication, retry logic, and real-world error-handling patterns. If your workflow works during testing but randomly breaks when real users hit it, this video shows you exactly how to fix that.

In this tutorial, you’ll learn why “naked webhooks” are a major security risk and how to protect your automations using Header Auth API keys, Basic Auth, HMAC signatures, and JWT authentication. I’ll walk you through which method to choose based on whether callers are trusted, untrusted, or user-specific — and show practical examples of securing an n8n webhook endpoint.

We’ll also cover designing for flaky APIs. You’ll learn how to enable retry logic inside n8n, when to retry, when not to retry, and how to diagnose whether the issue is with your configuration or the external API provider.

Finally, we’ll implement proper error visibility using the Global Error Trigger node, email/Slack alerts, and the Stop & Error node. These patterns ensure you always know when failures happen — a core principle of defensive workflow design.

Whether you’re building AI automations, front-end integrations, or production-grade services, these techniques will make your n8n workflows more reliable, secure, and resilient.

⏱️ CHAPTERS

00:00 Why your n8n workflows break in production
00:25 The “naked webhook” problem
02:00 Securing webhook entry points
04:15 API Key (Header Auth) setup
06:20 Basic Auth vs Header Auth
07:10 HMAC signed requests
08:00 JWT for user-based access
09:00 Implementing retry logic
11:00 Handling flaky APIs
12:00 Global Error Trigger alerts
13:30 Stop & Error node
14:00 Production mindset: defensive design
Email: [email protected]

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