How I’d Learn n8n if I had to Start Over in 2026

Uploaded: 2025-12-10
In this video, the creator shares insights on how to effectively learn automation with a focus on understanding workflows before diving into AI, emphasizing the importance of foundational knowledge and strategic planning to build efficient systems that deliver real value. Key concepts include the layers of automation, the transition curve of learning, and the significance of tracking results to build trust and long-term relationships with clients.

channel	AI Automation, Nate Herk
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This video presents a practical roadmap to learn Naden and build AI automations: prioritize deterministic workflows before agentic AI, master JSON/APIs/webhooks, and focus on testing, monitoring and ROI-driven delivery. It warns against starting with AI too soon and against tutorial paralysis, advocating process design and iterative proof-of-concepts.

– Start with workflows: rule-based automations are predictable and deliver fast ROI.
– Master data plumbing: JSON, HTTP requests and webhooks move and shape data.
– Context engineering: LLMs only predict words—give precise context and guardrails.
– Iterate and prove value: log executions, stress-test edge cases, and report time/money saved.

Quotes:

Do not start with AI. Start with workflows.

An LLM doesn’t know your business — it only predicts the next word.

If I had 6 hours to chop down a tree, I’d spend the first four sharpening the axe.