I've been running my automation on n8n for about a year now. Before that, I was paying Zapier $50/month for workflows that took me 10 minutes to rebuild in n8n. Here's what I learned.
The Context
I've been running AI-assisted workflows for about 8 months now. Not as an experiment—this is part of my actual work. I process content, generate reports, and handle communication prep using LLMs integrated into n8n.
Here's what actually works.
What Works: Structured Input, Structured Output
AI is good at transformation. Give it structured input and ask for structured output, and it's remarkably consistent.
Example: I feed meeting transcripts into a Claude node that extracts action items, assigns owners based on context, and formats everything for our project management tool.
The key is the prompt structure. I use a template that includes:
- The raw transcript
- Output format specification
- Examples of good outputs
- Error handling instructions
What Works: Human-in-the-Loop
Fully automated AI is risky. I always include a human review step for anything that leaves my system.
My content workflow: AI generates a draft → I review and edit → AI helps with formatting and distribution → I do final approval.
The AI handles the boring parts. I handle the judgment calls.
What Doesn't Work: Open-Ended Generation
I tried having AI write complete blog posts. The results were... fine. Competent but generic. It took me almost as long to edit them into something worth publishing as it would have to write from scratch.
AI is a great research assistant and a mediocre writer. Use it accordingly.
The Setup
If you want to try this, start with n8n's OpenAI or Anthropic nodes. The HTTP Request node works too if you need more control.
Key lessons:
- Always set max tokens to prevent runaway generation
- Use system prompts to constrain behavior
- Log everything for debugging
- Plan for API failures (they happen)
The Bottom Line
AI in workflows isn't magic. It's a tool that excels at specific tasks and fails at others. The value comes from knowing which is which.
Conclusion
This is what works for me. Your mileage may vary, but the principles should translate. Let me know if you hit any snags.
Questions? Find me on LinkedIn. I actually respond.