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AI Agent Prompting for n8n: The Best Practices That Actually Work in 2025
15 min read5 days ago
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Why Most Prompting Approaches Fail
According to Anthropic’s Context Engineering Research, in 2025, it’s not “prompt engineering” that matters — it’s “context engineering.” The question is no longer “how do I craft the perfect prompt,” but “which configuration of context leads to the desired behavior.”
I’ll take you through what current research (Anthropic, OpenAI, Google, Wharton) says about AI agent prompting — and how to implement it specifically for n8n workflows.
What you’ll learn:
- System Message vs User Prompt (and why wrong separation doubles your token costs)
- The five core techniques that actually work in 2025 (with research backing)
- Advanced patterns (Chain-of-Thought, RAG, Structured Outputs, Tool Use)
- Why you should generate prompts WITH the model instead of building them manually
- Model-specific considerations (only what’s actually relevant)
- Production patterns (testing, error handling, token optimization)
