Jan 16
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Pawel Huryn has built more N8N workflows than almost anyone. He walks through building real workflows from scratch - from competitor monitoring to AI agents. Here's everything you need to master the most powerful workflow automation tool. Summary: https://www.news.aakashg.com/p/pawel-huryn-podcast Transcript: https://www.aakashg.com/mastering-n8n-how-to-build-powerful-ai-workflow-automations/ ---- Timestamps 0:00 - Intro 1:55 - Why n8n Matters 3:14 - Building Competitor Monitoring Workflow 8:44 - Cost & Free Version Benefits 12:09 - Ads 13:53 - Workflow Automation Deep Dive 19:57 - Traditional Workflow vs AI Agent 23:13 - Building an AI Agent 31:50 - Ads 34:11 - Agent Workflow Results 40:36 - n8n Best Practices 45:35 - Multi-Agent Research System 49:04 - PM Use Cases & Automation 51:12 - Free Version Hacks 57:57 - Outro ---- š Thanks to our sponsors: 1. Amplitude: The market-leader in product analytics - https://amplitude.com/session-replay?utm_campaign=session-replay-launch-2025&utm_source=linkedin&utm_medium=organic-social&utm_content=productgrowthpodcast 2. Vanta: Automate compliance across 35+ frameworks - http://vanta.com/aakash 3. Testkube: Leading test orchestration platform - http://testkube.io/ 4. Kameleoon: AI experimentation platform - http://www.kameleoon.com/ 5. Pendo: the #1 Software Experience Management Platform - http://www.pendo.com/aakash ---- Key Takeaways 1. n8n combines traditional workflow automation AND AI agent building in one platform - making it more powerful than Zapier or Make for complex automation needs. 2. Real use cases span from simple business workflows to chatbots, automatic competitor monitoring, multi-agent research systems, and inbox workers that take actions based on emails. Sky is the limit. 3. Pawel's competitor monitoring workflow costs $1-2/week using the FREE version of N8N. Just needs Perplexity API ($1-2 for hundreds of calls) and OpenAI credits. Enterprise tools charge $500+/month. 4. Pin your data during development. N8N caches API responses so you don't burn credits while testing workflows. Click the pin icon and N8N uses cached data instead of making new API calls. 5. n8n automatically loops through items - no need to write for-loops or while-loops. When you connect a node with 6 items, N8N repeats the action 6 times automatically. 6. Compress context before sending to LLMs. Pavel cuts 70% of tokens by extracting only summary content and citation URLs from Perplexity results, ignoring irrelevant snippets and metadata. 7. Use ChatGPT to write n8n code snippets. Pavel never writes code blocks himself - just takes a screenshot of the data and asks GPT "how do I compress this information?" 8. Traditional workflows are more efficient (saves tokens, very reliable) for predictable tasks. AI agents are more flexible but use more tokens and can make mistakes. Use workflows when you know the steps. 9. Set GPT reasoning effort to "low" for simple tasks. When you just need formatting or summarization (not complex thinking), low reasoning effort saves tokens significantly. 10. Best practices: Set dedicated error probes to catch errors before they break workflows. Use max iterations to prevent infinite loops. Set retry on fail to 3x attempts. Pin data during development. ---- šØāš» Where to find Pavel Huryn: LinkedIn: https://www.linkedin.com/in/pavelhuryn/ X: https://twitter.com/pavolhuryn Company: https://www.n8n.io šØāš» Where to find Aakash: Twitter: https://www.x.com/aakashg0 LinkedIn: https://www.linkedin.com/in/aagupta/ Newsletter: https://www.news.aakashg.com #n8n #ProductManagement --- About Product Growth: The world's largest podcast focused solely on product + growth, with over 187K listeners. Hosted by Aakash Gupta, who spent 16 years in PM, rising to VP of product, this 2x/week show covers product and growth topics in depth. Subscribe and turn on notifications to get more videos like this.