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How to Build AI Agents INSTANTLY with n8n’s NEW NATIVE AI Builder

Mark Kashef

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How to Build AI Agents INSTANTLY with n8n’s NEW NATIVE AI Builder

37 546 просмотров · 1 год назад
Mark Kashef
84,6 тыс. подписчиков
37 546 просмотров · 1 год назад
🚀 Gumroad Link to Assets in the Video: https://bit.ly/4fWiflA 🤖 Join My Community for Exclusive Content ➡ https://bit.ly/3ZMWJIb Work With Us: https://www.promptadvisers.com/ What if you could type a plain-English prompt and get a production-ready automation in seconds? In this 22-minute hands-on demo, I put n8n’s brand-new AI Assistant Builder (Prompt → Workflow) through real projects—showing how it plans the architecture, wires nodes, explains each step, and even helps you generate mock data to test. You’ll see three builds: a lead-qualification pipeline (Calendly → GoHighLevel with OpenAI + Perplexity + Outlook), a Fireflies-powered meeting analysis that branches to a nurture sequence, and a multi-agent LangChain “content swarm” where one agent uses another as a tool. I also cover when to use an AI Agent node vs a simple LLM call, how to fix red-state nodes fast (credentials & params), and how to iterate with the sidebar co-pilot. Note: this feature is rolling out in phases—if it’s not in your account yet, it’s coming soon. Perfect for beginners leveling up and builders who want to go from idea → working automation without MCP servers, giant JSONs, or endless copy-paste. ⏳ TIMESTAMPS: 00:00 – n8n’s AI Assistant Builder changes everything 00:34 – Why old hacks broke (giant prompts, JSONs, MCP) 01:00 – What Prompt → Workflow actually does 01:18 – Rollout note: phased access & where to find it 01:34 – Prompting tips: name your tools & outcomes 02:00 – Built-in templates (Invoice, RAG assistant) 02:36 – Still possible: start manually if you prefer 02:49 – Meet the sidebar co-pilot & build log 03:22 – Test #1 prompt: Calendly → GoHighLevel lead qual 04:18 – Plan → nodes → connections auto-wired 05:12 – Post-build checklist: creds, params, models 06:01 – Flow explained (trigger → research → score → store → notify) 06:46 – Clearing red errors & picking models 07:20 – Prefilled prompts, placeholders, dynamic vars 08:10 – Generate & pin mock Calendly JSON; execute run 09:04 – Results review: what worked, what to tweak 10:42 – 60–70% head start; what’s left to ship 11:20 – Architecture: AI Agent vs plain LLM node 11:58 – Extension idea: Fireflies transcript → nurture path 12:40 – Swap in community node; get transcript step 13:10 – Sales-readiness (BANT) prompt + drafted emails 14:56 – New canvas: LangChain agent brief (autonomous handler) 15:29 – Build output; wrong trigger spotted 16:02 – Iterate in chat: replace webhook with Form node 16:31 – Open form, submit, pin data, re-run 17:59 – Test #3: multi-agent “content swarm” 18:31 – Master/worker agents with shared tools 19:40 – Final setup: Sheets/Docs, credentials, models 20:10 – Takeaways: beginner → intermediate with a tutor 21:32 – Early AI-dopters access & outro #n8nAIWorkflowBuilder #n8n #AIAssistantBuilder #PromptToWorkflow #Automation #LangChain #AIAgents #PerplexityAI #OpenAI #Calendly #GoHighLevel #HubSpot #Outlook #FirefliesAI #RAG #NoCodeAutomation