Prompts Matter in Agentic Workflows
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Quick briefing — cleaned from the original RSS feed
Guys I had created a n8n workflow with all the tools and everything in place. tl;dr Here is the workflow: { "name" : "My workflow" , "nodes" : [ { "parameters" : { "options" : {} }, "type" : "@n8n/n8n-nodes-langchain.chatTrigger" , "typeVersion" : 1.4 , "position" : [ 0 , 0 ], "id" : "a28a630c-8f87-4881-bf5a-1c0d3b9ab597" , "name" : "When chat message received" , "webhookId" : "43333eec-230f-44ed-a007-a8513f0904b1" , "alwaysOutputData" : true }, { "parameters" : { "options" : { "systemMessage"…
1Key Takeaways
- Guys I had created a n8n workflow with all the tools and everything in place.
- Headline: Prompts Matter in Agentic Workflows
- Category focus: Prompt Engineering — relevant for AI builders and decision-makers.
2AIWedia Score
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that guys I had created a n8n workflow with all the tools and everything in place.
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