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A user finds n8n's native AI agents unreliable, leading them to use GPT assistants via OpenAI nodes as a workaround. They note that better prompting is possible with the OpenAI API, suggesting a need for n8n's built-in AI agent functionality to offer comparable reliability and advanced prompting options.
The Truth About AI Agents and n8n: Cutting Through the Hype I noticed a recent Reddit post questioning if we're all being lied to about AI agents, particularly in the context of automation tools like n8n. As the VP of Systems at Church Media Squad overseeing a team of 3 system integrators, I want to share some real-world perspective. We run 4 instances of n8n with each handling 80-100k executions weekly across 800+ workflows. We came from Make looking for something that could truly scale with our operations. Let me be clear: those "$40,000 workflow" claims you see on YouTube? Are not realistic. One workflow no matter how clever isn't replacing an entire team. However, if you think n8n can't scale, it's because you haven't used it at scale. The limitation isn't n8n it's your understanding of what's possible. n8n isn't something you master in "a few hours" that's a massive oversimplification. You haven't scratched the surface until you've set up workers, migrated to Postgres and dealt with maintaining hundreds of workflows. What about AI agents? They're the latest fad not some workflow savior. They attempt to handle variables with brute force, but unless properly trained and prompted, they fall down. They can't adapt to unexpected situations like humans can. The real value isn't "replace your team" but "make your existing team dramatically more efficient." n8n has transformed us more into a code team than a no code team which speaks to its depth. #Automation #SystemsIntegration #n8n #TechLeadership