Date: 10/22/2025
Okay, this video is gold for anyone like me who’s been straddling the line between traditional coding and the exciting world of AI agents. It tackles the core question: “n8n (no-code) or Python (code) for building AI agents?” which is exactly what I’ve been wrestling with lately. It’s not a simple answer, and the video acknowledges that, diving into the pros and cons of both approaches. For instance, n8n’s visual workflow is undeniably faster for initial prototyping, whereas Python offers that granular control that’s critical for complex logic – something I learned the hard way trying to wrangle a particularly stubborn API integration.
What makes this video super valuable is that it acknowledges the realities of modern development. We’re not strictly “code” or “no-code” anymore. It highlights a hybrid approach, leveraging the strengths of both n8n and Python. Imagine using n8n to rapidly build the basic agent structure, then dropping into Python for the intricate logic, custom integrations, or performance optimizations where n8n’s visual style might become cumbersome. I can totally see this applying to client projects where speed of deployment is key, but specific features require a more tailored solution.
Honestly, it’s inspiring because it validates the direction I’m heading. It’s a reminder that mastering AI agent development isn’t about choosing one tool, but about intelligently combining the best of both worlds. I’m itching to experiment with the hybrid approach he suggests. Maybe start by refactoring one of my existing, clunky Python scripts into a more visually manageable n8n workflow, then bolting on the custom Python bits where needed. Sounds like a perfect weekend project!