Build your first NO CODE AI Agent in n8n (for beginners)

Build your first NO CODE AI Agent in n8n (for beginners)

by Nate Herk

Applied Sciences & Engineering AI — Models & Research UYQArtificial intelligence (AI)UYQMMachine learning
🎙 Nate Herk 👥 964K 📅 September 25, 2024 ⏱ 20 min 👁 13K 📄 tutorial 🧭 2026-08-28
Available in: English (current) Français

Keywords

n8nAI agentno-codeOpenWeather APIOpenAI

Summary

This tutorial by Nate Herk demonstrates how to build a no-code AI agent in n8n that can answer questions about weather and Wikipedia. The agent uses two workflows: one for the weather tool (using OpenWeather API) and one for the agent itself (using OpenAI). The video walks through setting up the OpenWeather API key, creating a weather tool workflow that fetches current weather data, parses it with an OpenAI node, and returns a friendly response. Then, it shows how to create an agent workflow that uses a chat trigger, an AI agent node with memory, and tools like Wikipedia and the custom weather tool. The creator emphasizes the importance of prompting and shows how to debug by inspecting executions. The video is practical and aimed at beginners, with clear step-by-step instructions and live troubleshooting.

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Critical Evaluation

Value of the Information & Strength of the Argument

The video provides a clear, hands-on demonstration of building an AI agent with n8n, which is valuable for beginners. The argumentation is based on practical experience, showing real-time problem-solving and adjustments. The creator explains the logic behind each step, such as why memory is needed and how tools are called. However, the video lacks deep theoretical explanations and does not discuss alternative approaches or potential pitfalls in detail. The value lies in its actionable tutorial format rather than in-depth analysis.

Scientific Rigor, Source Quality, Title Accuracy

The video is a tutorial and does not cite formal sources, but it references the tools used (n8n, OpenWeather API, OpenAI). The description includes links to the creator’s community and other videos, but no scientific references. The title accurately reflects the content, and the video stays on topic. The creator’s approach is transparent, showing both successes and failures, which adds to the credibility of the tutorial.

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Title / Content Match

The title accurately reflects the content: a beginner-friendly, no-code tutorial for building an AI agent in n8n.

Quality & Reliability

7/10

The tutorial is practical and demonstrates a working example, but lacks in-depth explanation of underlying concepts and potential limitations. The creator openly shares his reasoning and troubleshooting, which adds credibility, but the content is based on personal experience rather than formal sources.

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Cited Sources

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Contribution & Novelties

This video offers a practical, beginner-friendly introduction to building AI agents with n8n, focusing on tool integration and agent memory. It provides a concrete example of combining external APIs (OpenWeather) with AI models (OpenAI) in a no-code environment. The creator’s live troubleshooting and emphasis on prompting offer insights into common pitfalls and best practices.

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Radar Profile

The radar profile shows a balanced performance across all dimensions, with slightly lower scores in technical depth and information quality, reflecting the beginner-oriented nature of the tutorial. The high scores in practical application and reliability indicate a useful, hands-on resource.

Reliability 7/10

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