Comment Créer des Agents IA en 2026 : Formation Complète Débutant

Comment Créer des Agents IA en 2026 : Formation Complète Débutant

🎙 Yassine Sdiri 👥 270K 📅 July 6, 2025 ⏱ 241 min 👁 180K 📄 tutorial 🧭 2026-08-21
Available in: English (current) Français

Keywords

AI agentsworkflowLLMn8nno-code

Summary

This 4-hour tutorial by Yassine Sdiri aims to teach beginners how to create and monetize AI agents without coding. The video is structured in three chapters: foundations, practical tutorials, and monetization. The foundations chapter explains the concepts of LLMs, workflows, and AI agents, highlighting the limitations of LLMs and how workflows and agents overcome them. The practical chapter demonstrates building two AI agents using n8n, a no-code automation tool, integrating with OpenAI, Google Drive, Sheets, Calendar, Gmail, Slack, and WhatsApp. The final chapter focuses on monetization strategies, including finding clients and a business model. The creator emphasizes the growing demand for AI agents in businesses and positions this skill as a lucrative opportunity. The video is practical and step-by-step, but lacks external citations and relies on personal experience.

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Critical Evaluation

Value of the Information & Strength of the Argument

The video provides significant practical value, offering a step-by-step tutorial on building AI agents with n8n, which is directly applicable for beginners. The argumentation is persuasive, using market trends and personal success stories to motivate viewers. However, the claims about job displacement and market growth are not substantiated with specific sources, relying on general references like Forbes and the World Economic Forum without providing details. The reasoning is coherent and builds logically from basic concepts to advanced implementation, but the lack of citations weakens the overall argumentative rigor.

Scientific Rigor, Source Quality, Title Accuracy

The video demonstrates a structured approach with clear chapters and a logical progression. However, scientific rigor is limited: the creator cites reports (Forbes, World Economic Forum) without giving specific details or links, and the content is based on personal experience rather than peer-reviewed research. The title accurately reflects the content, and the tutorial is well-organized. The description provides links to the creator’s LinkedIn and a free AI foundations course, but no direct references to the cited reports. Overall, the video is informative but lacks verifiable sources.

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Title / Content Match

The title accurately reflects the content: a complete beginner-oriented tutorial on creating AI agents, covering theory, practical no-code implementation, and monetization.

Quality & Reliability

7/10

The video is a comprehensive tutorial with practical demonstrations, but it lacks citations to external sources and relies heavily on personal experience and anecdotal evidence. The claims about market trends are not backed by specific references, though the content is generally consistent with current industry knowledge.

Chapters

Cited Sources

Concurring Sources

  • World Economic Forum Future of Jobs Report — The video cites this report for job displacement and creation statistics, which aligns with the WEF's published data.
  • Forbes article on AI job displacement — The video references a Forbes report on jobs at risk, which is consistent with Forbes' coverage of AI's impact on employment.

Dissenting Sources

  • No specific contradictory sources found — The video's claims are generally aligned with mainstream discussions, but the lack of specific citations makes it difficult to identify direct contradictions.

Contribution & Novelties

The video offers a comprehensive, no-code approach to building AI agents, which is valuable for non-technical entrepreneurs. It bridges the gap between theoretical understanding and practical implementation, with a focus on business applications and monetization. The step-by-step tutorials using n8n are practical and actionable.

Pour aller plus loin :

  • AI agent (Wikipedia) — Provides a general overview of intelligent agents, relevant for understanding the concept.
  • Large language model (Wikipedia) — Explains the underlying technology of LLMs, which is central to the video.
  • n8n documentation — Official documentation for the no-code tool used in the tutorials, useful for further exploration.

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Radar Profile

The radar profile shows high scores in information quantity and technical level, reflecting the video's comprehensive and practical nature. However, the lower scores in information quality and global reliability indicate that while the content is useful, it lacks rigorous sourcing and scientific depth.

Reliability 6/10

💬 Très positif. Sur les 30 commentaires analysés, les spectateurs expriment une gratitude et une admiration massives, saluant la clarté pédagogique, la générosité du contenu gratuit et l'impact concret sur leur apprentissage.