Stop Learning n8n in 2026... Learn THIS Instead
Is N10 Worth Learning Ahead of 2026?
Current Trends in AI Automation
- The speaker addresses the growing interest in whether N10 is worth learning, especially as many are transitioning to cloud code.
- Mikuel introduces himself and shares his experience scaling an AI agency and teaching others about AI automation.
- Observations indicate a shift from N10 content creators to those focusing on cloud code due to changing trends in the automation space.
Evolution of Automation Tools
- The speaker outlines three phases of automation evolution:
- Phase 1: Manual coding (1950s - 2011).
- Phase 2: Visual workflow builders (starting in 2011 with tools like Zapier and N10).
- Phase 3: Generative workflows using platforms like cloud code that allow for natural language prompts.
Arguments Against N10's Relevance
- Critics argue that:
- Commoditization: Similar to past tech roles, basic automation skills may become obsolete as tools simplify processes.
- Efficiency: New tools enable rapid development of automations compared to traditional methods.
- Real World Application: Many viral AI agents lack practical business value despite their popularity on platforms like YouTube.
- Complexity: Managing complex workflows can be challenging, requiring deep technical expertise which new tools aim to bypass.
Counterarguments Supporting N10
- Proponents highlight:
- Fundamentals Understanding: Mastery of APIs and basic logic is crucial for effective use of advanced tools like cloud code.
- Control Over Processes: Using N10 allows users to see each step clearly, providing better debugging capabilities compared to opaque systems in cloud code.
Is N10 Dead? Insights on Automation Tools
Deployment and Reliability in Automation
- The deployment and reliability of automation tools are crucial; Nitan offers mature hosting options with clear execution logs and predictable behavior.
- Cloud code, while powerful, presents deployment frictions that can complicate long-term maintenance.
Evolution of Automation Tools
- In 2022-2023, automation options were limited to tools like Zapier for simple tasks or Make.com for more complex automations.
- By 2026, the landscape has expanded into three layers:
- Template-based solutions (e.g., Lindy AI)
- Visual workflow builders (e.g., Nitn)
- Agentive workflow platforms (e.g., cloud code).
Learning Path for Automation
- Beginners should start with template-based solutions to grasp fundamentals before progressing to more complex systems like cloud code.
- The misconception that one must choose between tools is addressed; it's about selecting the right tool for specific tasks.
Future Predictions for N10 and Cloud Code
- N10 is not dead; its learning approach needs adaptation. Understanding APIs and workflow logic is essential for effective automation.
- Over the next 12 to 18 months:
- Improvements in AI-assisted building features within N10 are expected.
- Cloud code will become more user-friendly as hosting issues are resolved.
Emphasis on Problem-Solving Skills
- The future of automation will focus less on technical skills and more on understanding business problems that can be solved using these tools.
- Regardless of skill level, businesses prioritize problem-solving capabilities over specific tool expertise.
Conclusion: The Role of Automation Architects
- For beginners, starting with Niten is recommended to build foundational knowledge before tackling complex applications with cloud code.
- Advanced users should adopt a tool-agnostic mindset, focusing on applying their skills to solve real business challenges rather than fixating on specific technologies.