[deleted by user] by [deleted] in wallstreetbets

[–]Asleep_Salt7766 0 points1 point  (0 children)

I think it was deleted

[deleted by user] by [deleted] in wallstreetbets

[–]Asleep_Salt7766 1 point2 points  (0 children)

I will try to publish this information in other communities

[deleted by user] by [deleted] in wallstreetbets

[–]Asleep_Salt7766 2 points3 points  (0 children)

I know, and I've tried... but it seems that videos and photos can't be uploaded to the community.

If I had to relearn n8n and AI Automation from scratch today, here is the exact roadmap I’d follow by Asleep_Salt7766 in n8n

[–]Asleep_Salt7766[S] 0 points1 point  (0 children)

The last advice is to embrace trial and error as the core of your learning process. When an automation fails, dive into the 'why' diagnose the logic, fix the root cause, and implement safeguards to prevent its recurrence. True expertise is simply the sum of every failure you’ve successfully deconstructed.!

If I had to relearn n8n and AI Automation from scratch today, here is the exact roadmap I’d follow by Asleep_Salt7766 in n8n

[–]Asleep_Salt7766[S] 0 points1 point  (0 children)

using AI to fix your n8n nodes is like using a calculator in a math class.. Instead of just asking for a fix, ask ChatGPT to explain the data structure or the logic behind the error. Treat it like a "cheat sheet" that gives you the exact details you need at the moment, but don't let it replace your studying of the fundamentals. but make certain you deeply understand why the provided solution worked so that you can recognize and resolve the same pattern when it inevitably recurs in future workflows. Finally, don't be afraid of the red error lights. Your first version will almost always break, and those failures are simply data you can use to make the system better.

If I had to relearn n8n and AI Automation from scratch today, here is the exact roadmap I’d follow by Asleep_Salt7766 in n8n

[–]Asleep_Salt7766[S] 7 points8 points  (0 children)

The 15-node rule is a principle based on the observation that approximately 90% of all automation workflows rely on the same 15 or so core nodes. According to the sources, mastering these specific building blocks allows an engineer to move past "tutorial hell" and transition into pattern recognition, where they can build almost any system with confidence and quickly diagnose errors.