This is a theoretical question, not specific to one workflow.
N8N seems to have one heck of a hard time maintaining data flow from beginning to end.
The rules are surprisingly unique to n8n’s architecture, with the AI informing me that I need one or more of these patterns:
- “paired data sets” (15 nodes ago I had an odd result but 25 nodes ago I had an even result and now N8N can’t move my data forward), and/or
- “execute once” but also “always return data”, and/or
- “execute for each” but also NOT “always return data”, and/or
- Use set nodes to re-establish data alivenessness as data will fade and we want to keep it alive, and/or
- Use code nodes to re-animate data that appears to have had a near-death experience, and/or
- no no no output from airtable will process all the way through to the end but ONLY on Tuesdays and/or
- Huh. It worked for me.
This is time consuming and headache inducing. AI tells me I am “right” to be frustrated and the community agrees that rules seem strange and hard to follow.
Is there an instruction book on how to get data through the process without losing it to architecture-based rules?
All I want to do is "for i=0; i< value; i++), or “for each record in this dataset, perform these functions.”
But I am stopped at seemingly every turn when 16 records from Airtable becomes one null record for reasons that 4 hours of AI conversation can’t resolve.
I’m not asking for an answer to THIS SPECIFIC scenario.
I’m asking: What are the rules for dataset integrity?
Thank you in advance.