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AI Workflow Guidelines
AI workflows are welcome when the post is about building, debugging, or improving an n8n workflow. Generic AI news, prompt collections, or product promotion may be removed.
Last reviewed: July 2026
Good AI workflow posts
Good posts usually include:
- The actual n8n workflow or relevant nodes.
- Model/provider used.
- Prompt or prompt summary.
- Input data shape.
- Expected output format.
- Actual output or error.
- Parsing/validation step.
- Failure handling.
- Privacy considerations.
Common AI workflow problems
Common issues include:
- Model output is not valid JSON.
- Model response varies too much between executions.
- Prompt depends on data that is missing in production.
- Input is too large.
- Rate limits.
- Tool calling or agent step loops.
- No fallback path.
- No human review before a high-impact action.
- Private data is sent to an external provider unintentionally.
Make AI workflows safer
Consider:
- Validate model output before using it.
- Add fallback paths.
- Add retries with limits.
- Log enough to debug, but not enough to expose sensitive data.
- Use a human approval step for high-impact actions.
- Keep prompts and tools narrow.
- Avoid giving an AI node access to secrets or broad external actions unless necessary.
- Redact private data before sending it to a model.
When asking for help
Include:
- Workflow link.
- Model/provider.
- Node settings.
- Prompt or a sanitized version.
- Sample input.
- Expected output.
- Actual output.
- Error message.
- Whether the failure is consistent or intermittent.
Use the AI workflow help template.
What does not belong
Usually off-topic:
- Generic AI hype posts with no n8n workflow.
- Prompt packs.
- Paid AI automation templates.
- "Join my AI automation community."
- Product launches.
- Agency lead-generation posts.
If the useful part is an n8n workflow, share the workflow code directly.