Stack recipe

AI Automation Workflow Stack

A controlled automation stack for connecting AI outputs to workflows, approvals, traces, and human review.

Best for

Teams testing AI-assisted operations such as ticket triage, report drafts, data enrichment, and internal workflow routing.

Core tools

n8n
Dify
Flowise
Langfuse
Phoenix

Recommended models

Qwen
Llama
Mistral
DeepSeek, Kimi, or GLM models matched to the task

Hardware notes

Automation can use local models for sensitive or simple steps, but hosted or self-hosted APIs may be more reliable for heavier workflows.

Setup steps

Choose one narrow workflow with low-risk outputs.
Keep tool permissions read-only at first.
Add human approval before any write, send, purchase, or customer-facing action.
Log prompts, tool calls, outputs, and failures.
Review results weekly before expanding permissions.

Trade-offs

Automation saves time only when the task is well scoped. Broad agents with unclear permissions can create operational and privacy risk.

Alternatives

Use n8n when workflow integration is the main job.
Use Dify or Flowise for app-style LLM workflows.
Use Langfuse or Phoenix when tracing matters.

FAQ

Should AI workflows run without approval?

Not at first. Start with drafts and recommendations, then add approved actions after review.

What should be logged?

Log prompts, retrieved context, tool calls, model choices, outputs, and human corrections.

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