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We Didn't Migrate from n8n to Python Because n8n Failed

DEV Community·Joseph Yeo·6 months ago
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#aiagents#localai#code#orchestrator#logic
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We migrated because our AI orchestrator became something that needed tests, trust boundaries, and deterministic behavior.

ForgeFlow is a fully local, multi-agent TDD system — a planning agent (Claude) designs a spec document set, and a local 45GB LLM executes TDD cycles overnight on Apple Silicon. During our initial development iterations, n8n was the orchestrator. It felt like the right call. Visual workflow, no-code glue, easy HTTP nodes, built-in error routing. What's not to like?

Turns out, quite a lot.

What n8n Got Right

To be fair, n8n earned its place early on. When we were validating the core loop — call LLM → apply files → run pytest → branch on result — the visual canvas was genuinely useful. You could see the entire decision tree at a glance. Non-engineers could follow it. Debugging a single node failure was fast.

And for a prototype, that matters.…

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