Async operations are really important for high performance workflows. We should have “Async Start” and “Async End” Nodes.
My use case:
I officialy have 5 Agents in parallel (not just 3). I’ve just adapted several things on my workflow to fit the “Body is limited to 32000 characters” new topic requirement.
In my case i have 5 Agents that can run asynchronously in parallel but instead i get a synchronous run that makes my simple workflow much much slower.
This also happened to me when i wanted to read multiple files that could be done asynchronously in parallel but instead i wasted so much time waiting for unnecessary sync node runs.
With this node/s we’ll be able to reduce an huge amount of time in our workflows and will make n8n more robust with high performance with less time consuming workflows.
the fan-out pattern you’re after actually works today — one input splits into parallel branches, each branch runs its agent, and they resync at a single convergence point at the end. we run 5+ agents in parallel this way in production with no sync bottleneck. the native async start/end node concept is still worth pursuing for fire-and-forget patterns and cleaner subflow composition, but the current approach covers the parallel execution case well.
Yeah, this is a common issue even though it looks like things are running in parallel, n8n often processes them sequentially depending on the node setup.
If you want true parallel execution, a better approach is to split each agent into separate branches or workflows (using Execute Workflow or webhooks) so they run independently, then merge the results at the end.
This avoids one long synchronous chain and significantly improves performance.
For file processing, the same idea applies process items in separate executions instead of one loop.
n8n can handle parallel runs, but it needs to be structured that way
I’ve tested the community-recommended workarounds (this POC helped me understand the pattern, but scaling it to 5 concurrent agents revealed the friction)…
Creating separate workflows + webhooks just to achieve basic parallel async execution feels like fighting the platform. For AI/LLM use cases where 5 agents need to run concurrently (like in my use case example), this adds significant overhead for what should be a simple fan-out/fan-in pattern.
n8n is an automation platform, and automation today demands efficient parallelism. Native async start/end nodes (or similar) would unlock so many AI workflows.
Is there a timeline for this? I’d love to keep building in n8n, but I need the primitives to express parallelism without architectural gymnastics.
(For reference: I’ve tested this pattern with LangGraph [with the help of Claude Code] and native fan-out delivers impressive results for this simple 5 agents use case workflow. Happy to share the code if it helps prioritize async nodes in n8n.)
even though it looks like things are running in parallel, n8n often processes them sequentially depending on the node setup.