New human-in-the-loop capabilities add fine-grained control

Community Highlights
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We’ve been thinking a lot about how to give humans more control in AI-powered workflows without hindering the speed and versatility that make AI valuable. Our latest additions to human-in-the-loop (HITL) capabilities do just that while making it easier to support complex business processes involving multiple users and services.

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What’s new

If you’re building agentic flows, you now have more granular control over AI behavior. Drop in human feedback exactly where it’s needed, using native features that are flexible and easy to configure.

Here’s what you can do with updates in v2.5 and v2.6:

  • Enable multi-turn conversation within a single execution using the Chat node. This capability supports things like conversational forms, branched flows based on replies, or step-by-step approvals as part of a deterministic workflow in conjunction with the Chat Trigger node.

  • Let AI Agents send chat updates, ask for clarification, and optionally pause for a response using the Chat tool. It’s great for cases when prompts are unclear, and keeping users updated during longer-running processes or multi-step workflows.

  • Enforce human intervention before a specific tool executes by requiring an explicit approval. Get targeted control over potentially risky steps like deleting records, writing to live systems, or sending sensitive emails.

  • Support review and approval processes within your agentic workflows that involve multiple users across a number of messaging and email platforms like Slack, Microsoft Teams or Gmail.

Why this really matters (and yes, you should be smiling)

These capabilities unlock all sorts of useful scenarios: Maybe your AI Agent is processing a big dataset, and gives you an update on progress periodically. Maybe it finds a sales lead and drafts a message, but gets approval from you in Slack before the email goes out. Maybe it processes your expense report from a form, but sends anything over $1,000 to your manager in Outlook before submission.

The magic here is in the flexibility and ease of implementation. Whether you’re automating approvals, building interactive chat experiences, or just want human checkpoint in production workflows, these features give your AI Agents the ability to be fast and thoughtful without going off the rails.

Adding human-in-the-loop to AI workflows might be easier than you think

With these new features, you can add human review in just a few steps.

:backhand_index_pointing_right: Learn more about the new Send Message and Send and Wait for Response Actions for Chat (V 2.5) here.

:backhand_index_pointing_right: Learn more about Human-in-the-loop for AI tool calls [v2.6] here, or see how it works in 90 with this demo:

Got an interesting use case or question? Drop it below. We excited to see what these new features unlock. :slight_smile:

24 Likes
Discussion On HITL Tool In the AI Agent
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Hi,
I just noticed this new feature and I’m really looking forward to use it.

At the moment I had to manually add HITL into the workflows.

Is it planned to open up this feature more?
In my case I’m using Mattermost as a chat interface and webhooks for the users decision.

In addition I need more information than just the tool-parameters.
E.g. for “Delete Email”, the AI passes the id of the mail, but for the Approval, I need the subject, sender, …

Yes, I could let the AI write a text, but when using the e-mail ID and retrieve everything without AI, there is no chance something gets mixed up.

4 Likes
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Hi @deeKay93 , welcome to the n8n community!
As far as I know, HITL is still tightly coupled to the n8n UI, so when I need external approvals in tools like Mattermost I rely on Wait for Webhook or similar wait based flows. For additional context such as subject or sender, I fetch the full email data with a Get Email node before the approval step and pass that information directly, instead of relying on the AI. I also keep tool parameters minimal and hydrate the context with regular nodes. I agree with you, more flexible native HITL for external approvals would be a great future improvement.

5 Likes
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As of 2.10.4 this feature is broken

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Curious how early businesses handled the trust problem — when you first
launched an AI answering business questions, how did you
convince businesses to trust it with real customers before it had
a track record?

Building something similar in a high-stakes domain (tax law) and
that’s the wall I’m about to hit.

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That’s a real issue as the agents might not have seen all the situations and might just make things up on new ones. We have seen teams close it with scope, evidence, and escalation discipline.

What worked in early production:

  • Start with low-risk actions and keep high-risk actions behind explicit approval.

  • Show the operator exactly what the agent saw, proposed, and changed before approval.

  • Keep one audit trail for reviewer, decision, edited fields, and final action.

  • Add timeouts and escalation rules so nothing waits forever.

A concrete pattern is: auto-approve low risk, route medium/high risk to a named reviewer, and require a short decision note. Based on the data from the human approval, you can adjust and get more confident with the automatic responses.

That gives the team confidence because they can verify behavior, not just trust promises.