AI scenario helper
AI scenario helper is a chat panel inside the scenario editor. You describe the automation in plain language; the assistant plans the structure, asks for approval, then adds and connects nodes on the canvas. You stay in control: nothing is published until you review and deploy.
The result is a normal Latenode scenario. You can edit any node, re-run tests, or keep chatting to adjust the flow.
When to choose AI scenario helper
- You want a first draft in minutes, not an empty canvas.
- The chain has many nodes and you prefer describing the goal over wiring each step.
- You need help debugging: paste what failed and ask for a fix.
- You want explanations for nodes or logic on the open canvas.
Using the helper consumes PnP tokens. Longer chats and bigger builds cost more; each message shows the step cost in the panel.
What the assistant can do
Build. Describe trigger, apps, and outcome. The assistant proposes a numbered plan, then builds after you Approve.
Explain. Ask how a node works or how the open scenario fits together. Answers use what is on your canvas.
Debug. Describe a failed run or odd output. The assistant points to the likely node and suggests changes.
Full guide: Build with AI.
How to work with it
Open the helper
Open a scenario (new or existing) and click AI scenario helper at the bottom of the builder.
Describe the task
Say what should trigger the scenario, which services to use, and what the result should be. The more specific the prompt, the fewer iterations you need.
Approve the plan
After the assistant thinks through the request, a Scenario approval card lists the steps it will take. Click Approve to start building, or Request changes to adjust the plan first.
Review on the canvas
Check nodes, authorizations, and required fields. Run Run Once and inspect Execution History.
Deploy when ready
Save, Deploy to Production, and turn Active on when you are satisfied.
Write effective prompts
Include:
- what triggers the scenario (schedule, webhook, app event),
- which apps or data sources to use,
- what to read, send, or update,
- what should happen on success or failure.
Example:
Every day at 9 AM collect AI news via Perplexity and email a short digest to me.
Use a schedule trigger.Before you go live
- Read the scenario logic on the canvas.
- Confirm every connection and authorization is set.
- Test with realistic input in Development.
- Do not paste API keys into chat; use the authorization screens.
Go deeper
- Build with AI - approval flow, PnP usage, examples
- Creating with AI - quick start for new users
Build manually
Add nodes on the canvas, connect routes, and configure each step yourself.
Latenode MCP Server
Connect Cursor, Claude, or another MCP client to the Latenode MCP Server and build scenarios from your agent.
Need Help? Ask the community
If something on this page is missing or unclear, post on the Latenode community forum. Our team and other users usually reply quickly.