AI-native workflows
Automate the impossible. Grow 100x and beyond.
Map a job once on one canvas. Brain² and Super Agents run the steps, you approve the result, and every run builds on the last.
Beta in ClickUp Labs
Why AI-native
Built to think, not just trigger
Rule-based tools pass data from app to app. AI-native workflows read the work, make the calls, and hand the result to a person.
Rule-based automation
- If this
- Then that
- Moves data between apps
- Runs only the rule you wrote
- Breaks when the input changes
AI-native workflows
- Reads the work
- Decides the path
- Drafts the output
- You approve
- Reads tasks, Docs and replies
- Picks the path when a run has to choose
- Learns from every run it finishes
The canvas
Give AI a repeatable set of tasks
Set up the steps once. Run the workflow again whenever you need it, and check what happened each time.
- Start
- AI
- People
- Flow
- Exact
Choose how it starts
Run it yourself on any task, or set it to start on its own.
- Manual run
- Automation
- Schedule
- Webhook
- Choose how it starts. Run it yourself on any task, or set it to start on its own. Steps: Triggers.
- Hand the thinking to AI. Brain² or a Super Agent reads the work and writes the draft. When the run has to choose, AI picks the path. Steps: Agent, Condition.
- You make the call. Add an approval anywhere a person should check the work. They decide right in a ClickUp task. Steps: Approval.
- Keep the run moving. Give people time to reply and bring split paths back together. When it ends, you see exactly what the run made. Steps: Wait, Merge, Output.
- Some steps don't need AI. When a step should happen the exact same way every run, use one of these instead. Steps: Action, Transform.
Learning loops
Every run makes the next one better
Each run saves what worked. The next run starts from those learnings, so the work compounds instead of starting over.
Learnings applied
- Run 3Carousels outrun single images
- Run 2Tuesday 9 AM beats Friday afternoon
- Run 1Customer quotes get 2x the saves
A loop: Brain² drafts posts, a person approves them in a task, the posts go live, a Super Agent measures the results, and what worked is saved to a Doc. The next run drafts from those learnings.
Human in the loop
AI does the work. You make the call.
Add an approval anywhere a person should check the work. The run waits in a ClickUp task until someone decides.
- ApproveThe run moves on
- Request changesAI revises with your note
- EscalateSomeone else decides
We cut our launch checklist from 40 steps to 6. Here’s the workflow that does the rest.
+ 2 more posts
For every team
Every team has a job worth repeating
Pick a team to see a workflow in action, from the starting task through AI steps to a person’s review.
Integrations
Bring in the other apps you use
Connect an app once in App Center, then choose it inside any Agent step. Apps with an MCP server connect the same way.
- Salesforce
- ZoomInfo
- Attio
- DocuSign
- Box
- Webflow
- PostHog
- Tableau Cloud
- tl;dv
- Calendly
- GitHub
- Any MCP server
AI transformation
Want us to set it all up?
Our team maps your jobs, builds the workflows and Super Agents, and gets your people running. You skip the setup.
AI Workflows