How to Build Multi-stage AI Pipelines That Actually Work

What’s a Pipeline?

A pipeline is a sequence of stages that run one after another. Each stage creates its own board with tasks, and when all tasks in a stage are complete, the next stage begins automatically.

Think of it like an assembly line for AI work:

Research → Draft → Review → Publish

Why Pipelines Matter

Without pipelines, you’d have to manually:

1. Run a research board
2. Wait for it to finish
3. Create a drafting board with the research results
4. Wait again
5. Create a review board…

Pipelines automate this entire chain. Define it once, run it whenever you need.

Building Your First Pipeline

Step 1: Define Your Stages

Start with the end goal and work backwards. For a content pipeline:

• Stage 1: Research — Gather sources, analyze competitors, identify key points
• Stage 2: Draft — Write content based on research output
• Stage 3: Review — Quality check, fact-check, tone review
• Stage 4: Publish — Format and prepare for distribution

Step 2: Configure Each Stage

Each stage gets its own:

• Objective — What should agents accomplish?
• Agent team — Which agents should work on this?
• Output expectations — What does “done” look like?

Step 3: Set Your Trigger

Pipelines can run:

• Manually — Click “Run” when you’re ready
• On a schedule — Set a cron schedule (e.g., every Monday at 9am)

Best Practices

1. Keep stages focused — Each stage should have one clear purpose
2. Use file paths — Organize outputs per stage for clean handoffs
3. Start small — Begin with 2-3 stages, expand once you’re comfortable
4. Review the first few runs — Let agents learn your standards

Get Started

Pipelines are available on all plans. Create your first pipeline →