Build a Custom Agent: The Complete Tour
A Custom Agent turns a blank canvas into a running automation — a trigger, a few steps, and the data flowing between them. Here's the complete tour, from your first node to a deployed, scheduled workflow.
A Custom Agent is an automation you design visually. You start with a blank canvas, drop in the steps you want, connect them in order, and press run. No glue code, no servers to babysit — just the workflow you had in your head, now actually running.
This post is the map. We'll walk the whole builder once, end to end, and link out to deeper dives on each part.
The canvas
Everything happens on a node-based canvas. Each node is one step — send an email, call an AI model, scrape a page, branch on a condition. You drag a tool from the sidebar onto the canvas, then draw an edge from one node to the next to set the order of execution.
The canvas is built for real workflows, not toy demos:
- A minimap and zoom controls so large agents stay navigable
- Drag-to-connect edges that make the flow obvious at a glance
- A live configuration status badge — Not Configured, Partially Configured, or Fully Configured — so you always know what's left before a run
Step one is always a trigger
Every agent begins with exactly one trigger: the event that starts a run. It might be you pressing Run, a schedule (hourly, daily, weekly, or monthly), or a real-world event like a new email, a new Google Form response, a calendar update, or a GitHub push.
Triggers are the difference between a script you remember to run and an automation that just happens. We cover the full menu in Triggers: How Custom Agents Start.
Steps: actions, logic, AI, and code
After the trigger, you compose the work from four kinds of building blocks:
- Actions — ready-made operations for the tools you already use: Gmail, Telegram, GitHub, the Google Workspace, and live web data.
- Logic — If/Else branches, Loop/Repeat blocks, and secure Environment Variables for decisions and repetition.
- AI — Generate Text for free-form output and Generate Object for typed, structured data.
- Custom code — an Execute JS Code step for the moments a ready-made action doesn't quite fit.
Passing data between steps
Steps aren't islands. Any field in a later step can reference the output of an earlier one. Start typing {{ in a field and a variable picker appears, listing the outputs available from the steps above it. Pick a value and the agent wires it in at run time.
That single idea — outputs flowing forward — is what turns a list of steps into a real pipeline: scrape a page, summarize it with AI, then send the summary to Telegram, each step feeding the next.
Build it by talking
You don't have to place every node by hand. The builder ships with two assistants, docked together as Pal:
- Build (Pal) — describe the workflow in plain language and it adds the right tools, connects them, and even sets the trigger for you.
- Configure — walks through each unconfigured step one field at a time, and prompts you to connect any accounts a step needs.
The Configure assistant is also why your agent never gets "stuck" on a half-filled step — it knows exactly which fields are still required.
Run, inspect, save, deploy
When the flow is ready, press Run. The agent executes step by step, and each node shows its own result — success, error, or skipped — so you can see precisely where something went wrong instead of guessing. You can Stop a run at any time.
When you're happy, Save persists the nodes and edges, and every execution is recorded under the Results tab so you can reopen the full output later. If your trigger is a schedule or an event, deploying it lets the agent run on its own — no one has to be watching.
The goal is simple: the workflow you can describe in a sentence should be one you can build in a few minutes — and trust to run without you.
Keep reading
This was the overview. Each part gets its own deep dive:
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