Delegating design work to AI agents: a practical guide for email teams

"Just have the AI do it" is easy to say and surprisingly hard to operationalize. Which tasks? With what guardrails? How do you know when the output is good enough to ship, and when it's confidently wrong?

With the Figma Agent now in open beta, these stopped being hypothetical questions for design teams. The agent can build layouts, edit files, duplicate campaigns, and run multi-step workflows, guided by skills, attached files, and connectors. The sessions on agentic workflows at Figma's annual conference this year were among the most packed for a reason: everyone is trying to figure out the same thing. What do you actually delegate?

After months of building AI-assisted workflows for lifecycle campaigns, here's our honest framework.

The delegation test: three questions

Before handing any task to an agent, we run it through three questions:

• 1. Is the standard explicit? Agents excel at tasks with clear success criteria. "Wireframe from our component library" works because the library is the standard. "Make it feel premium" fails because the standard lives in someone's head.

• 2. Is the cost of error low or catchable? A wrong wireframe costs a review cycle. A wrong send costs subscriber trust. Delegate upstream tasks first, where human review is already built into the workflow.

• 3. Would you delegate it to a capable new hire on day one? If a task needs six months of brand context to do well, an agent needs that context too, written down, not assumed.

Tasks that pass all three: delegate aggressively. Tasks that fail any: keep a human in the driver's seat and use the agent as an accelerator.

What email teams should delegate first

Wireframing from a component library

This is the highest-value, lowest-risk starting point. Give the agent your email component library and a copy deck, and ask for three layout options. The agent isn't inventing design, it's arranging components you already trust. You review, pick, refine. The prerequisite is a real email component library; if you don't have one, that's step zero.

Multi-audience and multi-language duplication

"Duplicate this campaign for five segments, swap in each copy variant, and flag any layout breaks from longer text." This is exactly the kind of tedious, precision-demanding work agents are built for, and exactly the kind humans do worst at 4pm on a Friday.

Layout QA passes

Ask the agent to walk a file and check spacing consistency, orphaned text layers, off-grid elements, and naming conventions. It won't catch everything, but it catches the mechanical issues so human review can focus on judgment calls.

First-draft variations

Subject line areas, hero copy placements, CTA arrangements: generating five variations for a human to react to is faster than a human generating five variations cold. The agent produces volume; you provide taste.

What to keep human (for now)

• Brand judgment calls. Whether a layout feels right for this client, this moment, this audience. Agents don't know that the last urgency-heavy campaign underperformed, unless you tell them, and even then, knowing isn't feeling.

• Client-facing decisions. What gets presented, how feedback is interpreted, when to push back. Relationships are not a delegable workflow.

• The final ship decision. Every email that goes out is your reputation. Agents draft; humans ship.

This division of labor is the heart of every good AI-assisted design workflow: the agent handles legwork, the human keeps the taste and the accountability.

Making agents actually useful: context is everything

The biggest lesson from our experiments: an agent without context is a very fast intern with amnesia. The teams getting real value are the ones investing in written, structured context:

• A component library with clear names and usage rules

• Brand guidelines the agent can reference, in the file, not in a PDF nobody opens

• Documented dos and don'ts from past campaigns (what underperformed and why)

• Coding and accessibility standards, written as checkable rules

Notice what this list really is: it's the documentation your team should have anyway. Agents just made the ROI of writing it down undeniable. Brand consistency was always a systems problem. Now the system has a new reader.

The bottom line

The question isn't whether AI agents will be part of email workflows, that's already settled. The question is whether your team delegates deliberately, with standards and guardrails, or accidentally, by letting output quality drift. The first path compounds; the second erodes. The defining lifecycle trend of this era: AI rewards teams that know exactly how they work.

Want help designing an agent-ready email workflow? Talk to us, we're building these systems every week.