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Alison Eyo's video thumbnail, captioned “steal this workflow”21:49

How AI has improved my design process

Alison Eyo · YouTube channel

AI Editor

SEO Blog Post

What an AI design workflow actually looks like

Most "AI for designers" advice is a list of tools. Product designer Alison Eyo takes the opposite approach in her walkthrough of her own process: she organises it by problem, and the tools fall out of that.

The shape is the useful part. The product names will change.

Start with the problem, not the tool

Eyo says she stopped asking what a given tool does and started asking what problem she is solving and which tool fits it. Several tools appear more than once in her workflow, and she describes that as intentional rather than untidy.

The most surprising claim comes early: generating UI is now the least interesting part of how she uses AI.

The problems, in her order

Context. Her first and least glamorous problem. A local setup she calls her chief of staff pulls together email, Slack, calendar and the previous day's work into a morning check-in — what is still open, what was already decided, what needs following up. The value she names is retrieval, not answers: she already has the information.

Research at volume. Fifty responses in a study and no time to watch fifty sessions. She works in layers — an initial pass across the whole study, NotebookLM to connect it to research the team already did months ago, then Claude to synthesise the transcripts more deeply. One of her questions is which single session she should go back and watch herself.

Pressure-testing a decision. She gives the model the problem, the findings and the direction she is leaning, then asks what assumptions she is making and what evidence contradicts her.

Working across scattered files. A folder of context handed over whole, rather than a chat full of pasted excerpts.

Visual design. A fast first direction to react to, then Figma for the actual work — with a bidirectional Figma integration moving context in both directions.

Design to code. Working inside the real codebase and opening an MR, which her engineers still review before anything ships.

The skill she rates above prompting

Prompting is useful, Eyo says, but the bigger skill is reading the response — knowing what is useful, what is irrelevant, and what the right question to ask next is.

Every stage of her process ends with a person deciding something. That is not a caveat added at the end. It is how the workflow is built.

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