How I use AI tools in everyday design
Over the last few years, I’ve deliberately integrated AI into my design workflow to increase clarity, speed, and creative range without sacrificing quality. I use AI as a force multiplier, not a shortcut. It helps me think through complexity, generate and refine ideas, synthesize research, and translate abstract concepts into tangible outputs.
My use of AI spans three core areas: content, imagery, and prototyping. In every case, human judgment remains central.
Structuring messy information and early sense-making
Tools: ChatGPT, Claude
I regularly work with unstructured inputs like interview transcripts, help center comments, public reviews, and competitive research. AI helps me cluster themes, extract meaningful quotes, and turn noise into a usable narrative. Claude’s artifact-based outputs are useful for structured synthesis, while ChatGPT allows me to maintain long-term context through custom workspaces.
This dramatically reduces time spent on first-pass analysis and lets me focus on interpretation and decision-making.
Lightweight design critique and gap detection
Tool: ChatGPT
As an individual contributor, access to frequent critique is not always guaranteed. I use AI as a preliminary reviewer to sanity-check flows, assumptions, and edge cases, especially in technically complex work.
It does not replace real design feedback, but it consistently surfaces issues around clarity, accessibility, and logic. I treat it as a first filter before sharing work with other designers or stakeholders.
Simplifying dense material through audio
Tool: NotebookLM, ChatGPT
As a researcher, I am often handed complex or research-heavy material to be understood in tight timelines. NotebookLM is my go-to in these situations. It excels at synthesizing multiple documents, citing sources accurately, and avoiding hallucinations. I frequently use its Audio Overview feature to turn dense inputs into podcast-style summaries, making it easier to absorb insights while multitasking.
Product and engineering documents are often either too technical or too ambiguous to act on directly. I ask ChatGPT to reframe these inputs into clear, structured design briefs with goals, constraints, and open questions surfaced upfront.
The output still requires editorial judgment, but it significantly accelerates alignment and reduces ambiguity at the start of a project.
Using AI for Prototyping and Building
Tool: Lovable, Google AI Studio, Claude, and Figma Make
I’ve been using AI tools like to prototype and build working software. These tools have meaningfully reduced the distance between concept and execution, allowing me to validate ideas in real, interactive form rather than static mocks.