"I never decided to go all in on AI, it just kept showing up. At first, in small, practical ways. Generating content for design mocks or writing simple scripts to automate boring tasks. I even built a Figma plugin to easily rename all the icons in our icon library, to avoid the repetitive work, but also because I was curious if I could make it work."
"Early on I changed how I approach research online. I stopped defaulting to Google search and started relying more on Perplexity, and other similar tools. On paper, it's an obvious upgrade. Direct answers, cleaner summaries, fewer tabs open, and much less noise. But something subtle disappeared in the process. No more random blog posts from 2010, fewer half-relevant Reddit rabbit holes. Almost nothing that pulled me somewhere unexpected."
"I stopped wandering, I started extracting. Super efficient, but over time, that efficiency started to shape how I thought. I was moving faster towards answers, but along narrower paths. Ideas felt more predictable, and I was less surprised by where I ended up. The work converged quickly, sometimes too quickly. Design almost never benefits from straight lines. Some ideas only show up when you take the long way around, when you don't quite know what you're looking for yet."
AI adoption began incrementally with small automations like content generation, scripts, and a Figma plugin to remove repetitive work. Experimentation expanded into building apps, using brainstorming tools, shipping production PRs, and joining a product team, making AI integration inevitable. Research behavior shifted from broad web searches to tools like Perplexity, producing direct answers, cleaner summaries, and less noise. That change eliminated random discoveries and reduced exploratory wandering, leading to faster but narrower idea paths. The resulting efficiency shaped thinking, causing work to converge quickly, while design continues to benefit from detours and nonlinear exploration.
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