What to adapt first in an AI world

When AI changes the speed of execution, the first thing to adapt isn’t your tools or even your title. It’s your approach to problems.

For most of design’s history, our value has been tied to execution: the ability to create high-quality outputs quickly and efficiently. Now, AI can do that in seconds. The difference between good work and generic output is no longer speed, it’s judgment.

Judgment is what turns a flood of AI-generated possibilities into a clear, intentional solution. It’s the ability to see which ideas are worth developing, which can be combined, and which to leave behind.

In an AI-first environment, this shift from output to orchestration is the core adaptation designers need to make.

From Tools to Principles

The temptation when AI tools appear is to focus on mastering them. While there’s value in learning how to get the most from AI, those skills have a short shelf life. The tool you rely on today could be irrelevant in a year. What doesn’t expire are the principles you work by.

The designers who thrive in an AI-accelerated world will anchor their work in principles that sharpen judgment and direct the technology toward meaningful outcomes. In my practice, five principles have emerged as the most valuable:

• Authentic — Your voice, your intent, your lived experience.
• Reduction — Filtering out the noise to focus on what matters.
• Nonlinear — Embracing exploration and branching paths.
• Emergent — Sensing patterns and shaping unexpected outcomes.
• Modular — Designing in flexible, reusable parts.

Over the next few weeks, I’ll be breaking down each of these principles in detail, showing how they work in an AI context and how to put them into practice. Next week, we’ll start with Authentic.

Practical Ways to Start Adapting Today

You don’t need to wait for the full principles series to put this into practice. Here are a few shifts you can start making right now in your AI-assisted design work:

1. Ask “What am I solving?” before touching a tool.
   Write down the problem or opportunity in one clear sentence. This keeps AI outputs anchored to intent instead of wandering into novelty for novelty’s sake.
2. Set output limits.
   Give yourself a cap, like “I will review no more than 10 variations.” This forces you to choose faster and avoid decision fatigue.
3. Evaluate in passes.
   First pass: remove anything that’s off-brief or visually incoherent.
   Second pass: look for ideas with potential, even if they’re not fully formed.
   Third pass: pick your top two or three and take them forward.
4. Document why you chose what you chose.
   A short note or voice memo on why an idea survived helps you sharpen judgment and explain your thinking to others.
5. Ship something small.
   Instead of chasing perfection, get a quick, clickable prototype or mock-up into someone’s hands for feedback. The sooner you see it in action, the sooner you’ll know if it works.

These steps may sound simple, but in an AI workflow, they are your guardrails against noise and endless iteration.

A Design Practice for Clarity: SWARM

This is where SWARM comes in. SWARM is the creative practice I use to move from raw ideas to real outcomes without losing clarity. It breaks the work into five repeatable phases:

• Spot — Notice what’s showing up. Ideas, patterns, sparks.
• Weigh — Pause and reflect. What has real potential?
• Arrange — Structure the strongest directions so they can be compared and tested.
• Refine — Improve clarity by removing anything that weakens the idea.
• Make — Get to made fast. Once you have a clear direction, use an AI-assisted design tool to produce a clickable prototype or working draft. The goal is speed to something tangible you can put in front of people, so you can see it in action and learn from real interactions.

The phases aren’t rigid. You can loop, remix, or jump between them as the work evolves. In an AI workflow, SWARM keeps you in control rather than reacting to every output.

Why This Matters Now

Adaptation doesn’t begin with the newest app or prompt trick. It begins by changing how you approach problems, how you direct the flow of ideas, and how you decide what’s worth making.

Over the next few weeks, we’ll dig into each principle in detail, starting next week with Authentic — why your perspective, intent, and tone still matter more than any AI model.

If you start building this mindset now, you’ll be ready to use each principle not just as theory, but as a filter for every decision you make in an AI-driven workflow.