How I Use AI to Expand Design Thinking and Accelerate Discovery

Artificial intelligence is changing how product teams explore problems and develop solutions. In my design practice, I use AI not as a replacement for design thinking, but as a way to scale curiosity, accelerate research synthesis, and rapidly explore solution spaces.

I experiment with AI tools that help me go deeper into complex problems, generate alternative perspectives, and move more quickly from insight to concept.

Going Deep and Wide on Complex Problems

One of the most valuable ways I use AI is during early discovery. When defining a problem space, I often use AI tools to help explore adjacent possibilities, challenge assumptions, and surface additional angles that might otherwise be overlooked.

Using tools like Miro’s AI Sidekicks, I can quickly:

• Expand a research question into multiple investigative paths
• Generate alternative ways to frame a problem
• Identify potential blind spots in early thinking
• Explore a wider set of hypotheses before narrowing toward solutions

This allows me to go both deeper and wider during discovery, ensuring the design process starts with a well-examined problem space.

Scaling the Analysis of Customer Feedback

AI has been particularly useful in helping me synthesize large sets of qualitative data.

During research and feedback analysis, I use AI to:

• Quickly identify emerging themes in customer feedback
• Generate multiple ways to group and cluster insights
• Explore alternative categorizations of user pain points
• Pressure-test the structure of insight synthesis

Rather than replacing human interpretation, this process allows me to rapidly test multiple synthesis models before arriving at the most meaningful interpretation of the data.

This speeds up research cycles and helps teams move from feedback to actionable insight faster.

Exploring “Vibe Coding” Platforms

I’ve also been experimenting with emerging AI-assisted development environments such as Base44 and Claude.

These tools allow designers to quickly explore:

• Early product concepts
• Interface structures
• Functional prototypes
• API-driven interactions

While these tools are not replacements for engineering teams, they enable designers to prototype and test ideas much earlier in the product lifecycle.

This experimentation helps bridge the gap between design thinking and technical feasibility, allowing product teams to evaluate ideas faster.

Why This Matters

AI will not replace thoughtful design. But it can dramatically improve the speed, breadth, and rigor of the design process.

Used well, AI can help designers:

• Explore problem spaces more thoroughly
• Synthesize research more efficiently
• Generate and test ideas faster
• Move from insight to prototype with greater speed

My goal in experimenting with these tools is to understand how AI can augment the designer’s role while preserving the judgment, empathy, and systems thinking that define great design.