Design Thinking Your Business (and Life) with your AI Co-Founder
Nizar Hasan, VP Internal and Commercial Operations at Primordial Design, Inc.
December 2025
Design thinking isn’t just for product teams. Used right, it can drive how you build your career, shape your routines, streamline your workflows, even how your team solves problems. And just like startups use AI to accelerate product development, you can use it to accelerate how you design your life and work.
Why is this helpful? Most businesses are using AI and still not seeing results. According to McKinsey’s 2025 State of AI survey, 88% of organizations now use AI in at least one business function yet only 23% have successfully scaled real workflow automation, and 74% struggle to get measurable ROI. This happens when we invest in tools before investing in problem clarity and evaluating processes.
So instead of “using AI,” start by thinking and designing with AI. Here’s a step-by-step approach using design thinking for personal blockers, customer challenges, or department bottlenecks — with AI accelerating each stage.
1. Empathize: Understand the pain point
Before you jump to solutions, diagnose your bottlenecks like a UX researcher. Audit yourself or your team:
What tasks constantly drain attention?
What tasks repeat weekly?
What frustrates customers or colleagues over and over?
Helpful Tools:
Notion Q&A Assist — summarizes scattered notes into themes
Typeform + ChatGPT Analysis — collect and synthesize real feedback
Rewind.ai — brutally honest time tracking and desktop behaviour
Look for patterns & recurring problems, not opinions or feelings.
2. Define the problem clearly
Convert insights into a measurable problem statement.
“We spend 10 hours weekly on manual reporting, reducing time for strategy execution.”
Then refine it with AI:
“Rewrite this as a measurable problem with KPIs and hidden assumptions.”
Clear problems attract lean solutions. Vague problems attract expensive tools.
3. Ideate: let AI ask you questions
Most people treat AI like a shortcut to answers. But answers without the right questions just lead to faster bad decisions. The real unlock is having AI challenge your assumptions.
Use prompts like:
“Ask me 10 questions that will uncover high-impact, low-effort ways to solve this.”
This forces deeper context. It pushes you past obvious solutions. It simulates the best part of collaboration: someone smart pushing you.
Tools for Co-Ideation:
Perplexity for research context
Claude / ChatGPT for exploratory questioning (make sure to turn on “deep thinking”)
Gamma to instantly turn ideas into canvases or briefs
AI shouldn’t replace creativity; it should pressure-test it.
4. Prototype Fast (vibe-code it)
Prototype small, messy, and fast — just enough to test if the solution feels right.
Quick AI-Prototyping Tools:
Lovable — build apps or websites simply by chatting
Bubble — classic no-code builder for real functionality
Replit — great for engineers who want real code with AI help
The goal isn’t perfection. It’s feedback velocity.
5. Test, Measure, Iterate
Ship your small version. Observe. Did it save time? Improve experience? Change behaviour?
Tools: Mixpanel AI Insights, Userback, Google Gemini for synthesizing learnings.
If it failed, perfect — you learned cheaply. Most teams fail slowly but time is your differentiator.
As you think through the above, remember to use frameworks like design thinking to obtain more effective results. And as you make improvements in your day to day, don’t just ship solutions but share how you got there, so we grow as an ecosystem. This knowledge compounding will drive innovation for all, and shrink the learning curve to true AI adoption.