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03AI-native dashboard

Designing a dashboard that knows what matters.

Getting chefs to what they need, when they need it.

Company
Topanga
Role
Led product and design, with engineering and data
Discipline
AI interaction design, product strategy

Before

Come see data.

The chef entered the dashboard, navigated the information, spotted something interesting, and decided what to do.

After

Come understand what matters.

The product surfaced what was relevant, gave context, and helped the chef explore or act.

02   The audienceSkeptic · Pragmatist · Visionary

Chefs didn’t need more data, they needed an answer they could trust.

Most chefs weren’t using AI in their daily lives, and many distrusted it. We knew trust would be hard to earn and easy to lose.

Skeptic

Distrustful of AI. Overwhelmed by technology and new systems. Relies on others.

Pragmatist Target

Curious about AI, but not using it personally. Frustrated by learning new tools. Looking for the path of least resistance.

Visionary

Comfortable with AI. Excited by its potential. Interested in details and deeper analysis.

Experience principles

  1. 01Time back is the most valuable thing we can give the chef.
  2. 02Trust must be earned, and can be lost instantly.
  3. 03Know each chef, and make each chef feel known.
  4. 04Be comfortable with the chaos of the kitchen.
  5. 05Connect the dots, but call out the gaps.
03   The design approachOpen Floor Plan · Surface → Recommend → Converse → Act

Deliver the right interface at the right moment.

Fluid

The experience shifted with what the chef was doing.

Personalized

It surfaced what was relevant to each chef.

Adaptive

The interface changed with context.

Context-aware

It knew what information mattered in the moment.

Proactive

It didn’t always wait for the chef to ask.

We called the concept Open Floor Plan. Instead of giving every chef the same fixed dashboard, the product used generative AI to assemble the right starting point for the moment and adapt to what the chef needed in that moment.

Surface

Bring important information forward, before the chef goes looking for it.

Recommend

Identify an opportunity and suggest what the chef might change.

Converse

Let the chef ask questions, explore context, and dig deeper.

Act

Help the chef move from a decision into an operational workflow.

Interaction depended on the use case.

Structured content & recommendations

Best when we already knew what mattered.

Chat

Best when the chef wanted to explore, ask a question, or dig deeper.

Chat let chefs deep dive into specific questions.
04   Reimagining the homepageA jumping-off point, not a better dashboard

The homepage gave chefs what they needed and guided them toward action and discovery.

  1. Surface something relevantDon’t make the chef go looking.
  2. Show why it mattersGive enough context to create confidence.
  3. Create a clear entry pointMake the next action obvious.
  4. Scaffold the deeper workflowOnce they’re in, guide them through the work.
05   RecommendationWhat we designed and tested

Finding the signal for the chef.

The system identified the production issues worth attention. The chef decided what to do about them and took action.

87.5%of flagged items showed waste reduction
31.1%reduction across flagged items

Instead of asking chefs to search through the data, we brought the important signals to them.

What changed

We brought the right answers to the chef at the right time.

Adoption98%of users started an AI workflow
Engagement70%of users engaged with chat
Retention66%of users who chatted once came back