Design a product with AI

A long, open, guided conversation with a single person to understand in detail their experiences, motivations and way of seeing a topic.

Output

Detailed accounts of experiences and motivations

Avoid

Asking for general opinions instead of concrete stories (“the last time you…”), asking leading questions or selling your idea.

Understanding customers by the progress they are trying to make in a specific situation, the “job” they hire a product for, not by their demographics.

Avoid

Confusing the job with a product feature.

A method for summarizing research in a few fictional characters, with a name, goals and context, who represent groups of users.

Output

A few fictional characters, with a name, goals and context

Avoid

Making them up in an afternoon or filling them with stereotypes and details that don't help decide.

The often incomplete idea a person forms of how something works, and uses to predict what will happen when they act.

Avoid

Assuming people understand the system the way the team does.

Three criteria an idea must balance: it meets what people need and want, it can be built with the available means, and the organization can sustain it.

Avoid

Using it as a quick vote, without data.

A technique for turning a problem or an insight into an open, optimistic question that invites ideas: “How might we…?”

Output

Open questions that invite ideas

Avoid

Putting the solution inside the question (“How might we build an app that…?”).

A template to see whether an offer fits a customer type: on one side, their profile (jobs, pains and gains); on the other, the offer’s value map.

Output

A canvas with the customer profile and the value map

Avoid

Filling the profile with assumptions and taking it as valid.

Eighteen guidelines for designing interaction with AI systems, across four moments: initially, during interaction, when the system is wrong and over time.

Avoid

Applying them only at the end, when nothing can be changed.

Designs how a person converses with a system, by voice or in writing, as in voice assistants and chatbots, drawing on how conversations between people are organized.

When to use it

Write sample dialogues and read them aloud before designing the flow.

Avoid

Designing a menu disguised as a conversation.

A sequence of panels that shows a person using a product or a service in context, step by step.

Output

A sequence of panels showing use, step by step

Avoid

Drawing only screens instead of the situation.

A prototype in which a hidden person, the “wizard,” produces the system's responses by hand while the participant uses it as if it worked on its own.

Output

People's reactions to a simulated system and what the real system needs to do

Avoid

Letting the wizard improvise: if the answers change every time, you won't know what failed.

Building quick, incomplete versions of an idea, from a paper sketch or a cardboard mock-up to something that works, to answer a design question before developing the idea.

Output

Prototypes, from a sketch to something that works

Avoid

Polishing the look when you don't yet know if the idea works.

The team, and sometimes users, act out a situation with simple or cardboard objects to imagine how a product or service would work.

Output

Acted-out situations that show how an idea would work

Avoid

Turning it into theater without a design question.

A method in which real people try to do specific tasks with a product while being observed, to find out where they get stuck and why.

Output

A list of usability problems, with where they appear and why

Avoid

Asking “do you like it?”: measure what people do, not what they think.

Ten general rules that evaluators use to review an interface and spot usability problems before testing it with users.

Avoid

Letting a single person review the interface and call it done.

Interface designs that lead people to do something they didn't want to, like buying, subscribing or giving up data, by exploiting how we decide.

Avoid

Hiding cancellation, preselecting extras or using guilt-tripping wording.

A framework for choosing what to measure in a digital product (happiness, engagement, adoption, retention and task success), starting from goals rather than available data.

Avoid

Always using all five categories; choose the ones that make sense for your product.