How Gamma uses UX design to de-risk AI product development

AI products require rapid prototyping and tight user feedback cycles

Author

Hamza Choudery
February 07, 2024

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Generative AI — and non-deterministic software more broadly — is dismantling preconceived notions about how users want to engage with their software.

The future of user experience (UX) for AI products is a “Great Unknown.”

However, that’s no reason to sit on the sidelines and wait to see how things shake out — the market has and will continue to handsomely reward companies that are on the frontier of reimagining UX for AI-powered products.

So, how do you actually build sticky user experiences?

There’s not a copy-and-paste playbook for this. However, there are best practices you can adopt to maximize your chances of creating something that resonates with users.

Behind many early successes in the AI application layer are product teams that excel at rapid product iteration, Gamma being a fantastic example of this. Gamma’s product team has made it a core competency to crank out prototypes and continuously engage in user discovery.

“Our design team was modeling out the user experience and just showing it to people. So they were actually just drawing up screens and going through a lot of user testing on those to see what people would ‘get’ or not get … You want people who are comfortable actually talking to users and building an understanding of what people want. You need people who are capable of showing their vision clearly, end-to-end.”

Jon Noronha, Chief Product Officer, Gamma

When designing AI experiences, what you want to avoid is spending a bunch of time creating a blueprint for complex user journeys. This approach doesn’t allow enough space for user feedback AND it bakes in too many assumptions about what’s possible from an execution standpoint.

Prototype, test, ship, repeat.

“We really believe that to see these ideas in action, you have to build them out. And so we were building lots of these things and also throwing away lots of these things. I would say the typical lifetime of one of these prototypes was like two weeks, and at a given time there were at least three of them in flight.”

Jon Noronha, Chief Product Officer, Gamma

The role of UX design

When you boil down the primary job of a strong UX design function, it’s to de-risk product development.

This is especially important for AI products because product risk is inherently higher. GenAI is still in its nascency, so there’s a high-degree of technology risk (i.e., the ability to get the product to do what it needs to do) and UX risk (i.e., the ability to build a product experience that delights users).

UX designers help de-risk AI product development in a few ways.

  • Engage in lightweight prototyping: They can quickly create prototypes in Figma or code. This helps get something in front of users for feedback sooner, so product development doesn’t become an R&D project.

  • Reduce technology risk: UX designers are able to experiment with prompts to get an early read on whether foundation models are able to deliver on the task at hand (i.e., feasibility assessment).

  • Build an intuition for user preference: Since they remain hyper-fixated on users, they can quickly identify the golden nuggets in user feedback (both implicit and explicit) to make sure the product strategy is heading in the right direction.

“We’re a bit unusual in that our team is very UX design heavy. Our team of 12 has four UX designers, and I think that 1/3 ratio is pretty unheard of. But it ended up serving us really well through this process, because the skill that is most valuable in doing this kind of prototyping exploration is UX design. Which means they’re comfortable using visual tools like Figma to actually mock up the UI. And the real power comes when you have people who can both design and code to some degree.”

Jon Noronha, Chief Product Officer, Gamma

⭐ Episodes Mentioned

To catch our entire conversation with Jon Noronha, head over to your favorite streaming platform for the full episode:

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