How to make confident design decisions at AI speed: A practical checklist
AI has dramatically accelerated how fast teams can design, build, and ship.
But there’s a growing problem:
Speed hasn’t made decisions easier.
In fact, it’s made them harder.
In a recent webinar, four experts—Jason Giles (VP of Product Design, UserTesting), Andrew Hogan (Head of Insights, Figma), Logan Morris (Senior Manager UX Research, CarMax), and Andy Stites (Principal Experience Designer, CarMax)—came together to unpack what’s actually happening inside modern product and design teams.
The takeaway?
Teams are moving faster than ever—but not necessarily with more confidence.
So we distilled that conversation into a practical checklist:
ON-DEMAND WEBINAR
Defensible Design: Making Confident Decisions at Speed
1. Don’t confuse speed with progress
AI has made it easy to create quickly—but that doesn’t mean you’re moving in the right direction.
As Andrew Hogan (Figma) explained:
“You have more people doing more tasks… more participation… but attention hasn’t actually increased that much.”
More ideas. More prototypes. More noise.
What to do:
Slow down just enough to ask: Are we aligned on the problem we’re solving?
2. Prioritize alignment—not just output
High-fidelity prototypes are no longer a signal of quality.
Everyone can create them.
What matters now is whether teams are aligned on what to build.
Andy Stites (CarMax) put it clearly:
“Moving fast doesn’t imply quality… it’s also about how fast you can align internally.”
What to do:
Build rituals that ensure teams align on insights—not just artifacts.
3. Treat discovery as continuous—not a phase
One of the biggest shifts: discovery is no longer something you do once.
It’s something you do all the time.
As Logan Morris (CarMax) explained:
“Discovery needs to be viewed as a continuous practice… not something done in lumps along the product development life cycle.”
What to do:
Make customer feedback a weekly habit—not a project milestone.
4. Use AI to go faster—but not to replace humans
AI has made synthesis and analysis dramatically faster.
But it can’t replace real human understanding.
Logan highlighted the risk:
“If everybody’s asking the same questions to the same AI… you run the risk of everything looking the same and feeling the same.”
What to do:
Use AI to accelerate research—but ground decisions in real human insight.
5. Double down on expert judgment
When everything becomes easier to create, knowing what’s right becomes harder.
That’s where expertise matters more—not less.
Andrew explained:
“Expert judgment… becomes more critical because you’re overwhelmed with options.”
What to do:
Invest in developing taste, intuition, and domain expertise—not just tools.
6. Make research faster—but protect its quality
Research isn’t “too slow.”
It just hasn’t sped up at the same rate as everything else.
As Logan pointed out:
“Discovery isn’t moving too slow… it’s just moving at the pace it always has while everything else is accelerating.”
What to do:
Use AI to speed up synthesis and testing—but protect time for real understanding.
7. Assume you’re wrong—and test accordingly
High-performing teams don’t rely on confidence alone.
They rely on validation.
At CarMax, this mindset is baked in:
“We test things because we assume we’re wrong.” — Andy Stites
What to do:
Treat testing as a default, not an exception.
8. Design your workflows around where decisions happen
Research can’t live in a separate tool or process anymore.
It has to show up where work happens.
As the panel discussed, embedding insights into tools like Figma allows teams to validate decisions in real time—without slowing down.
What to do:
Bring research into the workflow—not outside of it.
9. Optimize for insight adoption—not just insight creation
Generating insights isn’t enough.
They need to land—and drive action.
Andy shared how teams are adapting:
“We can take insights and format them in multiple ways… depending on the audience… so they actually act on it.”
What to do:
Tailor insights to stakeholders so they’re understood—and used.
10. Create space for real discussion
In a world of AI summaries and rapid output, one thing still matters:
Human conversation.
As Andrew emphasized:
“There is no substitute for getting together around information and discussing it deeply.”
What to do:
Make time for teams to interpret insights together—not just consume them.
Figma + UserTesting
Learn how design and research teams can test prototypes, gather rapid feedback, and make more confident product decisions without leaving Figma.
Further learning
- Figma + UserTesting — Learn how design and research teams can test prototypes, gather rapid feedback, and make more confident product decisions without leaving Figma.
- Continuous discovery: transform your product development process — This on-demand webinar explores how product, design, and research teams can integrate continuous discovery practices into faster-moving workflows while staying grounded in customer insight. Especially relevant to the discussion around continuous discovery and defensible design decisions.
- Customer-first innovation and discovery guide — A guide focused on uncovering unmet customer needs, validating ideas earlier, and building customer-centric products through ongoing discovery and innovation research. Strongly aligned with the webinar’s emphasis on continuous customer understanding and AI-powered UX research.
- Design’s critical role in AI products: Insights from Figma — A UserTesting Insights Unlocked episode featuring Andrew Hogan discussing AI in product design, judgment, design workflows, and the future of craft in AI-assisted product development. Closely connected to the webinar’s themes around AI-assisted design workflows and human judgment.
- AI-powered customer insights in your Figma design workflows — A blog post about embedding AI-powered user research directly into Figma workflows to help teams make faster, more confident product decisions while keeping customer insight at the center of design.
