UX for AI teams
We bring UX into how your team builds with AI. We find where the agents' choices fall short, carry your brand into what they make and test it with real users.
With AI agents your team turns ideas into working screens faster than ever, and much of it works fine. But an agent picks the most common answer, not the best one for your users. So your product gets the same components, the same font and the same gradient as every other, and looks like AI made it. We bring out what it could be: a better experience, in your own brand, tested with real users.
- Your team builds with AI faster than anyone can check it
- It works, but it doesn't feel as good as it could
- Your product looks like every other AI product
- What gets built doesn't match what users need
- Every agent makes its own design choices
- You only hear where users get stuck once the numbers drop
- Where the agents' choices fall short, ranked
- Goals and user needs set down
- Your brand as a theme the agents apply
- A design system your agents can read
- Tests with real users
- An early warning when users stall
Your agents build on the brand and rules we set down, and AI lines up the reviews and tests; whether it helps your users, we judge with them.
Review what the agents made
Much of what an agent makes works fine. We go through it the way your users do and show where a better choice was there to make.
- What we do
- Judge which choices get in your users' way and what to fix first.
- How AI helps us
- Goes through every screen and lists where it strays from its own patterns.
Decide what's worth building
Before anything is generated, we set the goals and the users' needs with you, so the agents work on what matters.
- What we do
- Decide with you what is worth building, and for whom.
- How AI helps us
- Sorts the market, the data and the requests into options.
Make it look like yours
We translate your brand into the type, color and motion the agents apply on every screen.
- What we do
- Judge what feels like you and what still looks generated.
- How AI helps us
- Puts what the agents made in your brand, in many variations.
Set the rules
Your agents get the same components and rules as your team, in a form they can follow.
- What we do
- Decide what becomes the rule, so every agent follows the same one.
- How AI helps us
- Writes the first components, tokens and documentation.
Test with users
Real users try what the agents made. You see where it works and where it doesn't, before it goes live.
- What we do
- Watch users and judge what is a real problem.
- How AI helps us
- Sets up the test and sorts what users said and did.
Watch the signals
Once it is live, we see in the data where users stall, so the next round starts there.
- What we do
- Judge what a change means and what to do next.
- How AI helps us
- Watches how the product is used and raises what stands out.
- Your team keeps building, with its own AI agents. We add what they can't: a critical eye on their choices, your brand, the rules they follow and tests with real users.
- Anyone with access to AI can make something that works these days. The difference is a product people enjoy using and that pays off. Often a flow keeps steps it doesn't need, or the key action doesn't stand out. The audit shows where, ranked by what it costs your users.
- Because agents fill every open choice with the most common answer. We give them your brand as tokens and rules, so the common answer becomes yours.
- Any your team uses. We write the design system down as plain files and documentation, so every agent that reads text can follow it.
- Yes. Many teams start with an audit of what the agents made, or with the design system, and add the rest once it proves its worth.
Is your question not here?Jasper is happy to answer it.