So why did OpenAI acquire Jony Ive's startup for $6.5B?
When Sam Altman spoke to our YC X25 batch last Monday, he casually dropped a vision that stuck with me:
"Just-In-Time UI" – mobiles in terface that adapts to your needs, contextually and intelligently.
Fast-forward to OpenAI's acquisition of Jony Ive's LoveFrom studio, and it's crystal clear:
We're entering a world where AI doesn't just power apps - it designs and renders the experience itself on demand, contextually and intelligently. Unlike traditional UIs with static buttons, tabs, and menus, JIT UI is a dynamic interface system that adjusts based on context, behavior, and intent.
Think:
- A calendar app that shows navigation when it senses you're running late.
- A health app that reconfigures its home screen after your workout.
- An edtech app that adapts depending on who's using it (e.g. child vs. power user)
It's a state-of-the-art cognitive component in UI.
Jony Ive's legacy - from the iPod scroll wheel to the iPhone's keyboard-less interface - has always been about removing friction. OpenAI's language and vision models excel at reasoning and interpreting intent. Together, they could deliver the first truly intelligent mobile device (phone? glasses? watches?) - one that not only understands what you want, but presents it gracefully.
So here's the blunt reality for mobile teams:
🌀 The Future Is Adaptive
JIT Mobile UI is more than a design pattern - it's a philosophy. It's a state-of-the-art cognitive component in UI.
If your QA still relies on hardcoded test scripts and static flows, your engineering org may be left behind.
A new category is emerging.
At QualGent (YC X25), we're building for this future - helping teams test mobile apps the way real users experience them. Our AI agents navigate apps contextually, detect issues autonomously, and surface actionable insights that traditional tools miss.
We believe the rise of Just-In-Time UI will reshape not only how apps are designed, but how quality is defined.
Since our launch two weeks ago, we've had tons of inbounds from forward-thinking engineering teams around the world.
Teams adopting AI-powered mobile QA platforms like QualGent are positioning to:
- Reduce regression risk across personalized interfaces
- Accelerate releases without compromising stability
- Scale QA without scaling headcount
Meanwhile, teams that delay may face:
- More production bugs in dynamic environments
- Slower launches due to brittle automation
- Eroding user trust from inconsistent app quality
Those preparing now ➡️ will lead the next wave of AI-native, consumer-grade software.
Those who don't ➡️ risk building for a world that's already disappearing.