My designer life at MathWorks
My designer life at MathWorks
Workflow | Design & Research | Tools
Technical Support brought me valuable insight to customers daily life
I joined MathWorks at the end of 2022, and even now it sometimes feels unreal that I work here. I’ve never been someone who excelled at math or physics; the closest I came was studying Information Science in college.
My first few months as a Technical Support Engineer were a crash course in MATLAB and Simulink. I had to learn an entirely new technical ecosystem while helping customers solve their coding problems. It was challenging, but it taught me how engineers and scientists actually use these tools to tackle real-world problems.
A versatile channel for gathering user feedback.
We have a few challenges to do large scale A/B testing given our product is released only twice a year and reliability is a high customer request, we could not launch A/B test like other toC companies. Still, during my service at MATLAB Desktop, we gathered user feedback through multiple ways.
Regular 2h paid interview with MATLAB users to understand daily workflow
Technical report cases
Feedback button to collect user feedback from all over the world
DDUX (our data collection on user actions if signed up)
Also, we conducted company-wide review sessions twice a year, gathering intensive feedback from across the organization. These reviews included perspectives from many departments, including customer-facing engineers.
Designing with technical depth.
Our product sits deep in niche engineering domains. As a designer, I’m constantly picking up new terminology, workflows, and domain context — figuring out who the key players are and what the landscape looks like. I don’t code, but I’ve learned to observe carefully and ask the right questions. Agentic AI has become a real help for self-directed learning, and I regularly sync with my engineering team to make sure we’re reading the problem the same way.
In a world of endless AI tools, focus is my edge.
At MathWorks, everyone has access to Claude, so building things fast is the norm. As a designer, I use agentic tools to sharpen my writing, build realistic prototypes, and create small utilities that help my team move faster.
But it’s easy to get swept up in the noise — every week there’s a new tool, a new workflow, a new thing to learn. I don’t think AI changes the core of what we do. If anything, it asks more of us: more clarity about what actually matters, more time to sit and think.
I keep an eye on what’s new and explore tools occasionally, but I only go deep when something genuinely solves a problem I already have. If a simple Figma prototype gets the job done, that’s the right call.
Technical Support brought me valuable insight to customers daily life
I joined MathWorks at the end of 2022, and even now it sometimes feels unreal that I work here. I’ve never been someone who excelled at math or physics; the closest I came was studying Information Science in college.
My first few months as a Technical Support Engineer were a crash course in MATLAB and Simulink. I had to learn an entirely new technical ecosystem while helping customers solve their coding problems. It was challenging, but it taught me how engineers and scientists actually use these tools to tackle real-world problems.
A versatile channel for gathering user feedback.
We have a few challenges to do large scale A/B testing given our product is released only twice a year and reliability is a high customer request, we could not launch A/B test like other toC companies. Still, during my service at MATLAB Desktop, we gathered user feedback through multiple ways.
Regular 2h paid interview with MATLAB users to understand daily workflow
Technical report cases
Feedback button to collect user feedback from all over the world
DDUX (our data collection on user actions if signed up)
Also, we conducted company-wide review sessions twice a year, gathering intensive feedback from across the organization. These reviews included perspectives from many departments, including customer-facing engineers.
Designing with technical depth.
Our product sits deep in niche engineering domains. As a designer, I’m constantly picking up new terminology, workflows, and domain context — figuring out who the key players are and what the landscape looks like. I don’t code, but I’ve learned to observe carefully and ask the right questions. Agentic AI has become a real help for self-directed learning, and I regularly sync with my engineering team to make sure we’re reading the problem the same way.
In a world of endless AI tools, focus is my edge.
At MathWorks, everyone has access to Claude, so building things fast is the norm. As a designer, I use agentic tools to sharpen my writing, build realistic prototypes, and create small utilities that help my team move faster.
But it’s easy to get swept up in the noise — every week there’s a new tool, a new workflow, a new thing to learn. I don’t think AI changes the core of what we do. If anything, it asks more of us: more clarity about what actually matters, more time to sit and think.
I keep an eye on what’s new and explore tools occasionally, but I only go deep when something genuinely solves a problem I already have. If a simple Figma prototype gets the job done, that’s the right call.