Coming soonBringing a business-critical interface in-house.FlinkFlink's customer experience was fast, but the systems behind it were complex, so I brought the business-critical Hub interface in-house to make daily operations easier to manage.Senior Product Design Engineer
Designer/Builder
I turn complexity and AI output into clear, working software for founders and product teams that need senior product judgment and interaction design. I deliver testable pilots or functional products. I work in strategic setups or fully operational settings. 10+ years of experience.
My Approach
I help companies reduce the noise and increase the signal. I look for the shortest path from zero to one.
I have worked across strategy, design and engineering - from early ambiguity to production.
A selected list of clients over the years.
From ambiguous idea to working product.
A selection of
Works
Products, systems and experiments from early idea to production.
0 → 1 Product. Native Apps in Swift and Kotlin.Social WorkoutsSocial Workouts started as a way to coordinate workouts over chat, and I turned it into a focused native product for crews and athletes.
AI product exploration, 0 → 1 fully working MVP.FAAASTFAAAST explores how AI can support serious endurance training without taking control away from the athlete, now with a small number of paying customers.
Product and brand direction for B2B food wholesale.ChefsListChefsList was moving food wholesale into digital ordering, and I helped shape the brand and interface around the complexity of professional kitchens.- Coming soonBringing a business-critical interface in-house.FlinkFlink's customer experience was fast, but the systems behind it were complex, so I brought the business-critical Hub interface in-house to make daily operations easier to manage.
AI-enabled product loop.
AI can shorten the path from an idea to a testable product. Real behavior still decides what stays.Start with the smallest thing you can build or the smallest thing you can learn.
What is the smallest thing we can build?
DesignBuildLearn
Faster Cycles
Reality Check
What would give us the clearest signal?
AI makes it easy to build more. The harder question is what deserves to be built in the first place. I look for the smallest intervention that lets us test an assumption, learn from real behavior and decide what happens next.
Faster build times make it easier to test more ideas. An MVP still needs a clear reason to exist and an experience people can trust.
Begin with the problem space, then shape the solution.
UX strategy means stepping back from the requested fix and looking at the wider problem. The first ask is often built on a flawed assumption.
I clarify the problem with stakeholders and customers, then turn the findings into a UX-informed roadmap that gets us to zero to one.
Framing the problem.
State the hypothesis.
Are we seeing the same problem?
What assumption are we testing?
Reframing the problem,
with stakeholders and customers.
What changed when we spoke to stakeholders and customers?
Which parts of the problem need reframing?
Inform Developers.
Roadmap.
What does the team need to build next?
What belongs on the roadmap?
50%
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The Impact
Helping lead a business-critical inhousing project while coordinating stakeholders and interviews across departments.
The work became the foundation for a central dashboard used across the organization.
Team
Head of Products
Mitch Seguin
Sahil Gulhane
Product Management
Somto Zikora
Open Source
Agentic work changes how I build. I also work on reducing the slack around it. Too much signal is still noise.
Open Source
@hamedb89I have been building my own tools. AI is only as intelligent as the pipeline. Product outcomes are not guaranteed when an agent doesn't know what to do, where to look or what the right context is for the task.
I built my own package to code faster, save on tokens and keep most of the workflow deterministic instead of letting the agents handle the fuzzy work.
It doesn't matter where and how the LLM is hosted. The tools stay the same.