Early, zero-to-one work where I own the product and see the impact directly. I'm energized by small teams with high standards, fast feedback loops, and real users — and by problems where shipping something today beats planning something perfect.
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Early, zero-to-one work where I own the product and see the impact directly. I'm energized by small teams with high standards, fast feedback loops, and real users — and by problems where shipping something today beats planning something perfect.
Solving user needs with technology. It's not about creating the most sophisticated technological solution—it's about providing your users with the simplest, easiest way to achieve their goals or solve their needs. That focus on what users actually need, to predict what they will find useful - that's what got 5 million researchers in academia and pharma to adopt GeneCards and use it as their daily driver.
Tell me the thing is impossible to do. Everyone who has tried it failed. This has been a running problem in the organization for years.
Especially now that AI compresses the amount of effort for work, the part of me that likes solving puzzles needs something meaty to chew on.
I build video content for SaaS companies trying to get more users and keep them longer. Sounds narrow, but it's not. When onboarding works, people actually use the tools they bought. When tutorials are clear, they spend less time frustrated and more time doing real work. When search finds the right answer fast, someone solves their problem instead of giving up.
That's the work I believe in. Not the metrics or the growth charts, but the moment when a user gets it, when the software stops being friction and starts being useful. Every tutorial I've made, every onboarding flow I've helped fix, that's someone's day getting a little easier. That matters to me more than the pitch.
Problem solving is what gets me out of bed. Not the abstract kind—the concrete, messy kind where you're staring at a broken system and have to figure out why.
I've done this across domains. Warehouse automation at BairesDev. Early diabetic retinopathy detection at Universidad Americana. Now conversational AI at Saywise. The pattern is the same: hard problem, real constraints, think your way through. That's what energizes me. Not the title. The moment when something clicks and the system works.