Build an eval rubric for your AI Product from scratch

I'm co-founder of Lovelaice and a product leader with 10+ years building products across fintech, payments, and compliance. I hold a CFA charter and have led AI product development in highly regulated environments, where AI failures aren't just embarrassing, they're liabilities.

I've watched smart product teams make the same mistakes: choosing models based on benchmarks that don't reflect their use case, writing prompts that work in demos but fail in production, and leaving domain experts and PMs out of the AI iteration loop.

Through these failures (my own included), I developed a systematic approach to AI experimentation that puts product and domain expertise at the center. I teach what I've learned building Lovelaice: how to test, evaluate, and iterate on AI, before it reaches your users.

I bring over 14 years of software development expertise and a decade of startup experience to help teams build AI products that actually work. After founding my first company in 2019, I ran a consultancy in 2025, specializing in helping startups build MVPs, solve complex technical challenges, and integrate AI effectively.

I've seen firsthand how AI projects fail due to lack of experimentation and the right tools. Teams treat AI like traditional software and struggle with inconsistent results. That's why I co-created Lovelaice, a platform designed for non-technical professionals to experiment with AI agents systematically.