About Olivier.

My path into technology started in accounting and management at Vanier, before I moved into computer science at UQO. I remain interested in both: how systems work, and the economic forces that determine what gets built and used.

Financial markets are one way I follow those forces. I’m particularly interested in how AI changes the economics of products and companies, from the cost of computing to the new things a small team can attempt. That curiosity also extends to the physical side of technology: energy, infrastructure and robotics.

Within AI, I’m drawn to systems that carry context across interactions and participate in something larger than a single conversation. Questions about memory, behavior and how people interact with these systems inform my work on Kindoki.

I learn tools through the problems I’m trying to solve. At the Competition Bureau, I picked up enough PowerShell and C# during my first week to begin using them on the job. University projects similarly led me to learn the Java, Python or Rust needed for a particular task. A stack describes part of my experience; it doesn’t define the limits of what I can work on.

Codex, Antigravity and Kilo are part of my development workflow. I use AI coding tools to turn product ideas into software, refine requirements and iterate on the result. My role is to decide what the product should do and keep its development aligned with that intent.

I also explore ideas through smaller learning projects, including reinforcement-learning tutorials and Rainbow DQN experiments with Tetris. They give me a way to move beyond reading about a technique and observe its behavior firsthand.