I work at the intersection of artificial intelligence, backend engineering, and systems architecture, with years of experience in AI research and development across large language models, vision models, and production-grade software systems.
My technical work spans applied AI, model development, backend infrastructure, and architectural design. I’m especially interested in building systems that are powerful, scalable, interpretable, and robust enough to survive contact with reality.
My intellectual orientation sits between Aristotelian empiricism, Platonic rationalism, and a Cartesian approach to inquiry: observe carefully, reason from first principles, doubt weak assumptions, decompose hard problems, and search for structures that remain true under pressure.
Beyond engineering, I write and think about AI, civilization, and the long-term consequences of technological acceleration. My interests include modern rationality, AI alignment, mechanistic interpretability, theory of mind, machine consciousness, and the deeper question of what it means for a system to model the world, other minds, and eventually itself.
I’m also interested in planetary risk, existential risk, and planetary boundaries: whether our institutions, incentives, and technologies can scale without degrading the ecological and civilizational foundations they depend on. I see AI not merely as software, but as part of a larger evolutionary process: intelligence becoming recursive, industrialized, and increasingly difficult to govern.
My broader worldview is shaped by evolutionary biology, cognitive science, behavioral psychology, computation, and evolutionary-developmental thinking — from Darwinian selection and gene-centered evolution to biological constraint, computational universality, and grand questions about intelligence, complexity, and the universe.
I see my work as both technical and philosophical: building useful systems while trying to understand what those systems optimize for, what they make possible, and what they may quietly erode.