Cameron is a Developer Relations Engineer at .txt, helping developers use language models that generate reliable, structured output. With a PhD in finance and deep experience in probabilistic modeling, he bridges AI research and practical implementation.
The future of AI lies not in individual models but in the emergent capabilities that arise when we connect them through well-designed systems. Today's language models are powerful, and only improving. However, language models mean nothing without a system to support them -- language models need structure to tackle hard problems. This talk imagines how one might apply tools like structured generation in designing massive-scale AI systems.