Thomas Ager is a founder and AI researcher with 11 years of experience who earned a PhD in Interpretable Machine Learning from Cardiff University and now focuses on practical, open-source tooling for structured prompting. He leads Sophia Intelligence and (: Smile, where he has distilled novel prompt engineering methods—a new prompt instruction language and a library of modular, composable prompt modules—into a GUI and reusable workflows for reliable LLM behavior. His work bridges academic interpretability research and product-facing AI, applying principled vector-space insights to real-world multi-agent and multi-turn prompting problems. Thomas has also built AI systems for automated content generation at Crystallization Culture and consulted on automated transcript-to-article pipelines, showing a knack for turning research into repeatable engineering. A practiced traveller and retreat leader, he blends mindfulness and earth-data perspectives into eco-aware AI projects, and is actively open-sourcing his "(: Smile" prompt language on GitHub.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Artificial Intelligence, Doctor of Philosophy (Ph.D.) Artificial Intelligence at Cardiff University / Prifysgol Caerdydd
Contributions:47 commits, 46 pushes, 1 branch in 1 month
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