Artur is a systems architect and data engineer with over 20 years of experience in building end-to-end data platforms. As a Cloud Data Architect at Future Processing, he focuses on designing robust, scalable data ecosystems. He also engineers complex decision support systems and AI architectures for the London Insurance Market, bridging the gap between high-level business needs and production-grade execution environments.

Independently, he is the author and researcher behind the Decision Intelligence Runtime (DIR) and Responsibility-Oriented Agents (ROA) - architectural patterns that bridge probabilistic LLMs with the strict determinism required by critical business processes. His work on separating AI reasoning from execution has been featured on O'Reilly Radar.

To empirically validate these ideas, he built AIvestor, a research project operating on high-frequency financial data. Rather than just an investment tool, he uses live markets as a uniquely adversarial environment to stress-test real-time autonomy, state management, and decision integrity. Artur advocates for treating AI safety as a rigorous systems engineering challenge, not just a prompting exercise.