Quantum Vibe Coding – with Vincent van Wingerden of Classiq

How do you go from a quantum computing research paper to a circuit you can run on a real machine? Can AI help bridge the gap between complex mathematical theory and functional quantum code? In this episode, Vincent van Wingerden, Director of Strategic Partnerships at Classiq, joins host Konstantinos Karagiannis to discuss the dawn of quantum vibe coding. While traditional quantum programming often requires tedious manual manipulation of gates and hardware-specific constraints, Classiq’s platform introduces a high-level abstraction that allows users to focus on intent rather than implementation. Vincent explains how their AI-driven assistant, powered by Claude, can ingest an academic paper from arXiv and generate a working implementation in minutes, a task that once took experts weeks of effort.  
Beyond the vibe, this episode dives into the practical mechanics of how Classiq’s compiler optimizes code across diverse hardware modalities, from IonQ to IBM. You’ll hear about real-world collaborations with Comcast and AMD, as well as a fascinating example of how an AI agent suggested improvements to an image-edge-detection algorithm that outperformed its original human design. Whether you are a seasoned computer scientist or a curious beginner looking to bypass the gate-level barrier, this conversation reveals how the synergy between high-level languages and AI is dismantling the quantum talent gap and scaling the industry toward the future.  
For more information on Classiq, visit www.classiq.io/.   
An example of quantum code aided by AI https://github.com/Classiq/classiq-library/tree/main/applications/image_processing/quantum_hadamard_edge_detection.

Visit Protiviti at www.protiviti.com/US-en/technology-consulting/quantum-computing-services to learn more about how Protiviti is helping organizations get post-quantum ready.  
Follow host Konstantinos Karagiannis on all socials: @KonstantHacker             
Questions and comments are welcome!  
Theme song by David Schwartz, copyright 2021.  
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