Quantum Workforce Intelligence from qubitsok.com with Piotr Lewandowski

Piotr Lewandowski is a software engineer based in Poland who, as a side project, has built something that no well-funded research institute has: a continuously updated, ontology-tagged intelligence platform that ingests the entire quant-ph archive, tracks thousands of open quantum roles across hundreds of companies, parses patents and grants and open-source repositories, and links all of it to individual researcher profiles. He is not a tenured academic or a hardware engineer. He is an independent data practitioner, and that outsider position gives him a vantage point on the quantum workforce that insiders rarely have — or rarely share. This conversation matters now because the quantum industry is simultaneously claiming a generational workforce opportunity and struggling to fill highly specialized roles. Lewandowski's data offers a rare ground-truth check on both claims. If you work in quantum hiring, research, policy, or investment — or if you're a student trying to understand what the field actually looks like from the outside — this episode will give you a more honest picture than almost anything else currently available. What We Get Into How qubitsok's 500-tag ontology was built from scratch — why Lewandowski chose a tree-structured, parent-child tag system rather than relying on existing academic metadata infrastructure, and how it steers AI toward the most specific and useful classification rather than broad category labels. What the full quant-ph corpus reveals about researcher mobility — which countries are gaining quantum talent (Germany and China are notable winners) and which are losing it (the US and Australia are among the top brain-drain sources), based on tracking affiliation changes over time in published papers. The rising share of industry authorship in quantum research — industry-affiliated authors have grown from roughly 3.4% of quant-ph papers in 2005 to nearly 14% in 2026, and what that structural shift might mean for what gets published — and what doesn't. Why the platform tracks open-source contributions alongside papers — when researchers join industry and their publication rate drops, their open-source activity becomes a meaningful proxy for continued technical engagement, and qubitsok indexes both. The "qubie" talent-matching tool Lewandowski is building — rather than keyword overlap, qubie dispatches sub-agents to extract specific, claim-level evidence from a researcher's papers, dissertations, and other public writing, then returns a structured profile and interview guide for each candidate. Why sourcing quantum talent is a fundamentally different problem than general tech recruiting — the evidence of what a quantum researcher can actually do is largely public and published, but no one has had the infrastructure to read it systematically at scale until now. The two product directions Lewandowski is weighing — analytics and competitive intelligence for investors and companies versus talent matching for quantum hiring — and why he's currently prioritizing the latter. What it means to build a field-level intelligence platform as an outsider — Lewandowski is neither employed by a quantum company nor affiliated with a university, and that independence shapes both what he can see and what he can say. Resources & Links Guest Links qubitsok.com — The platform itself: quantum job board, daily arXiv paper digest with semantic tagging, and researcher collaboration search. All free for researchers and job seekers. qubitsok.com/collaborate — Search for quantum researchers by expertise, ontology tag, and affiliation — useful for