The launch of DINQ's AI-native career network addresses what the company identifies as the most urgent constraint in artificial intelligence adoption: access to proven, skilled talent. As AI accelerates across industries, traditional hiring platforms relying on static resumes and keyword-based searches fail to capture how technical talent actually builds, collaborates, and grows. Many top AI researchers and engineers do not maintain conventional professional profiles, leaving their work, code, papers, and open-source contributions scattered and difficult to assess.
DINQ's solution is the DINQ Card, a dynamic professional identity that aggregates a user's research, repositories, and professional signals from platforms including GitHub, arXiv, Google Scholar, and LinkedIn into one continuously updated profile. This enables hiring teams to evaluate candidates based on what they have built rather than where they have worked. The platform is available now at https://dinq.me.
"AI is not just changing how we hire. It is redefining what talent even means," said Sam Ko, founder and CEO of DINQ. "In the AI era, resumes, titles, and static profiles are obsolete. What truly matters is the real signal: what you build, who you collaborate with, and how fast you evolve. AI talent recruitment must shift from keyword matching to understanding people as living systems." Co-founder and COO Kelvin Sun, a serial entrepreneur in talent recruitment who previously served at Sequoia Capital China, added, "Hiring for AI is no longer about pedigree. It is about performance. Recruiters need to see how a candidate contributes, who they have worked with, and where their impact is visible."
The timing of DINQ's launch aligns with the beginning of the 2026 hiring cycle, which historically sees increased activity from companies and new graduates. This positions the platform to address a significant market gap: industry estimates indicate more than two million AI-related roles will remain unfilled globally in 2026, with recruiters reporting growing difficulty sourcing qualified candidates despite record investment in AI infrastructure. By focusing on merit and momentum rather than traditional resumes, DINQ aims to bring clarity and efficiency to the hiring process, potentially accelerating innovation by better connecting talent with opportunities in a field where human capital has become the primary bottleneck.
