Can AI Fix Professional Networking? | Inside Cosign

Cosign’s central thesis is that professional networking could rely less on résumés and more on the people willing to vouch for someone’s work. On The a16z Show, a16z New Media’s David Booth and Dhruv Gupta join MTS to introduce a network built around relationship and reputation signals. The ambition extends beyond helping people find jobs, co-founders or collaborators: Cosign’s longer-term goal is to make those signals accessible to AI agents as well as humans.

The Cosign Awards provide a concrete example of this approach. They recognize standout operators, companies and products through nominations from people who know their work. The broader framework is to map people and relationships that rarely appear in public data, creating a graph that captures information a résumé or publicly visible professional profile may not convey. The discussion positions firsthand knowledge and willingness to vouch as inputs to professional discovery, rather than treating a person’s documented credentials as the only basis for finding a match.

The AI context makes access to that relationship graph central to the proposal. The speakers envision a personal agent communicating directly with a company’s agent, assessing potential fit and surfacing an opportunity only when there is a genuine “coincidence of intent.” This remains a forward-looking scenario, not a demonstrated outcome in the notes. The distinction between Cosign’s nomination-based recognition and its longer-term agent-access ambition is important: the notes explain the intended direction but do not establish how reputation signals would be evaluated, how access would be governed or how reliably agents could identify a suitable match.