Exa co-founder Jeffrey Wang argues that technical teams can treat go-to-market as an AI engineering problem. Product quality and distribution both matter, while agents make research, qualification and customer support increasingly programmable.
Wang says the core requirement is a live model that combines internal product and customer data with external information about companies, people and current events. Exa exposes that context through agent interfaces, MCP-connected systems and customized tools that help teams research accounts, draft outreach and act on prior decisions.
He emphasizes permission boundaries and human oversight. Exa's internal agents expose different tools depending on the caller, while forward-deployed engineers combine domain work with maintaining the systems that support revenue teams.
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