Everett Berry describes go-to-market engineeringAI go-to-market orchestration coordinates customer data, decisions, automated actions, human tasks, and communication channels around a commercial outcome. as the technical foundation that lets commercial teams change data, automations and campaigns at software-release speed. The foundation begins with a continuously updated model of target accounts and contacts, combining first-party events with third-party data while resolving the same company across multiple systemsEntity resolution identifies records from different sources that refer to the same real-world person, company, account, or object..
Everett Berry explains that orchestrationAgent orchestration coordinates AI agents, tools, people, tasks, state, and control flow so a larger workflow reaches a verified outcome. must keep customer relationship management, warehouses, communication tools and other services synchronized despite different update schedules and failure modes. A graph of triggers, tool calls, conditional logic, code and fan-out operations can collect context, perform work and push reliable results back to the systems used by human teams.
For AI agents, Everett Berry favors one persistent agent per accountA stateful agent preserves task information across multiple events and model calls so its AI behavior can continue coherently over time. that can remain dormant, wake on a signal or heartbeat, rebuild current contextContext engineering designs the information, instructions, memory, and tool state an AI receives so it can perform a task reliably. and maintain state across a long sales cycle. Because mistakes can reach customers, the design also needs separated agent-owned fields, explicit feedback and careful coordination between automated actions and the human representative who ultimately handles the relationship.
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