A shared system for repeat client analysis.

We began by reviewing the team's deliverables and how people used the existing system. We organized the new system around a separate workspace for each client: a place for its business background, the documents and tools used in its work, and a history of completed assignments. Selecting a client would bring the relevant information and access together at the start of a work session.

For recurring tasks, we wrote reusable instructions called skills. A skill explains how the AI assistant should carry out a particular task and how its output should be checked. This gave the team a shared method it could inspect and improve, with a review step before an individual suggestion changed the instructions everyone used.

Consultants have a repeatable starting point for AI-assisted work. They can select a client, use the relevant instructions and sources, and leave an assignment history that another colleague can follow. The saved examples let the team assess changes to its methods, while feedback provides a documented way to propose corrections.

The dashboard brings those individual workspaces into a shared portfolio view. It is rebuilt weekly from the summaries saved during client work, with dates showing how recent the information is. The firm received the workspaces, skills, checks and operating guidance together, giving its team the means to run the system and maintain its methods.