Dynamic Expert Recruitment

Problem

A hard-coded role list is brittle: the team that suits a legal filing is not the team that suits a code refactor, and the writer-reviewer-editor lineup that helped the first request is dead weight for the second. Over-provisioning a large fixed pool wastes tokens and creates noise. Under-provisioning misses the specialist the task actually needed. Without a way to assemble the team at run time, every workflow either drags around unnecessary roles or quietly skips work that should have happened.

Solution

Add a recruiter agent (or a meta-agent committee: planner + agent observer + plan observer). Stage 1 — Drafting: recruiter receives the goal, generates role descriptions matched to that goal, instantiates the team and an execution plan. Stage 2 — Execution: the team works. Stage 3 — Evaluation: a reviewer scores progress; if unsatisfactory, the recruiter adjusts the team (add, remove, replace roles) and the next iteration runs. The recruiter is the only meta-agent that mutates team composition.

When to use

• Hard-coded role lists are brittle because the right team varies wildly across tasks.
• A recruiter agent can generate role descriptions and instantiate the team based on the goal.
• Evaluation feedback can drive team composition adjustments between iterations.