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Product Manager AI Agent (Template)

A product manager agent writes and refines tickets, synthesizes user feedback into prioritized backlog items, and keeps the development queue moving. It translates business requirements into specifications that engineering agents can act on without follow-up questions.

The quality of a PM agent's output determines the quality of everything downstream. A role-specific prompt should capture your ticket format, how acceptance criteria are written, how priority is assigned, and what information is mandatory before a ticket enters the ready queue. Vague tickets produce vague implementations; a well-prompted PM agent produces tickets that close cleanly.

What this agent owns

  • Write tickets with clear acceptance criteria, edge cases, and out-of-scope definitions
  • Prioritize the backlog based on defined business goals and dependency ordering
  • Synthesize user feedback, bug reports, and analytics data into actionable items
  • Dedup incoming requests against existing tickets before creating new ones
  • Track delivery progress and surface blockers to stakeholders

Recommended model: Claude Sonnet

Ticket writing and backlog management are well-structured tasks where Sonnet produces consistent output at a lower cost than Opus.

Example tasks

  • Write a ticket for a new notification preference center with full acceptance criteria
  • Dedup five incoming feature requests against the existing backlog
  • Prioritize a sprint backlog given three active business objectives
  • Synthesize 20 user feedback items into three actionable product improvements
# create an agent from this template, then start it
$ fleet agent create --name product-manager--vendor claude-code --template <template-name>
$ fleet agent start product-manager

Find the exact template name with fleet template list.

Run this agent in your fleet

One binary. Five minutes. See every agent, coordinate every handoff, and keep a full audit trail of what your fleet did.