2-4 weeks · Teams ready to move from AI curiosity to a maintained workflow.

Agent-Assisted Operations Sprint

Design and deploy a practical AI-assisted operating workflow.

Scope an operations sprintBack home

What this solves

This sprint turns one known operational bottleneck into a working assisted workflow. It is not a lab demo. The goal is a narrow system a team can run, review, and improve without pretending the AI is now the manager.

Good candidates include inbound request triage, recurring research briefs, internal follow-up drafting, document routing, CRM hygiene, or executive briefing loops.

Sprint shape

  • Confirm the workflow boundary and the first useful artifact.
  • Design the human approval path before adding automation.
  • Connect the minimum tools needed for the prototype or production slice.
  • Test against real examples, including messy edge cases.
  • Document ownership, monitoring, failure handling, and iteration cadence.

Deliverables

  • A working workflow slice: prototype or production-ready depending on access, risk, and scope.
  • A runbook explaining inputs, outputs, review steps, escalation paths, and maintenance owner.
  • A backlog of follow-up improvements that should not be crammed into the first release.

What we need from you

  • A workflow owner who can test and approve outputs.
  • Representative examples, including bad inputs and exception cases.
  • Tool access or safe exports for the systems involved.
  • A clear answer on what the workflow is not allowed to automate yet.

Before the sprint, send the agent-assisted operations sprint input packet. It asks for the workflow scope, ten recent examples, safe access path, review rule, stop conditions, launch surface, and maintenance owner.

Risks and constraints

The sprint is a bad fit if the process owner is unavailable, the data source is off-limits, or the team wants autonomy before review discipline. In those cases, start with the audit and fix the workflow boundary first.