Coordinate three proactive AI agent teams through one shared record. Carry a late correction through analysis, narrative and slides, and give finance a pack to check, then release or return.
What you will be able to do
- Organize three agent teams with named owners: Assign your existing agents to Data and Control, Planning and Analysis, and Management Reporting. Give each team a scope, inputs, outputs, a list of actions it must not take, and a named owner such as the controller, the FP&A lead or the CFO.
- Write handoffs that refuse incomplete work: Design a shared record that holds the accepted dataset version, period, entity, currency, units, control status, assumption version and open exceptions. Write acceptance criteria so a receiving team rejects an incomplete handoff and records why.
- Follow the approved record with Dots or Claude Duet: Pick OpenAI Dots or Claude Duet under your organisation's rules for nonpublic data. Set it to follow the record across handoffs and return reconciliations, variance explanations and unresolved differences, with measured variances kept apart from explanations that have no evidence yet.
- Carry a late correction through the whole pack: Take a freight-accrual correction that arrives after the draft pack. Reconcile it into a new accepted version, mark dependent work as out of date, rerun only what it touched, return provisional text to its owner, hold the affected page and compare v1 with v2 in an impact log.
- Show the Factory fails safely: Test changing inputs, blocked work and an interrupted run that restarts later. Confirm that the Factory stops, flags the problem and resumes from the record without double-counting or quietly reusing stale results.
- Set the rules and checks finance signs against: Write operating rules: permissions, stop conditions, retry limits and an exception-ownership map. Build release checks for reconciliations, assumptions, cross-pack tie-outs and named sign-off. Then run a full simulated cycle and record the controls needed before any further use.
Taught at learn.m-a-s-t-e-r.ai: lessons that adapt to your level, an AI tutor you can ask anything, quizzes and flashcards, and a certificate when you finish.
