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Operations·Big bet

Run operations from exceptions, not dashboards

One queue surfaces only breached rules, explains why each item matters, and assigns the next human action.

The problem

Operators scan multiple dashboards looking for the few orders, projects, or handoffs that actually need intervention.

What you get

A working system with the steps, tools, checkpoints, and expected return made explicit.

Setup
180 minutes
Back each week
8 hours
Difficulty
agentic

Expected return

The working case

A planning estimate, not a guaranteed result. Measure the first four weeks against your own baseline.

384

hours returned per year

At 8 hours/week across 48 working weeks.

1

week to earn back setup

Compare the setup estimate with the weekly time returned.

Operating contract

Input

The source material, constraints, and examples a human would need to do this work well.

Checkpoint

A person reviews judgment calls, sensitive content, unfamiliar tools, and irreversible actions.

Success signal

Track time returned, corrections required, and exceptions. Keep it only if the measured result compounds.

Before you start

The steps

  1. 01

    Choose one process and write deterministic exception rules before adding AI.

  2. 02

    Join the minimum fields needed to detect late, blocked, incomplete, or contradictory records.

  3. 03

    Use AI only to summarize context and recommend a reversible next action.

    Copy this prompt

    Summarize why this item breached rule [rule], quote the relevant fields, identify the owner, and propose one reversible next action. Do not change the source system. Record: [data]

  4. 04

    Operators resolve, snooze with reason, or correct false positives; review rules weekly.

What it runs on

Where this goes wrong

Definition of done

Run it for four weeks. Then make it earn its place.

Build the system around it

Related workflows

If this one stops working, tell us. Three reports in a month and it leaves the library until a person has looked at it again.