Playbooks

Reusable ways of working.

How AI moves from a promising demo to work you can actually run — named, so we can talk about it.

Playbook

AI Value Engineering

The discipline of converting AI pilots into governed production outcomes measured in Cost of Work.

The problem

AI investment is legible to boards; AI outcomes are not.

Engineer value; do not hope for it.

Playbook

Cost of Work

The unit economics of governed AI: cost per outcome, versus baseline, at governed quality.

The problem

Tokens and seats are illegible to the CFO signing the check.

Outcomes before tokens.

Playbook

Input → Consumption → Work → Outcome → Value

The five-stage translation chain from raw AI spend to enterprise value creation.

The problem

Programs measure the first two stages and assume the last three.

Consumption is not work. Work is not value.

Playbook

Pilot-to-Production Gap

The last-mile chasm between an approved pilot and a governed workflow in the operating model.

The problem

Investment stalls where the operating model has not been encoded.

The pilot-to-production gap is an operating model gap.

Playbook

Governed Reasoning Gap

The distance between what a model can infer and what a policy will let it act on.

The problem

Autonomy expands ahead of the governance layer that authorizes it.

Reasoning without governance is opinion.

Playbook

Earned Autonomy

A ratcheting model where agent authority expands only as governed behavior is proven.

The problem

Enterprises grant autonomy at launch, then withdraw it after incident.

Autonomy is earned by evidence, not granted by intent.

Playbook

AI Readiness Diagnostic

An executable instrument that names your position on the Pilot-to-Production Gap.

The problem

Leadership teams lack an honest, shared baseline before allocating.

Where is your program on the gap?

Playbook

Leverage Ladder

A staged progression of AI leverage from artifact assistance to autonomous governed work.

The problem

Programs jump rungs and land in incidents.

Skip a rung and you fall.

Playbook

PRISM Series

A running research program on the operating architecture of governed enterprise AI.

The problem

The literature confuses model capability with enterprise capability.

Refract the program before you scale it.

Playbook

Governed Decision Workflow

The reference pattern for embedding an AI-assisted decision into an enterprise system of record with policy and accountability.

The problem

AI outputs arrive as artifacts; decisions arrive without owners.

Every AI decision has a named owner or it did not happen.

Don't scale the pilot until the workflow, the guardrails, and the person on the hook are all clear.

AI Readiness Check

Take the check. Get one straight answer.

AI Readiness Check

Where is your program on the pilot-to-production gap?

Seven questions. Answer honestly and get back where you stand, what's still open, and the one thing to do next. No sign-in.

Q01AI-ready data
Is the data your AI systems operate on governed, versioned, and traceable to source?
Q02Encoded judgment
Where does the judgment used in AI outputs come from — a person reviewing each answer, or a codified policy the system enforces?
Q03Governance layer
Does a governance layer sit between AI reasoning and any action taken in your systems of record?
Q04Governed workflow
Are AI outputs part of a defined workflow with named accountability, or do they arrive as artifacts a user might use?
Q05Cost of Work
How is the value of your AI program measured?
Q06Pilot-to-production
How many of your AI pilots have crossed into governed production?
Q07Earned autonomy
Do your agents earn autonomy incrementally as their governed behavior is proven, or do they operate at a fixed level of authority?

0/7 answered