Playbooks
Evergreen checklists for running AI in a regulated enterprise. Each point has a one-line test you can hold a program against, and each playbook has a two-minute self-assessment.
- Governing coding agents in a bank: a 12-point checklist
The controls a regulated enterprise needs before coding agents write production code at scale. One page, kept current, meant to be copied into your own standards.
- Write down what each agent may do
- Give every agent its own identity
- Send every model call through one gateway
- Govern the tools as well as the models
- +8 more
- An AI operating model for a bank: ten decisions to make before the twentieth use case
How a regulated bank should organize, fund, govern and measure AI so that the first few wins turn into a portfolio instead of a pile of pilots.
- Name one accountable leader and a federated model
- Run a portfolio, not a pile of pilots
- Build the platform before the twentieth use case
- Tier use cases by risk and set controls by tier
- +6 more
- Gating AI investment: eight gates from pilot to production
A stage-gate checklist for funding AI use cases in a regulated enterprise: what evidence each gate needs, so money follows results instead of enthusiasm.
- The problem and its baseline
- A value hypothesis with a number
- Data rights and readiness
- Risk tier and controls
- +4 more