Pick a Mode and Record What the AI Workforce Holds

Multi-Player Mode

Use this when a Warwright effort starts or grows. Record its mode, what its AI Workforce holds, what stays out of it, and who reviews its work. Worked in “Start With One Builder, and Add Builders Only When One Can’t Do the Job.”

First, pick the mode from the modes table below.

The three modes: what each can own, its characteristic failure, and its rule.

Mode	Who, and what AI Workforce	Enough to own	Failure to watch	Rule
Single-player	One Warwright with one AI Workforce	A small, bounded piece: a plug-in, a staff section’s app, a configuration and its build record, a test card set, a parts log	Nobody reviews the builder’s judgment, and the knowledge rotates out with one person	Ships only inside a team or with a named reviewer; its build record passes Sustainment Tail Test question 2 first
Team	About 4 to 12 people, mostly warfighters, sharing one AI Workforce	A lane III or IV system class, end to end	The shared AI Workforce quietly becomes one member’s	The shared AI Workforce holds what each member knows, so a rotation doesn’t erase it
Multi-team	Several teams, each with its own AI Workforce, federated through shared specifications, interfaces, a registry, and a coordinating layer	A family of systems across a division or a fleet	The coordinating layer turns back into the old chain	Share interfaces and evidence. Never share one approval queue.

Mode

Who, and what AI Workforce

Enough to own

Failure to watch

Rule

Single-player

One Warwright with one AI Workforce

A small, bounded piece: a plug-in, a staff section’s app, a configuration and its build record, a test card set, a parts log

Nobody reviews the builder’s judgment, and the knowledge rotates out with one person

Ships only inside a team or with a named reviewer; its build record passes Sustainment Tail Test question 2 first

Team

About 4 to 12 people, mostly warfighters, sharing one AI Workforce

A lane III or IV system class, end to end

The shared AI Workforce quietly becomes one member’s

The shared AI Workforce holds what each member knows, so a rotation doesn’t erase it

Multi-team

Several teams, each with its own AI Workforce, federated through shared specifications, interfaces, a registry, and a coordinating layer

A family of systems across a division or a fleet

The coordinating layer turns back into the old chain

Share interfaces and evidence. Never share one approval queue.

Then fill in the one-page selector for the team.

The Multi-Player Mode selector for one team.

Field	What to write	Entry
The team	Name, charter date, members, and how many of them fight with the system
Its mode	Single-player, team, or multi-team, and what it owns in that mode
Specification	The SpecKit: the written specification of what the team builds and why, and where it’s versioned
Harness	The build and test environment, and the platform it deploys to (with that platform’s authorization)
Agents	Which AI agents draft, build, or test, and what each one may touch
Skills	The team’s methods written as skills (build steps, test cards, brief drafting), with version and owner
MCP connections	Each Model Context Protocol connection, the data it reaches, and who approved it
What stays out of it	Anything classified, controlled, or not publicly releasable; any tool the organization hasn’t approved; every decision that belongs to a person (authority, lanes, gates, rights clauses, requirements)
Its reviewer	The named person or team who reviews the work before anyone relies on it (for multi-team mode, the other teams, with the coordinating layer reconciling and never deciding)
Its failure to watch	The failure from the modes table for this mode, and the date someone last checked for it

Field

What to write

Entry

The team

Name, charter date, members, and how many of them fight with the system

Its mode

Single-player, team, or multi-team, and what it owns in that mode

Specification

The SpecKit: the written specification of what the team builds and why, and where it’s versioned

Harness

The build and test environment, and the platform it deploys to (with that platform’s authorization)

Agents

Which AI agents draft, build, or test, and what each one may touch

Skills

The team’s methods written as skills (build steps, test cards, brief drafting), with version and owner

MCP connections

Each Model Context Protocol connection, the data it reaches, and who approved it

What stays out of it

Anything classified, controlled, or not publicly releasable; any tool the organization hasn’t approved; every decision that belongs to a person (authority, lanes, gates, rights clauses, requirements)

Its reviewer

The named person or team who reviews the work before anyone relies on it (for multi-team mode, the other teams, with the coordinating layer reconciling and never deciding)

Its failure to watch

The failure from the modes table for this mode, and the date someone last checked for it

In every mode, the evidence comes from D0 or D1, and the build passes the same gates. The mode changes only what the team can own.