Proof model

Claim → Scenario → Run → Review → Decision

A claim about an agent or swarm is useful only when the system boundary, evidence class, scenario, run conditions, review, and decision are clear.

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Evidence flow

The proof chain

Each link can be inspected and challenged independently.

Claim
State exactly what the system, agent, control, or workflow is believed to do.
Scenario
Define representative inputs, context, tools, authority, constraints, and expected boundaries.
Run
Capture the versions, state, messages, calls, policy decisions, cost, latency, and outcome.
Review
Apply automated checks and named human judgment using explicit criteria.
Decision
Proceed, narrow, remediate, accept risk, defer, or stop—and record the conditions.

Classification

Evidence is labeled by what it can support.

Run evidence

Captured from a specific run or operating period with known versions and conditions.

Repeatability

Repeated under controlled conditions with materially consistent results.

Human judgment

Assessed by a named reviewer against stated criteria and authority.

Analysis

A reasoned conclusion from available evidence, explicitly marked as an inference.

Future state

A design, target, or control that has not yet been implemented or observed.

Gap

A material question that remains unresolved and affects the decision.

Swarm-level proof

Multi-agent systems can produce a plausible outcome through unsafe, wasteful, brittle, or irreproducible coordination.

Start with a bounded decision

A readiness sprint or evaluation engagement can turn an informal claim into a decision-ready proof chain.