Implement agent policy simulation

A proposed policy can be evaluated against historical decision inputs without granting live effects.

01 / The operating case

What changes in a real workflow?

A new rule may widen payment limits for finance agents.

Trace the authority boundary
  1. 01Authority origin
  2. 02Task and grant
  3. 03Current decision
  4. 04Observed outcome

02 / Decision contract

What the executor must check

Replay redacted requests against old and proposed policy versions, compare verdict and reason changes, and review high-impact newly allowed cases before release.

InputPrincipal · task · action · target
DecisionGrant ancestry · policy · current state
ResultEnforce · record · verify outcome

03 / Failure and evidence

What goes wrong, and what can be proven?

Failure mode

A simulation reuses stale or incomplete context and falsely predicts that no actions change.

Evidence to retain

Retain policy digests, input coverage, changed verdicts and review signoff.

04 / Canonical scope

Why this reference stands alone

Policy tests use deterministic cases; simulation measures impact on representative traffic.

Illustrative implementation artifact

Verdict-delta report

for recordedRequest in representativeTraffic:
  old = evaluate(oldPolicy, recordedRequest)
  new = evaluate(candidatePolicy, recordedRequest)
  if old != new: classify action risk and review
never execute during simulation

Primary references

Read the underlying material

Architecture discussion

Choose one consequential action and make its boundary explicit.

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