AI & SAAS · CONTROL PATTERN · V1.0.0

The reasoning–execution boundary.

A concrete contract for allowing probabilistic systems to propose actions while deterministic services retain authority to execute them.

REFERENCE FIGURE / NR-002CONCEPTUAL VIEW · NOT A DEPLOYMENT TOPOLOGY
The reasoning–execution boundary. A concrete contract for allowing probabilistic systems to propose actions while deterministic services retain authority to execute them.
nishantr · nishantr.techOpen full-size figure ↗
THE PROBLEM

Why this pattern exists

An LLM may interpret language and propose actions but is not a safe owner of financial, contractual or transactional invariants.

DESIGN GUIDANCE

Principles to preserve

  1. Model output is a proposal, never proof of permission.
  2. Validate schema, identity, scope, preconditions and policy before any side effect.
  3. Distinguish read, propose, approve, execute and compensate permissions.
  4. Use idempotency keys and transactional boundaries for state changes.
  5. Retain structured evidence of decision, execution and outcome.
THE REAL DESIGN WORK

Trade-offs, not just boxes

  • Approvals improve risk control but add handoff latency.
  • Schema constraints narrow model flexibility but make integrations testable.
  • Compensation may be unavailable for irreversible external effects; design compensating business processes.
REVIEW QUESTIONS

Before you implement

  • Can a malicious or mistaken prompt bypass execution policy?
  • How are stale context and concurrent updates rejected?
  • Where does an irreversible action require escalation?
  • Can we replay the audit without replaying the model?
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