APPLIED_PLAYBOOK: AGENTIC GOVERNANCE

Harness Engineering for AI Agents

A definition-first playbook for Harness Engineering: wrapping AI agent execution with context boundaries, authority boundaries, evidence capture, plan/confirm/trace records, rollback, remediation, deterministic delivery, and accepted outcome.
BACK_TO: PLAYBOOKSCONCEPT_CORE: AGENTIC LIFECYCLE GOVERNANCE
READING_ORDER: APPLIED_PLAYBOOK

Start with one question.

Harness Engineering is the discipline of wrapping agent execution with lifecycle boundaries: context boundary, authority boundary, evidence capture, plan/confirm/trace records, rollback, remediation, configuration, and accepted outcome. It is the execution boundary layer behind Deterministic Delivery, not a replacement for prompt quality.

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  1. 01Definition
  2. 02Scenario
  3. 03Inputs and outputs
  4. 04Failure modes
  5. 05Evidence required
  6. 06Sources
DEFINITION

Harness Engineering is the discipline of wrapping agent execution with lifecycle boundaries: context boundary, authority boundary, evidence capture, plan/confirm/trace records, rollback, remediation, configuration, and accepted outcome. It is the execution boundary layer behind Deterministic Delivery, not a replacement for prompt quality.

Why ordinary model/tool governance is insufficient

Prompt engineering controls how intent is expressed to the model. Harness Engineering controls the execution boundary around the work. A prompt cannot substitute for context boundaries, authority boundaries, evidence capture, plan/confirm/trace records, rollback paths, remediation closure, configuration state, or accepted outcome state.

Source context

This playbook applies lifecycle-responsibility questions to the stated scenario. Its relevant responsibility objects are Context boundary, Authority boundary, Evidence chain, Decision trace, Accepted outcome, Remediation closure. The page is an author-analytical guide and does not add scores, legal conclusions, certification, or vendor assessment.

Configurable Agent GovernanceRollbackable Agent WorkflowsAccepted Outcome

Scenario and distinctive question

Question: What execution boundaries must surround an agent so intent becomes reviewable, reversible delivery?

Scenario: A runtime team wraps model calls and tools with context, authority, evidence, confirmation, rollback, and acceptance state.

Inputs

  • Agent intent and context
  • Tool and authority policy
  • Plan, confirmation, and trace hooks

Outputs

  • Harness boundary specification
  • Evidence capture points
  • Rollback and acceptance transitions

Lifecycle governance checklist

  1. Separate prompt controls from harness controls: the prompt expresses intent, while the harness governs execution boundaries.
  2. Define the context boundary so active, stale, background, and cross-project context are separated.
  3. Define the authority boundary before consequential action or tool use.
  4. Capture evidence that supports review, replay, dispute, and remediation.
  5. Represent plan, confirmation, and trace as durable lifecycle records.
  6. Define rollback and remediation behavior before failure occurs.
  7. Record accepted outcome state and the human role that can accept or reject work.
  8. Link harness configuration to Deterministic Delivery so lifecycle state can be inspected after execution.

Failure modes to test

  • Prompt quality is treated as execution governance
  • Tool authority is implicit
  • Runtime state cannot be replayed or remediated

Evidence required for review

  • Context and authority configuration
  • Plan/confirm/trace records
  • Rollback verification
  • Accepted outcome record

Related Missing Regulatory Objects

Context boundaryAuthority boundaryEvidence chainDecision traceAccepted outcomeRemediation closure

RCCS-M / ALCS relevance

RCCS-M is relevant because a harness can make lifecycle responsibility objects explicit. ALCS is relevant because the harness must keep those objects coherent across execution, review, dispute, remediation, and closure.

Protocol path: MPLP as one option

MPLP and Cognitive OS can be understood as possible paths for protocol semantics and runtime state around harnessed agent work. They are not required implementations.

Boundary statement

This playbook is an author-analytical governance guide. It is not legal advice, legal compliance proof, certification, regulator-approved guidance, vendor ranking, or procurement recommendation.