# Human Approval Boundaries
Generated: 2026-09-13T04:42:43.842Z
Source build: local
Canonical docs: https://teammately.ai/docs
---
id: governance.human-approval-boundaries
title: Human Approval Boundaries
summary: Define which AI-assisted suggestions require accountable human review before becoming standards.
kind: reference
product_area: governance
status: stable
updated: 2026-09-07
canonical: /docs/governance/human-approval-boundaries
---
# Human Approval Boundaries
## Definition
Human approval boundaries separate preparation from governed correctness evidence. A suggestion, reviewer comment, interview answer, or draft standard can inform the loop, but it should not govern benchmark interpretation until the relevant human approval state is clear.
Use this page when prepared or contributed material is about to become a governed Policy, Rubric, Case-scoped reference output, or selected Benchmark Dataset evidence.
Comparison Directions are a narrower configuration object, not a governed standard. An AI-suggested Comparison Direction can be active without a separate approval step, but generated Cases, Benchmark membership, Policies, Rubrics, and reference outputs still follow their owning review or approval boundaries. A customer-owned human review packet is assembled from evidence; it is not a Teammately approval state.
> Approval is a state transition
>
> AI-assisted suggestions do not become governed standards until an accountable human approves the relevant artifact.
## Fields, states, or lifecycle rules
- Draft suggestions and reviewer notes are preparation material.
- Approved Policies and Rubrics, reviewed Case changes, selected Dataset membership, and supported Case-scoped reference outputs can affect governed evidence.
- AI-suggested Comparison Directions can affect future variant generation as active directions, but they do not approve the generated cases or standards they help explore.
- Approval should name the artifact being approved, not only the discussion that produced it.
- Stale or superseded approvals should be visible before older benchmark evidence is reused.
- This page does not claim external compliance approval, legal signoff, or production deployment authorization.
## Related objects
Read this with [What AI Features Can and Cannot Do](/docs/governance/what-ai-features-can-and-cannot-do), [Comparison Directions](/docs/assets/comparison-directions), [Approving Suggested Policies](/docs/correctness-governance/policies-and-rubrics), [Editing Suggested Rubrics](/docs/correctness-governance/policies-and-rubrics), and [Approval History and Reviewer Activity](/docs/governance/approval-history-and-reviewer-activity).
{% example-demo title="Human Approval Boundaries boundary" %}
Reviewer context: Several experts reject unsupported refund exceptions.
Suggested policy: The system proposes a policy that exceptions require approved support.
Approval boundary: The suggestion becomes governed only when a human owner approves the policy and its applicability.
Benchmark interpretation: Runs should cite the approved policy, not the unapproved suggestion that preceded it.
{% /example-demo %}
## Source confidence
Code-backed: Policy approval and activity components expose accountable approval state and history; contributed-artifact types keep expert learning distinct from materialized governed objects. Comparison Directions deliberately use active, archived, and advisory-stale behavior instead of the Policy approval lifecycle.
## Related task pages
{% related-card-grid title="Related task pages" %}
- [What AI Features Can and Cannot Do](/docs/governance/what-ai-features-can-and-cannot-do)
- [Comparison Directions](/docs/assets/comparison-directions)
- [Review Policies and Rubrics](/docs/correctness-governance/policies-and-rubrics)
- [Product quickstart](/docs/quickstart)
- [Task index](/docs/operating-manual/task-index)
{% /related-card-grid %}
---
id: governance.ai-feature-boundaries
title: What AI Features Can and Cannot Do
summary: Explain the difference between AI-assisted suggestions and approved correctness infrastructure.
kind: reference
product_area: governance
status: stable
updated: 2026-09-07
canonical: /docs/governance/what-ai-features-can-and-cannot-do
---
# What AI Features Can and Cannot Do
## Definition
AI-assisted features can help prepare correctness work, but they do not own the approval boundary. They may draft, classify, summarize, propose, or organize artifacts; a human still needs to approve governed standards and review context before benchmark evidence depends on them.
Use this page when a reader needs to separate preparation from authority. A fluent suggestion can be useful, but it is not an approved Policy, Rubric, Case-scoped reference output, Benchmark evidence, or downstream customer decision by itself.
> Human approval boundary
>
> AI features can draft, summarize, classify, or suggest; they do not approve policies, rubrics, benchmark evidence, or customer-owned decisions by themselves.
## Fields, states, or lifecycle rules
- AI-assisted output can be draft material, review support, classification help, or summarization.
- AI-assisted output should not be treated as approved standards, benchmark evidence, or customer-owned decisions without human approval.
- Suggested policies, rubrics, and classifications need visible approval or rejection state before they affect governed evidence.
- AI-suggested Comparison Directions are different from suggested standards: they can become active directions immediately, but they still do not approve policies, rubrics, cases, benchmark membership, or review context.
- AI-assistance language does not establish model-provider behavior, data retention, compliance posture, or autonomous approval.
- Source-backed product pages decide exact supported behavior; this page defines the public boundary.
## Related objects
Read this with [Human Approval Boundaries](/docs/governance/human-approval-boundaries), [Comparison Directions](/docs/assets/comparison-directions), [Using Expert Judgment](/docs/concepts/correctness-elicitation), [Using Checkpoints](/docs/expert-contributions/complete-contribution), and [Noisy AI Suggestions](/docs/troubleshooting/noisy-ai-suggestions).
{% example-demo title="What AI Features Can and Cannot Do boundary" %}
Draft suggestion: An AI-assisted workflow proposes a new compatibility policy after reading rejected cases.
Allowed use: The suggestion can help a reviewer start the policy draft.
Not allowed as governed evidence: A benchmark should not cite the policy until an accountable human approves the artifact and its applicability.
Interpretation: The AI feature accelerated preparation; the human approval boundary still controls whether the standard can govern benchmark evidence.
{% /example-demo %}
{% example-demo title="Example: active AI-suggested direction" %}
AI-suggested direction: Teammately suggests a stale-source conflict Comparison Direction after project cases and ontology values show that gap.
Allowed use: The direction can become active immediately and can guide preview examples or future variant generation.
Not allowed as governed evidence: The direction does not approve a policy, rubric, generated case, benchmark membership, or downstream decision. Users still review generated examples and manage the direction normally.
{% /example-demo %}
## Source confidence
Code-backed: generation surfaces can propose Dimension schemas, synthesize candidate Cases, and suggest Comparison Directions; Policy approval and contributed-artifact state establish separate human-governance boundaries. These sources support the product-state distinction here, not claims about model providers, retention, or autonomous authority.
## Related task pages
{% related-card-grid title="Related task pages" %}
- [Human Approval Boundaries](/docs/governance/human-approval-boundaries)
- [Comparison Directions](/docs/assets/comparison-directions)
- [Using Expert Judgment](/docs/concepts/correctness-elicitation)
- [Using Checkpoints](/docs/expert-contributions/complete-contribution)
- [Product quickstart](/docs/quickstart)
- [Task index](/docs/operating-manual/task-index)
{% /related-card-grid %}
---
id: assets.comparison-directions
title: Comparison Directions
summary: Create reusable guidance for meaningful candidate-output differences in comparative expert work.
kind: reference
product_area: assets
status: stable
updated: 2026-09-07
canonical: /docs/assets/comparison-directions
---
# Comparison Directions
## Definition
A Comparison Direction is a reusable project Asset that describes how candidate outputs should differ during comparative expert work. It can focus attention on a meaningful contrast such as evidence grounding, uncertainty handling, or response strategy without declaring which candidate is correct.
Comparison Directions are project-scoped. A Contribution can select or allow a pool of directions for its comparative component, while the benchmark Contribution still owns the objective, cases, candidates, and expert task.
## Fields, states, or lifecycle rules
- A direction has a name or label and a description of the intended contrast.
- Users can create, edit, pin, archive, and remove directions from **Assets → Comparison Directions**.
- Pinned directions are surfaced when a Contribution request selects comparative output guidance.
- The suggestion experience creates draft candidates in a suggestion run. Nothing enters the reusable library until a user accepts it.
- A direction can carry a staleness advisory when its source context has changed. Dismissing that advisory records a review decision; it does not approve a Policy, Rubric, Case, or Benchmark.
- A direction guides comparative presentation or generation. It does not create a Case, change coverage structure, or replace expert judgment.
## Correct scope
Use Dimensions, Project Topics, and Case Construction Patterns for the behavior space a benchmark should represent. Use Comparison Directions for how candidate outputs should be contrasted within a comparative Contribution. Use Correctness Governance for the approved standard that determines how an output is judged.
{% example-demo title="Example: source-grounding contrast" %}
A project creates one Comparison Direction asking for a response that cites the current source conservatively and another asking for a focused clarification when the source hierarchy is unresolved. A comparative Contribution can use those directions to elicit an expert preference. The direction does not approve either response or create the governing rubric.
{% /example-demo %}
## Source confidence
Code-backed: the active Assets routes expose the Comparison Directions library, detail controls, suggestion runs, accept or dismiss decisions, pinning, and staleness review. The API keeps legacy compatibility names internally, but this page uses the current product label.
## Related task pages
{% related-card-grid title="Related task pages" %}
- [Assets](/docs/assets)
- [Request an Expert Contribution](/docs/expert-contributions/request-contribution)
- [Manage benchmark coverage](/docs/coverage-management)
{% /related-card-grid %}
---
id: expert-contributions.artifacts
title: Contributed Artifacts
summary: Inspect policies, rubrics, cases, and coverage observations produced through attributable expert contribution work.
kind: reference
product_area: expert_contributions
status: stable
updated: 2026-09-07
canonical: /docs/expert-contributions/contributed-artifacts
---
# Contributed Artifacts
## Definition
Contributed Artifacts is the benchmark workspace for inspecting durable material produced through Expert Contributions. It organizes contributed **Policies**, **Rubrics**, **Cases**, and **new coverage observations** while preserving their relationship to the Contribution and expert work that produced them.
The view is a provenance and reconciliation surface. The final owner of a materialized artifact remains Correctness Governance, Assets, or Coverage Management according to artifact type.
## Fields, states, or lifecycle rules
- Policy contributions represent expert-grounded behavior rules or revisions.
- Rubric contributions represent proposed or accepted evaluation criteria tied to specialist judgment.
- Case contributions represent situations supplied or corrected through expert work.
- Coverage observations identify missing, thin, conflicting, or newly important benchmark behavior.
- A coverage observation preserves its source, proposed facet applications, and application status so an operator can distinguish a recorded observation from one incorporated into coverage structure.
- Each artifact should remain traceable to the Contribution, expert, selected evidence, task responses, and checkpoints that support it.
- Contribution completion and artifact governance are separate transitions. Inspect the artifact's owning surface before treating it as active policy, active rubric, benchmark dataset membership, or resolved coverage.
- Reconciliation can accept, revise, route, or leave material unresolved according to the active workflow.
## Interpreting contributed material
Use the artifact type to choose the next surface. A contributed policy or rubric belongs in Correctness Governance. A contributed case belongs in the project Assets pool before benchmark selection. A coverage observation belongs in Coverage Management and may motivate a Coverage Story, case construction, or another focused Contribution.
Preserve disagreements. Two experts can contribute conflicting Policy interpretations, and the artifact view should help an operator trace each interpretation rather than merge them into an invented consensus. Materialization should keep the Contribution, activity, checkpoint, expert, and scoped evidence links needed to explain why the artifact exists.
{% example-demo title="Example: contribution provenance" %}
An expert contributes a policy limiting compatibility claims, a rubric for explicit uncertainty, and a new case involving an unsupported adapter. The policy and rubric move to Correctness Governance for their lifecycle. The case enters Assets and is later selected into a benchmark dataset snapshot. All three retain the Contribution as their provenance.
{% /example-demo %}
## Source confidence
Code-backed: the active Contributed Artifacts workspace exposes policy, rubric, case, and new-coverage groupings. This page preserves the separation between contribution provenance and the lifecycle of each owning artifact.
## Related task pages
{% related-card-grid title="Related task pages" %}
- [Request an Expert Contribution](/docs/expert-contributions/request-contribution)
- [Complete an Expert Contribution](/docs/expert-contributions/complete-contribution)
- [Build policies and rubrics](/docs/operating-manual/build-policies-and-rubrics)
{% /related-card-grid %}