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.
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, Comparison Directions, Using Expert Judgment, Using Checkpoints, and Noisy AI Suggestions.
Worked example
What AI Features Can and Cannot Do boundary
Start
Behavior input
- Draft suggestion
- An AI-assisted workflow proposes a new compatibility policy after reading rejected cases.
Middle
Judgment into standard
- 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.
Result
Interpretation
- Interpretation
- The AI feature accelerated preparation; the human approval boundary still controls whether the standard can govern benchmark evidence.
Worked example
Example: active AI-suggested direction
Start
Behavior input
- AI-suggested direction
- Teammately suggests a stale-source conflict Comparison Direction after project cases and ontology values show that gap.
Middle
Judgment into standard
- Allowed use
- The direction can become active immediately and can guide preview examples or future variant generation.
Result
Interpretation
- 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.
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.