Expert inquiry plan
Core platform
Correctness Elicitation
Make in-house judgment executable without making experts write the entire specification.
Teammately agents prepare focused comparisons, model outcomes, and questions; specialists decide where their judgment matters; the platform structures those decisions into policies, applicability conditions, exceptions, and binary rubrics.
Starts withCases, comparisons, expert decisions
CreatesApproved policies and rubrics
Why it exists
The standard is usually tacit—and a blank form will not reveal it.
Experienced specialists recognize good behavior through context, tradeoffs, exceptions, and patterns learned over years. Asking them to author exhaustive policies or annotate endless outputs wastes the expertise you need most. Correctness Elicitation uses active, case-grounded inquiry to surface the smallest set of decisions that clarify the standard, then keeps specialists in control of what becomes executable.
InputCases, comparisons, expert decisions
Contextual decisions
Candidate correctness spec
Reusable outputApproved policies and rubrics
How it works
A controlled path from internal context to development evidence.
Select high-information decisions
Use coverage gaps, disagreement, and model behavior to find cases where specialist judgment can change the specification.
Expert inquiry plan
Elicit judgment in context
Present targeted comparisons, curated outcomes, short chat prompts, or structured interviews instead of blank rubric forms.
Contextual decisions
Structure the emerging standard
Agents organize decisions into candidate policies, applicability conditions, exceptions, and binary rubrics.
Candidate correctness spec
Align, approve, and preserve
Specialists resolve material disagreements and ratify the language at explicit checkpoints with decision provenance intact.
Approved executable standard
Durable outputs
Not another disconnected dashboard. A reusable correctness asset.
Policy library
Explicit statements of intended behavior grounded in actual expert decisions rather than generic evaluation criteria.
Applicability conditions
The context that determines when a policy or rubric applies—and when a different exception or escalation path takes precedence.
Binary rubrics
Clear, testable statements that model and agent outcomes can be evaluated against consistently.
Decision provenance
The cases, specialist input, disagreements, and approvals behind each correctness statement.
Division of work
Agents scale preparation. People retain judgment and control.
Domain specialists
Contributes
Judge consequential comparisons, explain exceptions, qualify uncertainty, and approve the final correctness language.
Gets back
Their expertise becomes reusable without turning them into full-time rubric authors.
AI engineering team
Contributes
Frames the behavior under development, selects integration points, and keeps the specification useful for evaluation and change.
Gets back
A correctness target detailed enough to guide models, agents, and harnesses.
Teammately agents
Contributes
Prepare cases, curate comparisons, conduct structured inquiries, synthesize candidate rules, and surface unresolved disagreement.
Gets back
Less expert time spent on preparation, transcription, and repeated explanation.
Decisions it supports
Questions your team should be able to answer with evidence.
What does “correct” mean in this exact context?
Move beyond faithfulness or preference scores to the standards and exceptions held inside your organization.
Which policy applies to this case?
Make applicability and precedence explicit enough to test instead of leaving them implicit in expert intuition.
Where do qualified specialists disagree?
Preserve disagreement as a signal for clarification, scope changes, or an explicit escalation rule.
What requires accountable human review?
Encode boundaries where uncertainty or consequence makes escalation part of correct behavior.
Connected infrastructure
Carry the work forward instead of starting over at every stage.
Turn the judgment already inside your company into a development standard.
Bring one consequential behavior, one expert group, and the development evidence you already have. We’ll help map the correctness workflow around them.