Field-Learning Register

Field-Learning Register

Read Field-Learning Register: templates guidance with evidence limits, practical checks and editable source material.

Use one record per candidate learning. Store source evidence in its governed system; link only the minimum sanitized evidence needed for triage and validation.

Register identity

Field Value
Register owner
Product/platform triage owner
Customer confidentiality approver
Review cadence
Evidence retention policy

Index

Learning ID Short claim Class Recurrence Confidentiality Destination Destination owner Disposition Validation status Review due

Learning record

Identity and observation

Field Value
Learning ID and revision
First / last observed
Reporting workflow, release, segment, and environment
Operational decision or invariant affected
Sanitized candidate claim
Class Customer configuration / reusable pattern / platform gap / model limitation / operating problem / non-viable use case
Reporter and triage owner

Recurrence and evidence

Field Value
Recurrence class One case / repeated within segment / cross-segment / cross-workflow / cross-customer
Occurrence count and eligible denominator
Time window and query/source revision
Affected and unaffected slices
Supporting evidence links and digests
Counter-evidence and alternative explanations
First divergent state or violated invariant
Sanitized replay/regression case
Comparable deployment or workflow cohort
Observed workflow variant and comparator
Variant class Policy-required / segment-specific / role-specific / system-constrained / accidental dysfunction
Standardization eligibility Ineligible / comparable cohort / candidate after remediation
Local constraints and validation that must remain Policy / data / security / evaluation / release / adoption / support / ownership
Target-specific delivery and support effort
Customer-specific effort ratio and prior comparable result
Existing governed artifact reused, exact version, and prior scope
Target revalidation, residual differences, and resulting disposition
Recurrence confidence and reviewer

Confidentiality and portability

Field Value
Source classification Public / internal / confidential / restricted
Customer-specific data, policy, or workflow detail present
Sanitization or abstraction performed
Confidentiality approver and date
Permitted audience and destination Customer only / product team / shared repository / public
Reuse constraints and prohibited transfer
Portable scope boundary

Ownership and reuse rights

Field Value
Customer-funded or jointly developed work Yes / no / mixed / unknown
Contract and statement-of-work reference
Intellectual-property owner and permitted uses
License, attribution, confidentiality, or publication constraints
Evidence and code that must remain target-specific
Sanitized reusable subject and provenance
Reuse decision owner, legal/contract reviewer when required, and date
Reuse status Cleared / restricted / pending / prohibited

Do not move raw customer data, proprietary policy, credentials, identifiers, or confidential workflow detail into a shared or public destination. A cross-customer recurrence label records independently reviewed evidence; it does not authorize evidence transfer between customers.

Destination and disposition

Field Value
Destination Customer configuration / target-owned extension / product backlog / platform backlog / pattern / blueprint / template / tool contract / evaluation suite / model-routing policy / operating procedure / temporary-asset retirement record
Destination owner
Disposition Investigate / configure / fix / productize / standardize / defer / reject / retire
Decision, rationale, and approver
Target artifact, issue, or release
Productization and ongoing maintenance cost
Expected effect on future delivery time, support load, quality, safety, or full cost
Required artifact owner and lineage update
Due date or reconsideration trigger
Existing parallel or shadow asset, owner, and deadline None / —

Validation and closure

Field Value
Validation hypothesis
Representative and negative cases
Independent holdout or comparison
Acceptance and guardrail thresholds
Affected-route evaluation and security regression
Pilot/canary segment, soak, and rollback trigger
Observed outcome and uncertainty
Validation owner / reviewer / date
Status Proposed / triaged / validating / accepted / implemented / rejected / deferred / retired
Closure evidence and next recurrence query

An accepted learning changes production only through its destination's normal architecture, security, review, compatible-release, evaluation, approval, support, and rollback gates. The learning record is evidence for a decision; it is not release authorization. Recurrence does not establish ownership, license, confidentiality clearance, or reuse permission.

A lower customer-specific effort ratio is useful only when outcomes, adoption, safety, supportability, and full cost remain healthy across comparable contexts. Template reuse, copied customer policy, or skipped local validation does not establish product leverage.

Standardization is a field-learning disposition, not permission to flatten variation. Preserve policy-required, segment-specific, role-specific, and system-constrained differences. Repair accidental dysfunction before treating the result as a reusable pattern, and retain every target's normal validation and release gates.

Evidence: R26-37, R26-45, R26-54, R26-70, and R26-71.