LEN-0180 - Determinism Lens

Primary Pattern Matches

• PAT-0210 - Non-Deterministic Execution

  A structural condition where equivalent inputs and declared constraints produce divergent outputs across executions.

• PAT-0380 - Silent Mutation

  A structural condition where a change occurs without a corresponding declared update, authority update, or version change.

Secondary Pattern Matches

• PAT-0170 - Constraints Underspecified

  A structural condition where declared constraints are insufficient to eliminate ambiguity or multiple admissible states.

• PAT-0190 - Contract Drift

  A structural condition where a declared contract changes but connected structures, implementations, consumers, or expectations do not update in sync.

• PAT-0290 - Divergent Outputs

  A structural condition where parallel evaluations under comparable scope and shared authority produce non-equivalent outputs.

• PAT-0350 - Persistence Instability

  A structural condition where persisted state cannot be stored and restored into an equivalent structure without alteration.

• PAT-0200 - Reference Instability

  A structural condition where references, identifiers, links, or anchors change across equivalent evaluations without a declared cause.

Related Issues

• Actual Policy Differs From Declared Policy

  The policy the AI or workflow actually follows differs from the policy that is documented, declared, displayed, or expected.

• AI Forgets Earlier Constraints

  A constraint, instruction, preference, or decision that should persist through the task stops affecting later output.

• AI Memory Has No Governance

  Saved or persistent AI memory affects output without clear rules for ownership, scope, review, update, expiry, or removal.

• AI Memory Updated Without Asking

  AI memory, saved context, preference, or durable state is updated without the user clearly asking for or approving that update.

• Answer Has No Traceable Source Link

  The answer makes a claim, recommendation, citation, or factual statement without a source link or trace path that allows the user to verify where it came from.

• Answer Has Too Many Paths

  The answer presents too many possible paths, interpretations, options, or next steps without enough structure to choose among them.

• Cannot Identify Authoritative State

  The user or workflow cannot tell which state, version, review result, decision, source, or output is currently authoritative.

• Citation Points to Wrong Source

  A citation, reference, link, or source pointer is present, but it points to the wrong source, wrong passage, wrong document, or unsupported evidence.

• Context Changes After Restore

  Restoring, reopening, resuming, or reloading a task changes the context that the AI uses to continue the work.

• Context Leaks Between Tasks

  Context, assumptions, constraints, examples, files, or decisions from one task affect another task where they should not apply.

• Diagnostic Area Has No Coverage

  A known diagnostic area, failure mode, requirement, or review dimension has no Issue, check, rubric item, or workflow coverage.

• Early Model Output Gets Overweighted Downstream

  An early AI output receives too much authority in later workflow steps, decisions, reviews, or generated artifacts.

• Evaluation Rubric Has Coverage Gap

  An evaluation rubric, grading standard, or review checklist leaves part of the required evaluation space uncovered.

• File-Bounded Task Uses Outside Content

  The AI is asked to work only from a specific file or document but uses content, assumptions, or sources outside that file.

• Format Rule Too Weak

  The format instruction is too vague, incomplete, or optional to reliably produce output that satisfies the expected structure.

• Invalid JSON Output

  The AI returns malformed JSON or structured output that cannot be parsed.

• Missing Fallback for Unavailable Information

  The task does not declare what the AI should do when required information, sources, tools, fields, or evidence are unavailable.

• Old Output Expectations Survive Migration

  Expectations from a prior model, prompt, schema, tool, or workflow survive a migration and continue shaping review or downstream handling after they should be replaced.

• One Prompt Carries Too Many Meanings

  A single prompt carries too many meanings, goals, roles, constraints, or implied tasks for the AI to interpret consistently.

• Output Breaks After Model Change

  Output that previously worked begins failing after a model, mode, runtime, or product behavior changes.

• Output Changed Without Declared Change

  Output shape, content, format, fields, or behavior changes without a declared change to the prompt, schema, model, workflow, or governing rule.

• Output Exceeds Length Limit

  The AI output exceeds a declared length, token, word, character, section, field, or size limit.

• Parallel Reviews Never Agree

  Parallel AI, human, workflow, or tool reviews keep producing different results without resolving into a shared decision state.

• Policy Area Has No Examples

  A policy, rule, standard, or guidance area has no examples showing how it should apply to real cases.

• Policy Update Not Reflected in Output

  A policy, rule, standard, or instruction has been updated, but the AI output still follows the older version.

• Prompt Behavior Changed Without Version Change

  A prompt begins producing different behavior even though no prompt version, model version, workflow version, or declared dependency change is recorded.

• Prompt Changed but Workflow Did Not

  A prompt changes but the workflow, parser, review step, routing rule, or downstream expectation still assumes the old prompt behavior.

• Prompt Does Not Say What to Exclude

  The prompt declares what to include but does not declare what should be excluded, allowing unwanted scope, sources, content, or actions into the result.

• Prompt Has Too Many Valid Interpretations

  The prompt allows too many reasonable interpretations, causing the AI to choose among valid paths without enough guidance.

• Prompt Only Works After Retry

  The prompt fails, misroutes, or produces an unusable response on one attempt but works after retry without a meaningful change to the input.

• Relationship Map Has Missing Links

  A map of related Issues, rules, patterns, cases, fields, tools, or workflow steps is missing links needed to navigate or reason over the structure.

• Repeated Constraints Create Confusion

  Repeated constraints, instructions, limits, or exclusions make the task harder to interpret instead of clearer.

• Results Vary Too Much

  Repeated or comparable runs produce outputs that vary more than the task, workflow, or user can tolerate.

• Retry Makes the Problem Worse

  A retry, repair attempt, regeneration, or follow-up instruction increases the error, expands the failure, or creates additional breakage instead of narrowing the problem.

• Review Rubric Missing Required Criteria

  A review rubric, grading rule, evaluation checklist, or classification standard lacks criteria required to make the review reliable.

• Revoked Approval Still Treated as Active

  An approval, permission, exception, or authorization that was revoked continues to affect AI behavior or workflow decisions as if it were still active.

• Rubric Changed but Results Did Not

  A review rubric, scoring rule, evaluation standard, or classification criterion changes, but AI results continue to reflect the old rubric.

• Same Contract Name Has Different Meanings

  The same prompt, schema, field, policy, tool, or workflow contract name is used in different places with different meanings.

• Same Instructions Allow Different Outputs

  The same instructions are broad or underspecified enough to allow materially different outputs that all appear compliant.

• Same Rule Declared in Multiple Places

  The same rule, constraint, instruction, or policy appears in multiple places, creating redundancy and possible drift.

• Saved Memory Not Used

  A saved memory, preference, instruction, or durable context item exists but does not affect the AI output when it should.

• Saved Reference No Longer Works

  A saved source, citation, file reference, prompt reference, or workflow pointer previously worked but no longer resolves to the expected object or meaning.

• Schema Reference Loops Without Base Case

  A schema, field, type, object, or structured reference points through a loop without a base case that allows validation or interpretation to resolve.

• Similar Cases Route to Different Outcomes

  Similar inputs, cases, prompts, or workflow states are routed to different outcomes without a declared difference that explains the split.

• Small Change Produces Large Downstream Effects

  A small prompt, schema, policy, output, or workflow change creates unexpectedly large effects in downstream steps.

• Stale Context Affects Output

  Old context, prior instructions, outdated references, or earlier task state continue to affect output after they should no longer apply.

• Task Has No Clear Limit

  The task does not declare where the AI should stop, what is out of scope, or what counts as enough work.

• Task Progress Is Lost Midway

  The AI loses track of completed work, prior decisions, current position, or remaining steps before the task is finished.

• Tool Exists but Required Inputs Are Missing

  A usable tool or integration exists, but the AI or agent does not have the required inputs, permissions, fields, identifiers, or context needed to call it correctly.

• Tool Result Not Integrated Correctly

  The AI receives a tool result but misreads, ignores, overwrites, misplaces, or fails to incorporate it correctly into the final output or workflow state.

• Validation Result Changes on Retry

  A validation, grading, review, classification, or pass/fail result changes after retry even though the input and declared validation rules did not change.

• Version Change Breaks Existing Prompt

  A prompt that previously produced usable results stops working after a version change in the model, tool, policy, schema, product surface, or workflow.

• Workflow Step Lacks Required Conditions

  A workflow step can run, route, approve, reject, or continue without the required conditions being declared or checked.

Ontology Metadata

Code

LEN-0180

Version

LEN-0180@0.1.0

Ontology release

0.1.0

Updated

2026-05-10T00:00:00Z

History

• 0.1.0 — 2026-05-10T00:00:00Z — Created

  Promoted reviewed Lens ontology entry: Determinism Lens.

  Receipt impact: None

View full ontology changelog