Timeout
A limit on how long a caller will wait before treating an operation as failed. A timeout ends the wait; it only stops the underlying work when cancellation is propagated.
The concept index
Definitions are grouped into reader-facing learning areas and linked to the stories where each concept becomes load-bearing.
28defined concepts
28covered by stories
0planned for coverage
15learning areas represented
Retry
A new attempt after a failed one. Retries help with transient faults, but they add load and can repeat side effects unless the operation is safe to retry.
Exponential backoff
A retry schedule in which the delay grows exponentially after each failure, usually up to a cap. It reduces pressure on a dependency that is still unhealthy.
Jitter
Random variation added to retry delays so many clients do not retry in lockstep. It spreads recovery traffic over time instead of creating another spike.
Retry storm
A feedback loop where failed requests trigger enough retries to raise load, deepen the failure, and delay recovery.
Circuit breaker
A stateful guard that stops calls to a failing dependency for a limited time, then probes for recovery. It protects both systems; it is not another retry mechanism.
Closed / open / half-open states
Closed allows calls and records outcomes. Open rejects calls immediately. After a cooldown, half-open admits a small number of probes and uses their results to close or reopen the circuit.
Fallback / degraded response
A deliberately reduced result returned when the preferred dependency or path is unavailable—for example, cached data without personalization.
Parametric vs non-parametric knowledge
Parametric knowledge is encoded implicitly in a model’s learned weights. Non-parametric knowledge lives outside the model—such as in documents or an index—and is fetched when needed. External knowledge can be revised without retraining the model.
Retrieval-augmented generation
A generation pattern that retrieves relevant external information for the current query and includes it in the model’s input before the answer is generated. Retrieval changes the context, not the model’s weights.
RAG vs fine-tuning
RAG supplies external knowledge at inference time; fine-tuning changes model weights through training. Use retrieval as the default for changing, sourceable facts and fine-tuning for learned behavior, format, or task adaptation. They can be combined.
Indexing pipeline vs query pipeline
The indexing pipeline prepares source content before questions arrive: load, split, enrich, and store it. The query pipeline runs per request: interpret the question, retrieve evidence, assemble context, generate, and validate the answer.
Grounding
Connecting generated claims to supplied evidence or an authoritative external source. Grounding makes answers inspectable and can reduce unsupported claims, but retrieval and generation can still fail.
State persistence and checkpointing
Persisting workflow progress so a long-running agent can resume after waiting or process loss. A checkpoint records completed orchestration state; it does not prove that an unacknowledged external effect failed or that the outside world is still unchanged.
Idempotency key
A stable caller-provided identifier for one logical operation. Repeating the same request with the same key lets the receiver suppress an additional effect within its documented scope and retention window; a new key represents new intent.
Exactly-once semantics
A guarantee that one logical operation is applied once inside a stated boundary, usually by combining atomic state changes, deduplication, or idempotency. A workflow or broker guarantee does not automatically make a separate external side effect exactly once.
Fencing token
A monotonically increasing epoch attached to work on a protected resource. The resource or gateway rejects requests carrying an older epoch, preventing a stale lease holder from beginning new effects after a successor takes over.
Trajectory vs end-state evaluation
End-state evaluation checks where the task finished. Trajectory evaluation also checks the actions, observations, policy decisions, costs, and prohibited intermediate effects used to get there. A correct final state can follow an unacceptable path.
Privilege composition
The broader capability created when several individually permitted operations can be chained. Local least-privilege checks do not establish that the complete path or resulting effect is authorized.
Source-to-sink authorization
An authorization decision over the complete path from protected input through transformations to a consequential destination. It checks whether this data may reach this sink for the current purpose, not only whether each intermediate tool call is allowed.
Record-subject binding
The supported relationship between a versioned record and the person or entity it concerns. A model may propose this relationship from semantic evidence, but release authority requires corroborating source metadata, policy, or explicit review.
Effect-bound approval
Human authorization tied to one canonical proposed effect: its target, parameters, evidence, constraints, destination, and expiry. A material change creates a new approval question instead of inheriting consent from the surrounding task.
Execution-time authorization
Re-evaluating current principal, workload, resource, purpose, policy, approval, and effect immediately before a consequential action. Permission observed during planning or approval is historical evidence, not automatic present authority.
Decision policy
A versioned rule that maps model evidence, thresholds, current context, capacity, and constraints into an action such as automate, inspect, review, defer, or abstain. The model supplies evidence; the policy owns the action boundary.
Shadow evaluation
Running a candidate model beside the live system without letting it control production actions. This limits exposure, but observed outcomes still reflect the incumbent policy unless the evaluation creates an independent evidence path.
Selective labels
Labels observed for a non-random subset because a prior decision policy determines which cases receive the action, inspection, approval, review, or follow-up that can reveal an outcome.
Sampling frame
The explicit register of eligible units available for selection into a sample. It is distinct from the target population, the design that chooses units from the frame, and the observed cohort that actually produces usable labels.
Disagreement canary
A bounded live policy that deliberately acquires evidence where an incumbent and candidate would choose different actions. It can estimate value in that disagreement region, but it does not establish whole-population model quality.