Jev knowledge base·verified Sep 22, 2026

online vs offline jev evals

Choose synchronous, asynchronous or offline Jev evaluation paths based on action timing, latency, labels, cost and feedback risk.

the short answer

Run Jev online only when its result must influence a current request or immediate operational response. Run it asynchronously or offline for regression suites, backfills, audits, threshold fitting and expensive analysis. Most teams need both: offline labeled evaluation establishes validity, while online observation measures production drift. A low-latency model claim does not eliminate network, retry or action-budget constraints.

Online
Runs on or near live traffic
Synchronous
Blocks the current action path
Asynchronous
Evaluates live events after the response
Offline
Runs over a fixed or replayed dataset
Required bridge
Same versioned criterion and outcome definition

Online Is Not Synonymous with Synchronous

A completed-session evaluator can process production traffic asynchronously and still be an online monitor. A policy gate is synchronous when the action waits for its answer. Use precise terms because their reliability requirements differ: blocking paths need strict deadlines and fallbacks; offline jobs need checkpointing, reproducibility and backfill control.

PathWhen it runsCan alter current action?
Synchronous onlineBefore a live action completesYes
Asynchronous onlineAfter live evidence is emittedUsually no; can alert or affect later work
OfflineAgainst stored datasets or replay windowsNo

One Criterion Across Two Evidence Loops

01Offline datasetRepresentative labeled sessions, boundary cases and slices.
02Fit and lockVersion question, state projection, model and threshold.
03Shadow onlineEvaluate live evidence without changing behavior.
04Observe outcomesJoin delayed truth, overrides and incidents.
05ReplayInvestigate drift and evaluate the next version offline.
Offline establishes the instrument; online validates it under real operating conditions.

Budget the Complete Synchronous Path

TypeSafe reports first-party Jev latency in the tens to hundreds of milliseconds, but its launch conditions and short dense state matter. A synchronous budget includes state retrieval, serialization, network, provider queueing, retries, response validation and fallback—not only model inference.

Set a deadline from the user or tool-call SLA, then allocate per-attempt timeout and maximum retries. If the check is not essential before action, move it asynchronous. The retry guide explains why SDK per-attempt defaults can exceed a product deadline.

An Asynchronous Evaluator Needs Durable Joins

Use an idempotency key at the evaluation-job layer so delivery retries do not create duplicate logical results. Preserve attempt count and provider failures separately. A dead-letter queue must remain visible in scorable coverage; otherwise dropped hard cases can make the dashboard look better. The drift guide defines the minimum monitoring record.

01EmitThe agent runtime writes a stable session-completed event after trace data is durable.
02ProjectA worker builds versioned Jev state from referenced evidence.
03EvaluateThe worker stores the typed distribution or an explicit failure state.
04AnalyzeResults join audits, slices and recurring findings by stable IDs.
05ReconcileDelayed human labels and product outcomes attach without overwriting the original result.
The user response can finish before evaluation without losing the connection to evidence and outcomes.

Offline Labels and Online Outcomes Answer Different Questions

Offline human labels provide quick controlled truth but can differ from actual success. Online outcomes arrive later, may be missing, and can be influenced by the action the evaluator helped choose. Preserve both. For an agent task, a reviewer’s completion label and a later customer reopening the issue are different signals.

Beware selective feedback. If only low-confidence cases receive review, labels are not representative of automated cases. Randomly audit each action band and use inverse-propensity or experimental designs when routing changes which outcomes can be observed.

Choose the Path from Consequence and Recoverability

Do not put every evaluator on the request path because Jev can be fast. Synchronous coupling adds a provider dependency and new failure mode. Jev evals versus policies explains when measurement should graduate into control.

NeedRecommended path
Release regression testOffline fixed dataset
Production quality dashboardAsynchronous online evaluation
Block an irreversible tool callSynchronous policy only after offline/backtest evidence
Explore a new criterionOffline development, then online shadow
Investigate an incidentOffline replay over retained evidence

Keep Offline and Online Measurements Comparable

  • Use the same resolved model, question, criteria and state-projection versions.
  • Record whether evidence was available at decision time or added afterward.
  • Compare traffic mix, missingness, languages and tool versions.
  • Separate provider failures from valid low-confidence results.
  • Report coverage, error, latency and cost by time window and slice.

Use an Explicit Gate Before Changing the Execution Path

Passing offline tests permits observation, not automatic enforcement. A candidate should first run beside the existing workflow so online evidence can reveal traffic and instrumentation differences. Promotion criteria must be written before results are inspected; otherwise teams can move thresholds until a preferred launch decision appears. Evaluate the evaluator supplies the release scorecard.

GateRequired evidence
Offline validityHeld-out errors and calibration meet criterion-specific targets
Operational readinessTimeout, retry, invalid-response and backlog behavior has been exercised
Shadow stabilityLive distributions, missingness and slice coverage match the evaluated range
Review capacityProjected review volume fits staffed service levels
RollbackPrevious evaluator and action path can be restored without losing evidence

FAQ

Are online Jev evals always blocking?

No. They may run asynchronously on live sessions after the user response. Only synchronous gates block the current action.

Can offline replay prove a policy would have prevented an incident?

It can estimate decisions on recorded state, but cannot recreate every counterfactual behavior after an intervention. State that limitation.

Should I calibrate on live traffic?

Use representative labeled production samples, but separate development, calibration and final test sets and preserve random audits.

Why keep an offline suite after deployment?

It provides reproducible release gates, boundary fixtures and diagnosis when the model, question, state or traffic changes.

Sources

Checked against the sources below on September 22, 2026. Model versions, prices and limits change.

  1. TypeSafe AI docs: Primitives
  2. TypeSafe AI docs: State
  3. TypeSafe AI docs: Jev 1.13 jaggedness
  4. LangChain: Can Jev be a better agent evaluator?
  5. Failproof AI docs: Evaluations overview