All capability theses

A use case to evaluate

Prioritize logs for deeper analysis

With Jev, an agent can suggest which supplied log records deserve closer inspection.

A human example

A diagnostic bundle contains repeated routine events and one unusual warning.

What the caller supplies

The caller marks protected records and supplies IDs, severities and bodies.

What happens next

The service advises on inspection priority while the caller retains the full archive.

Illustrative example, not a recorded result.

Potential value: low

May help some noisy workloads, but our conservative study added cost and simple severity protection explained an apparent win.

Evidence confidence: low

The available first-party study does not demonstrate net savings.

The rating describes support for this claim. It is separate from Jev's returned probability. How we assign ratings.

Evidence, including disagreement

The next test

This protocol is planned. Its outcome is not yet known.

50 incident bundles with incident-level labels, repeated records and relevant low-severity clues.

Compare against

  • Severity rules
  • Exact reuse
  • Read all records

Measure

  • Incident recall
  • Analysis volume
  • Actual downstream cost
  • Missed clues

Decision after the test

Reject any policy that hides a critical clue. Require demonstrated downstream savings before selling it as a cost feature.

The report will retain inputs, question versions, every attempt and failure examples. We will update the confidence rating after reviewing the result.

Use a related Engine recipe

Recipes are implementation starting points. Their presence does not mean the protocol above has passed.

Read or improve this thesis on GitHub.