All capability theses

A use case to evaluate

Keep useful parts of a long agent session

With Jev, an agent can propose which old tool records to retain for the next task step.

A human example

A long debugging session contains repeated file reads alongside one failed attempt that must not be forgotten.

What the caller supplies

The caller supplies bounded records and the current goal while preserving the original session.

What happens next

Jev recommends keep or review. The agent can recover all records and retains instructions through deterministic rules.

Illustrative example, not a recorded result.

Potential value: high

Context pressure is common for frequent coding-agent users. A reliable selector could make long tasks easier to continue.

Evidence confidence: low

Firsthand Reddit enthusiasm and conflicting X previews establish interest, not successful compaction or lower total cost.

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.

20 consented or purpose-authored long sessions, each with later questions about decisions, constraints and failed attempts.

Compare against

  • Existing agent compaction
  • Deterministic deduplication
  • No selection

Measure

  • Later task success
  • Lost constraints
  • Repeated failed actions
  • Cache rewrite cost
  • Recovery reads

Decision after the test

Do not automate destructive history edits. Retain the experiment only if task continuity matches the baseline and total cost or time improves.

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.